Short TRs are increasingly used for fMRI as fast sequences such as simultaneous multislice excitation become available. These have been associated with apparent sensitivity improvements, although greater temporal autocorrelation at shorter TRs can inflate sensitivity measurements leading to uncertainty regarding the optimal approach.n = 10), the optimal TR was assessed at the single subject level for event‐related designs  with 4 frequencies of presentation at 4 TR values (412‐2550 ms). T‐values in the visual cortex localized in each individual were obtained and receiver operating characteristics (ROC) analysis was performed by counting voxels within and outside expected task active regions at different thresholds. This analysis was repeated using 4 different autoregressive (AR) models; SPM AR(1) and SPM AR(fast) which globally estimate autocorrelation, and fMRIstat AR(1) and AR(5) that use a local estimate.In volunteers  optimally improved event‐related fMRI performance independent of design frequency. Autoregressive models with a local as opposed to global fit performed better, while low order autoregressive models were sufficient at the optimal TR. Reduced TR sequences with much greater temporal sampling can inflate statistical results because the degrees of freedom of the data can appear much larger than standard TR sequences. However, typical analyses  assume that each data point is independent of the next, . This assumption is clearly violated in fMRI data and so autocorrelations are modelled. However, as the TR decreases (TR<<hemodynamic response function) the degree of autocorrelation increases and may become more complex both temporally  and spatially . It is, therefore, imperative to control for this autocorrelation in the data which will increase as the TR is reduced. A recent study by Sahib et alIn this study, we investigated the effect of TR and event rate on fMRI sensitivity using a visual stimulus paradigm. We sought to establish optimal TRs at the single subject level for event‐related designs with differing frequency of fMRI events by estimating false positive rates and performing an receiver operating characteristics (ROC) curve analysis. In addition, we evaluated the impact of autoregressive models on these results.22.1Ten healthy adult volunteers  participated in this study after providing informed consent.2.2To simulate varying event rates, a paradigm was used that comprised of rest blocks viewing a fixation cross, and 4 event blocks consisting of viewing the fixation cross interspersed with a checkerboard pattern which was presented with a duration of 300 ms at pseudorandom intervals. Pseudorandom intervals were generated in Matlab using a random number generator with the same seed value for each session. The checkerboard pattern is shown in Figure The paradigm consisted of a rest block of 30 s, followed alternately by four 120‐s event blocks and four 30‐s rest blocks. Each event block had a different event presentation rate (PR) of 1/60 s, 13/60 s, 26/60 s, 39/60 s presented in the same order of 26/60 s, 13/60 s, 1/60 s, and 39/60 s for each session. The range of event rates was based on epileptic discharge patterns seen in previously scanned epileptic patients,2.31‐weighted images were obtained with an MP‐RAGE sequence . Event‐related fMRI data were obtained with GE‐EPI, and a voxel size of 2.5 × 2.5 in‐plane and 2.5 mm3 slices with a 0.5‐mm gap, matrix 80 × 80, 40 slices. Four sessions of 10 min with different simultaneous multislice speed up or multiband (MB) factors were used . Structural T1 of 1000 ms as a reasonable average value between measured white and gray matter T1 values.We used a maximum MB = 4 based on previous work that demonstrated increased false positives due to aliasing artefacts at higher MB factors.2.3.1To independently define the location of the maximum response in the visual cortex of each volunteer, a 2‐min V1 localizer  was first acquired with two 40‐s blocks, alternated with 20‐s rest blocks .2.4https://www.fil.ion.ucl.ac.uk/spm) for use with both SPM and fMRIstat. Preprocessing included image realignment, which consisted of co‐registration of fMRI time series data from each session to the mean, and then smoothing with a Gaussian filter using the default SPM value (8 mm FWHM). A high‐pass filter with a cutoff frequency of 1/128 Hz was used in all analyses to mitigate low‐frequency signal components.All images were first preprocessed using statistical parametric mapping software . The global maximum from the positive t‐contrast of the visual stimulus blