Downshift of the Ni d band center over Ni nanoparticles in situ confined within an amorphous silicon nitride matrix.

Herein, nanocomposites made of Ni nanoparticles in situ distributed in an amorphous silicon nitride (Ni/a-Si3N4) matrix, on the one hand, and within an amorphous silicon dioxide (Ni/a-SiO2) matrix, on the other hand, were synthesized from the same Ni-modified polysilazane precursor. In both compounds, the Ni/Si atomic ratio (0.06-0.07), average Ni nanocrystallite size (7.0-7.6 nm) and micro/mesoporosity of the matrix were rigorously fixed. Hydrogen (H2)-temperature-programmed desorption (TPD) profile analysis revealed that the activation energy for H2 desorption at about 100-130 °C evaluated for the Ni/a-Si3N4 sample (47.4 kJ mol-1) was lower than that for the Ni/a-SiO2 sample (68.0 kJ mol-1). Mechanistic study with X-ray photoelectron spectroscopy (XPS) analysis and density functional theory (DFT) calculations revealed that, at Ni nanoparticle/matrix heterointerfaces, Ni becomes more covalently bonded to N atoms in the a-Si3N4 matrix compared to O atoms in the a-SiO2 matrix. Therefore, based on experimental and theoretical studies, we elucidated that nickel-nitrogen (Ni-N) interactions at the heterointerface lead to remarkable Ni d band broadening and downshifting of the d band center relative to those generated by Ni-oxygen (Ni-O) interactions at the heterointerface. This facilitates H2 desorption, as experimentally observed in the Ni/a-Si3N4 sample.

Identifying the characteristics of patients with stroke who have difficulty benefiting from gait training with the hybrid assistive limb: a retrospective cohort study.

Robot-assisted gait training is effective for walking independence in stroke rehabilitation, the hybrid assistive limb (HAL) is an example. However, gait training with HAL may not be effective for everyone, and it is not clear who is not expected to benefit. Therefore, we aimed to identify the characteristics of stroke patients who have difficulty gaining benefits from gait training with HAL. We conducted a single-institutional retrospective cohort study. The participants were 82 stroke patients who had received gait training with HAL during hospitalization. The dependent variable was the functional ambulation category (FAC) that a measure of gait independence in stroke patients, and five independent [age, National Institutes of Health Stroke Scale, Brunnstrom recovery stage (BRS), days from stroke onset, and functional independence measure total score (cognitive items)] variables were selected from previous studies and analyzed by logistic regression analysis. We evaluated the validity of logistic regression analysis by using several indicators, such as the area under the curve (AUC), and a confusion matrix. Age, days from stroke onset to HAL initiation, and BRS were identified as factors that significantly influenced walking independence through gait training with HAL. The AUC was 0.86. Furthermore, after building a confusion matrix, the calculated binary accuracy, sensitivity (recall), and specificity were 0.80, 0.80, and 0.81, respectively, indicated high accuracy. Our findings confirmed that older age, greater degree of paralysis, and delayed initiation of HAL-assisted training after stroke onset were associated with increased likelihood of walking dependence upon hospital discharge.

Low temperature in situ immobilization of nanoscale fcc and hcp polymorphic nickel particles in polymer-derived Si-C-O-N(H) to promote electrocatalytic water oxidation in alkaline media.

We synthesized nickel (Ni) nanoparticles (NPs) in a high specific surface area (SSA) p-block element-containing inorganic compound prepared via the polymer-derived ceramics (PDC) route to dispatch the obtained nanocomposite towards oxygen evolution reaction (OER). The in situ formation of Ni NPs in an amorphous silicon carboxynitride (Si-C-O-N(H)) matrix is allowed by the reactive blending of a polysilazane, NiCl2 and DMF followed by the subsequent thermolysis of the Ni : organosilicon polymer coordination complex at a temperature as low as 500 °C in flowing argon. The final nanocomposite displays a BET SSA as high as 311 m2 g-1 while the structure of the NPs corresponds to face-centred cubic (fcc) Ni along with interstitial-atom free (IAF) hexagonal close-packed (hcp) Ni as revealed by XRD. A closer look into the compound through FEG-SEM microscopy confirms the formation of pure metallic Ni, while HR-TEM imaging reveals the occurrence of Ni particles featuring a fcc phase and surrounded by carbon layers; thus, forming core-shell structures, along with Ni NPs in an IAF hcp phase. By considering that this newly synthesized material contains only Ni without doping (e.g., Fe) with a low mass loading (0.15 mg cm-2), it shows promising OER performances with an overpotential as low as 360 mV at 10 mA cm-2 according to the high SSA matrix, the presence of the IAF hcp Ni NPs and the development of core-shell structures. Given the simplicity, the flexibility, and the low cost of the proposed synthesis approach, this work opens the doors towards a new family of very active and stable high SSA nanocomposites made by the PDC route containing well dispersed and accessible non-noble transition metals for electrocatalysis applications.

Early Initiation of Exoskeletal Robotic Gait Training Improves Functional Outcomes in the Patients with Stroke: A Retrospective Observational Study.

INTRODUCTION: The effect of early initiation of gait training using hybrid assistive limb (HAL) remains unclear. This observational study aimed to investigate whether early initiation of gait training using HAL improves functional outcomes in patients with stroke. METHODS: We retrospectively analyzed patients with acute stroke admitted to our facility. HAL was used for exoskeletal robotic gait training. Study participants were median split into an early group and a late group based on the days from stroke onset to initiation of gait training using HAL. The functional outcomes, defined by the Brunnstrom recovery stage (BRS), modified Rankin Scale (mRS), and Functional Independence Measure (FIM) at discharge, were compared using propensity score-matched analysis. RESULTS: We performed a propensity score-matched analysis in 63 patients with stroke (31 from the early group and 32 from the late group), and 17 pairs were matched. There were no significant differences in discharge in the BRS of the upper limb and finger in the post-matched cohort. On the other hand, the BRS of the lower limb in the early group was significantly higher than that in the late group. In addition, the mRS, but not FIM scores, was significantly better in the early group than that in the late group. CONCLUSIONS: In conclusion, early initiation of gait training using HAL might improve the motor function of the paralyzed lower limb and disability in patients with stroke.

Does frequent use of an exoskeletal upper limb robot improve motor function in stroke patients?

PURPOSE: To determine how differences in frequency of the single-joint hybrid assistive limb (HAL-SJ) use affect the improvement of upper limb motor function and activities of daily living (ADL) in stroke patients. MATERIALS AND METHODS: Subacute stroke patients were divided into the high or low frequency of HAL-SJ use groups. The two groups were matched by propensity score, and the degree of changes 30 days after initiating HAL-SJ use was compared. A logistic regression analysis was performed to examine whether frequent use would increase the number of subjects experiencing the efficacy of more than the minimal clinically important difference (MCID) of Fugl-Meyer assessment (FMA). RESULTS: Twenty-five stroke patients were matched by propensity score, and nine pairs were matched. The high-frequency group showed a significantly superior increase to total FMA shoulder, elbow, forearm, and Barthel index compared with the low-frequency group. Logistic regression analysis revealed no significant associations between frequent use and MCID. CONCLUSIONS: The frequency of HAL-SJ use may affect the improvement of motor function and ADL ability of the upper limb with exception of the fingers and wrist. However, the frequency of intervention was not effective enough to further increase the number of subjects with clinically meaningful changes in upper limb motor function.IMPLICATIONS FOR REHABILITATIONThe current study aimed to clarify how differences in the frequency of single-joint hybrid assistive limb (HAL-SJ) use can affect the improvement of upper-limb motor functions and ADL in subacute stroke patients.Our results implied that the frequency of HAL-SJ use may influence the recovery of upper limb function.However, even if HAL-SJ is used frequently, it does not mean that more patients will achieve clinically meaningful recovery.

Clinical Prediction Rule for Identifying the Stroke Patients who will Obtain Clinically Important Improvement of Upper Limb Motor Function by Robot-Assisted Upper Limb.

BACKGROUND: The number of studies on the characteristics of patients with stroke who would benefit from robot-assisted upper limb rehabilitation is limited, and there are no clear criteria for determining which individuals should receive such treatment. The current study aimed to develop a clinical prediction rule using machine learning to identify the characteristics of patients with stroke who can the achieve minimal clinically important difference of the Fugl-Meyer Upper Extremity Evaluation (FMA-UE) after single-joint hybrid assistive limb (HAL-SJ) rehabilitation. METHODS: This study included 71 patients with subacute stroke who received HAL-SJ rehabilitation. The chi-square automatic interaction detector (CHAID) model was applied to predict improvement in upper limb motor function. Based the analysis using CHAID, age, sex, days from stroke onset to the initiation of HAL-SJ rehabilitation, and upper limb motor and cognitive functions were used as independent variables. Improvement in upper limb motor function was determined based on the minimal clinically important difference of the FMA-UE, which was used as a dependent variable. RESULTS: According to the CHAID model, the FMA-UE score during the initiation of HAL-SJ rehabilitation was the most significant predictive factor for patients who are likely to respond to the intervention. Interestingly, this therapy was more effective in patients with moderate upper limb motor dysfunction and early initiation of HAL-SJ rehabilitation. The accuracy of the CHAID model was 0.89 (95% confidence interval: 0.81-0.96). CONCLUSION: We developed a clinical prediction rule for identifying the characteristics of patients with stroke whose upper limb motor function can improve with HAL-SJ rehabilitation.

Mechanistic Investigation of the Formation of Nickel Nanocrystallites Embedded in Amorphous Silicon Nitride Nanocomposites.

Herein, we report the mechanistic investigation of the formation of nickel (Ni) nanocrystallites during the formation of amorphous silicon nitride at a temperature as low as 400 °C, using perhydropolysilazane (PHPS) as a preformed precursor and further coordinated by nickel chloride (NiCl2); thus, forming the non-noble transition metal (TM) as a potential catalyst and the support in an one-step process. It was demonstrated that NiCl2 catalyzed dehydrocoupling reactions between Si-H and N-H bonds in PHPS to afford ternary silylamino groups, which resulted in the formation of a nanocomposite precursor via complex formation: Ni(II) cation of NiCl2 coordinated the ternary silylamino ligands formed in situ. By monitoring intrinsic chemical reactions during the precursor pyrolysis under inert gas atmosphere, it was revealed that the Ni-N bond formed by a nucleophilic attack of the N atom on the Ni(II) cation center, followed by Ni nucleation below 300 °C, which was promoted by the decomposition of Ni nitride species. The latter was facilitated under the hydrogen-containing atmosphere generated by the NiCl2-catalyzed dehydrocoupling reaction. The increase of the temperature to 400 °C led to the formation of a covalently-bonded amorphous Si3N4 matrix surrounding Ni nanocrystallites.

Effects of gait training with the Hybrid Assistive Limb on gait ability in stroke patients: A systematic review of randomized controlled trials.

The Hybrid Assistive Limb (HAL) is used in training to improve walking ability for stroke patients; however, the quality of the evidence for its effects has not been fully critiqued to date. This study conducted a systematic review of randomized controlled trials to investigate the effectiveness of post-stroke gait training with the HAL. PubMed, the Cochrane Library, the Physiotherapy Evidence Database (PEDro), and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched for randomized controlled clinical trials evaluating the effect of HAL on gait training in stroke patients, published from the inception of each database until March 2021. Two authors screened the titles and abstracts of articles returned in the initial search and reviewed the full text of articles that met the selection criteria. The risk of bias was assessed using the PEDro scale. Of 273 articles retrieved from the databases, three met all inclusion criteria. One study showed that gait training using HAL improves independence in walking; however, the quality of this study was rated as 4 (medium quality). Other studies did not show improvement with HAL in walking independence. This review did not provide strong evidence to support the effectiveness of HAL in improving walking ability.

Involvement of the Rostromedial Prefrontal Cortex in Human-Robot Interaction: fNIRS Evidence From a Robot-Assisted Motor Task.

Assistive exoskeleton robots are being widely applied in neurorehabilitation to improve upper-limb motor and somatosensory functions. During robot-assisted exercises, the central nervous system appears to highly attend to external information-processing (IP) to efficiently interact with robotic assistance. However, the neural mechanisms underlying this process remain unclear. The rostromedial prefrontal cortex (rmPFC) may be the core of the executive resource allocation that generates biases in the allocation of processing resources toward an external IP according to current behavioral demands. Here, we used functional near-infrared spectroscopy to investigate the cortical activation associated with executive resource allocation during a robot-assisted motor task. During data acquisition, participants performed a right-arm motor task using elbow flexion-extension movements in three different loading conditions: robotic assistive loading (ROB), resistive loading (RES), and non-loading (NON). Participants were asked to strive for kinematic consistency in their movements. A one-way repeated measures analysis of variance and general linear model-based methods were employed to examine task-related activity. We demonstrated that hemodynamic responses in the ventral and dorsal rmPFC were higher during ROB than during NON. Moreover, greater hemodynamic responses in the ventral rmPFC were observed during ROB than during RES. Increased activation in ventral and dorsal rmPFC subregions may be involved in the executive resource allocation that prioritizes external IP during human-robot interactions. In conclusion, these findings provide novel insights regarding the involvement of executive control during a robot-assisted motor task.

A systematic review of the usefulness of magnetic resonance imaging in predicting the gait ability of stroke patients.

The usefulness of magnetic resonance imaging (MRI) in predicting gait ability in stroke patients remains unclear. Therefore, MRI evaluations have not yet been standardized in stroke rehabilitation. We performed a systematic review to consolidate evidence regarding the use of MRIs in predicting gait ability of stroke patients. The Medline, Cumulative Index to Nursing and Allied Health Literature, and SCOPUS databases were comprehensively searched. We included all literature published from each source's earliest date to August 2020. We included 19 studies: 8 were classified as structure- or function-based MRI studies and 11 as neural tract integrity-based MRI studies. Most structure- or function-based MRI studies indicated that damage to motor-related areas (primary motor cortex, corona radiata, internal capsule, and basal ganglia) or insula was related to poor gait recovery. In neural tract integrity-based MRI studies, integrity of the corticospinal tract was related to gait ability. Some studies reported predictive value of the corticoreticular pathway. All included studies had some concerns, at least one, based on the Cochrane risk of bias instrument. This review suggests that MRIs are useful in predicting gait ability of stroke patients. However, we cannot make definitive conclusion regarding the predictive value, due to the lack of quantitative evaluations.

Reductions in Muscle Strength and Range of Motion Cause Locomotion Disability via Locomotion-Related Functional Limitation in Japanese Older Adults: A Cross-Sectional Study.

BACKGROUND: Functional issues (impairments, functional limitations, and disabilities) gradually occur with age. Nonetheless, maintaining physical capability may help prevent locomotion disabilities at an older age. The present study aimed to determine whether reductions in muscle strength and range of motion (ROM) cause locomotion disability via locomotion-related functional limitations among healthy older adults. METHODS: Data from a total of 144 participants (61 men, 83 women) were analyzed. To assess locomotion disability, the locomotor domain of the activities of daily living (ADLs) survey from the Ministry of Education, Culture, Sports, Science, and Technology of Japan was used. Muscle strength (grip strength) and two ROMs (hip flexion and knee flexion) were measured. To measure locomotion-related functional limitations, participants underwent a 10 m hurdle walking test and side-step test. Thereafter, path analysis was conducted for testing the hypothetical model. The goodness of fit in the model was assessed using statistical parameters, such as the chi-square value, goodness of fit index (GFI), adjusted goodness of fit index (AGFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA). RESULTS: The analysis revealed a nonsignificant chi-square value (chi-square = 41.885; p=0.113), as well as high values of GFI (0.944), AGFI (0.904), CFI (0.970), and RMSEA (0.046), indicating that locomotion disability was caused by locomotion-related functional limitations, which were influenced by muscle strength and ROM. CONCLUSIONS: The present study demonstrated that decreased muscle strength and ROM caused locomotion disability via locomotion-related functional limitations. Older adults should participate in physical exercise programs that focus on strengthening muscles and improving ROM to counteract age-related locomotion disability.

Comparison of Supervised Machine Learning Algorithms for Classifying of Home Discharge Possibility in Convalescent Stroke Patients: A Secondary Analysis.

OBJECTIVES: Classifying the possibility of home discharge is important during stroke rehabilitation to support decision-making. There have been several studies on supervised machine learning algorithms, but only a few have compared the performance of different algorithms based on the same dataset for the classification of home discharge possibility. Therefore, we aimed to evaluate five supervised machine learning algorithms for the classification of home discharge possibility in stroke patients. MATERIALS AND METHODS: This was a secondary analysis based on the data of 481 stroke patients from the database of our institution. Five models developed by supervised machine learning algorithms, including decision tree (DT), linear discriminant analysis (LDA), k-nearest neighbors (k-NN), support vector machine (SVM), and random forest (RF) were compared by constructing a classification system based on the same dataset. Several parameters including classification accuracy, area under the curve (AUC), and F1 score (a weighted average of precision and recall) were used for model evaluation. RESULTS: The k-NN model had the best classification accuracy (84.0%) with a moderate AUC (0.88) and F1 score (87.8). The SVM model also showed high classification accuracy (82.6%) along with the highest AUC (0.91), sensitivity (94.4), negative predictive value (87.5), and negative likelihood ratio (0.088). The DT, LDA, and RF models had high classification accuracies (≥ 79.9%) with moderate AUCs (≥ 0.84) and F1 scores (≥ 83.8). CONCLUSIONS: Regarding model performance, the k-NN and SVM seemed the best candidate algorithms for classifying the possibility of home discharge in stroke patients.

Relationship between Mobility-Related Activities of Daily Living and Health-Related Quality of Life among Healthy Older Adults: A Cross-Sectional Study Using Structural Equation Modeling.

Objective: To develop a conceptual model that confirms whether mobility-related activities of daily living (ADLs) abilities are strongly associated with reduced health-related quality of life (HRQOL) in older adults. Methods: A total of 153 participants (63 men, 90 women) were analyzed. The mobility-related ADL survey from the Ministry of Education, Culture, Sports, Science, and Technology of Japan was used. The Japanese version (v1.2) of the Medical Outcomes Study 36-item Short-Form Health Survey was administered to evaluate HRQOL. Structural equation modeling was performed to test a hypothetical model: mobility-related ADL abilities would influence HRQOL. Results: The chi-square value was not significant (chi-square = 9.463, p = .305), and goodness-of-fit values were high, implying that the model was validated; goodness-of-fit index, 0.981; adjusted goodness-of-fit index, 0.949; comparative fit index, 0.996; and root mean square error of approximation, 0.035. Results showed that mobility-related ADL abilities influenced the physical health including physical function and general health in HRQOL. Conclusions: This study developed the conceptual model confirming the influence of mobility-related ADL abilities especially on physical health. Further intervention studies on instructions/training for physical activity of healthy older adults should assess this causal relationship.

Machine Learning Algorithm Identifies the Importance of Environmental Factors for Hospital Discharge to Home of Stroke Patients using Wheelchair after Discharge.

BACKGROUND AND PURPOSE: Physical environmental factors are generally likely to become barriers for discharge to home of wheelchair users, compared with non-wheelchair users. However, the importance of environmental factors has not been investigated adequately. Application of machine learning technology might efficiently identify the most influential factors, although it is not easy to interpret and integrate various information including individual and environmental factors in clinical stroke rehabilitation. This study aimed to identify the influential factors affecting home discharge in the stroke patients who use a wheelchair after discharge by using machine learning technology. METHODS: This study used the rehabilitation database of our facility, which includes all stroke patients admitted into the convalescence rehabilitation ward. The chi-squared automatic interaction detection (CHAID) algorithm was used to develop a model to classify wheelchair-using stroke patients discharged to home or not-to-home. RESULTS: Among the variables, including basic information, motor functional factor, activities of daily living ability factor, and environmental factors, the CHAID model identified house renovation and the existence of sloping roads around the house as the first and second discriminators for home discharge. CONCLUSIONS: Our present results could scientifically clarify that the clinician need to focus on the physical environmental factors for achieving home discharge in the patients who use a wheelchair after discharge.

Decision Tree Algorithm Identifies Stroke Patients Likely Discharge Home After Rehabilitation Using Functional and Environmental Predictors.

BACKGROUND AND PURPOSE: The importance of environmental factors for stroke patients to achieve home discharge was not scientifically proven. There are limited studies on the application of the decision tree algorithm with various functional and environmental variables to identify stroke patients with a high possibility of home discharge. The present study aimed to identify the factors, including functional and environmental factors, affecting home discharge after stroke inpatient rehabilitation using the machine learning method. METHOD: This was a cohort study on data from the maintained database of all patients with stroke who were admitted to the convalescence rehabilitation ward of our facility. In total, 1125 stroke patients were investigated. We developed three classification and regression tree (CART) models to identify the possibility of home discharge after inpatient rehabilitation. RESULTS: Among three models, CART model incorporating basic information, functional factor, and environmental factor variables achieved the highest accuracy for identification of home discharge. This model identified FIM dressing of the upper body (score of ≤2 or >2) as the first single discriminator for home discharge. Performing house renovation was associated with a high possibility of home discharge even in patients with stroke who had a poor FIM score in the ability to dress the upper body (≤2) at admission into the convalescence rehabilitation ward. Interestingly, many patients who performed house renovation have achieved home discharge regardless of the degree of lower limb paralysis. CONCLUSION: We identified the influential factors for realizing home discharge using the decision tree algorithm, including environmental factors, in patients with convalescent stroke.

Low temperature in situ formation of cobalt in silicon nitride toward functional nitride nanocomposites.

This work highlights the first demonstration of a low-temperature in situ formation of Co nanocrystallites embedded within an amorphous silicon nitride matrix through careful control of the chemistry behind material design using perhydropolysilazane (PHPS) as a Si3N4 precursor further coordinated with CoCl2 and ammonia as a pyrolysis atmosphere. The Co nucleation was allowed to proceed at temperatures as low as 400 °C via thermal decomposition of Co2N pre-formed in situ by the reaction of CoCl2 with the Si centers of PHPS at the early stage of pyrolysis (220-350 °C).

Intravitreal Aflibercept in Japanese Patients with Neovascular Glaucoma: The VEGA Randomized Clinical Trial.

INTRODUCTION: Neovascular glaucoma is characterized by neovascularization of the iris and the anterior angle chamber. Intravitreal anti-vascular endothelial growth factor agents may improve intraocular pressure (IOP) and neovascularization. METHODS: The VEGA trial assessed the efficacy and safety of intravitreal aflibercept (IVT-AFL) in patients with neovascular glaucoma in a 13-week, randomized, double-masked, sham-controlled, phase 3 study performed at multiple sites in Japan that enrolled patients with anterior segment neovascularization and IOP > 25 mmHg. Patients received background therapy plus IVT-AFL (2 mg) or sham injection at baseline. Patients were re-treated if presenting with IOP > 21 mmHg and incomplete regression of iris neovascularization, receiving additional sham or IVT-AFL injections at week 1 and IVT-AFL injections at weeks 5 and/or 9. Double-masking was maintained throughout. The primary endpoint was change in IOP from baseline to week 1. RESULTS: Fifty-four patients were randomly assigned (full analysis set); the per-protocol set comprised 52 patients. At week 1, the least squares mean change in IOP was -9.9 mmHg for IVT-AFL versus -5.0 mmHg for sham [full analysis set: difference -4.9 mmHg (95% confidence interval -10.2 to 0.3; P = 0.06); per-protocol set: -5.5 mmHg (95% CI -10.8 to -0.2; P = 0.04)]. At week 1, a greater proportion of patients administered IVT-AFL versus sham achieved IOP ≤ 21 mmHg and had improved neovascularization grades. Patients in the sham group who met re-treatment criteria and received IVT-AFL at week 1 [n = 22 (81.5%)] had an additional mean IOP decrease of 9.2 mmHg by week 2, and the proportion with improvement in neovascularization grades increased from 11.5% to 69.2%. Increases in the proportion of patients with improved neovascularization grades and the proportion who achieved IOP control (≤ 21 mmHg) were also observed by week 2 in this group. Overall, 77.8% and 74.1% of patients treated with IVT-AFL and sham/IVT-AFL, respectively, received a single IVT-AFL injection. The most common ocular treatment-emergent adverse event was punctate keratitis (9.3%: 7.4% and 11.1% in the IVT-AFL and sham/IVT-AFL groups, respectively). CONCLUSIONS: IVT-AFL was associated with clinically meaningful improvements in IOP control, indicating that IVT-AFL may be a potential treatment option for patients with neovascular glaucoma. TRIAL REGISTRATION: Clinicaltrials.gov identifier, NCT02396316.

Efficacy and Safety of Intravitreal Aflibercept Injection in Japanese Patients with Neovascular Glaucoma: Outcomes from the VENERA Study.

INTRODUCTION: Neovascular glaucoma is characterized by neovascularization of the iris and anterior angle chamber. Intravitreal anti-vascular endothelial growth factor agents may decrease intraocular pressure (IOP) and improve neovascularization. The VENERA study assessed the efficacy and safety of intravitreal aflibercept (IVT-AFL) in patients with neovascular glaucoma. METHODS: This was a 5-week, single-arm, nonrandomized, open-label, phase 3 study performed at 7 study sites in Japan that enrolled Japanese patients with anterior segment neovascularization and IOP > 25 mmHg who had not undergone (within 30 days prior), nor were imminently scheduled to undergo (within 8 days following) intraocular surgeries, including panretinal photocoagulation (PRP). Patients received background therapy plus 2 mg IVT-AFL at baseline. Background therapy with systemic IOP-lowering drugs was prohibited for 3 days before day 1 and until IOP evaluation at week 1. The primary endpoint was the change in IOP from baseline to week 1 and the secondary endpoint was the proportion of patients with an improvement of ≥ 1 grade of neovascularization of the angle (NVA) from baseline to week 1. RESULTS: Sixteen patients received treatment (full analysis set); the per-protocol set comprised 15 patients. The mean IOP decreased from 34.1 mmHg at baseline to 25.8 mmHg at week 1 (mean change, -8.3 mmHg [95% confidence interval; CI -12.2 to -4.4; P = 0.0004]). At week 1, 81.3% of patients had an improvement in the grade of neovascularization of the iris (NVI) and 50.0% of patients had an improvement in NVA grade. The proportion of patients with controlled IOP (≤ 21 mmHg) was 43.8% (95% CI 19.8-70.1) at week 1, and increased to 56.3% at week 2 and 86.7% at week 5. The most common ocular treatment-emergent adverse event was eye pain, which occurred in 4 patients (25.0%). CONCLUSIONS: IVT-AFL was associated with statistically significant and clinically meaningful IOP reductions, without concomitant use of systemic IOP-lowering drugs or PRP. The safety profile was consistent with the known safety profile of IVT-AFL. These findings supplement those from the previous VEGA study, and suggest that IVT-AFL may be a potential treatment option for patients with neovascular glaucoma. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT03639675.

Reversible Redox Property of Co(III) in Amorphous Co-doped SiO2/γ-Al2O3 Layered Composites.

This paper reports on a unique reversible reducing and oxidizing (redox) property of Co(III) in Co-doped amorphous SiO2/γ-Al2O3 composites. The Fenton reaction during the H2O2-catalyzed sol-gel synthesis utilized in this study lead to the partial formation of Co(III) in addition to Co(II) within the composites. High-resolution transmission electron microscopy (HRTEM) and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) analyses for the composite powder sample with a composition of Al:Si:Co = 85:10:5 showed the amorphous state of the Co-doped SiO2 that modified γ-Al2O3 nanocrystalline surfaces. In situ X-ray absorption fine structure (XAFS) spectroscopic analysis suggested reversible redox reactions of Co species in the composite powder sample during heat-treatment under H2 at 500 °C followed by subsequent cooling to RT under Ar. Further analyses by in situ IR spectroscopy combined with cyclic temperature programmed reduction/desorption (TPR/TPD) measurements and X-ray photoelectron spectroscopic (XPS) analysis revealed that the alternating Co(III)/(II) redox reactions were associated with OH formation (hydrogenation)-deformation (dehydrogenation) of the amorphous aluminosilicate matrix formed in situ at the SiO2/γ-Al2O3 hetero interface, and the redox reactions were governed by the H2 partial pressure at 250-500 °C. As a result, a supported mesoporous γ-Al2O3/Co-doped amorphous SiO2/mesoporous γ-Al2O3 three-layered composite membrane exhibited an H2-triggered chemical valve property: mesopores under H2 flow (open) and micropores under He flow (closure) at 300-500 °C.

Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis.

BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stroke severity and patients age cannot be modified with rehabilitative treatment. There are limited clinical prediction rules (CPRs) that have been established using only changeable variables to predict the activities of daily living (ADL) dependence of stroke patients. This study aimed to develop and assess the CPRs using machine learning-based methods to identify ADL dependence in stroke patients. METHODS: In total, 1125 stroke patients were investigated. We used a maintained database of all stroke patients who were admitted to the convalescence rehabilitation ward of our facility. The classification and regression tree (CART) methodology with only the FIM subscores was used to predict the ADL dependence. RESULTS: The CART method identified FIM transfer (bed, chair, and wheelchair) (score ≤ 4.0 or > 4.0) as the best single discriminator for ADL dependence. Among those with FIM transfer (bed, chair, and wheelchair) score > 4.0, the next best predictor was FIM bathing (score ≤ 2.0 or > 2.0). Among those with FIM transfer (bed, chair, and wheelchair) score ≤ 4.0, the next predictor was FIM transfer toilet (score ≤ 3 or > 3). The accuracy of the CART model was 0.830 (95% confidence interval, 0.804-0.856). CONCLUSION: Machine learning-based CPRs with moderate predictive ability for the identification of ADL dependence in the stroke patients were developed.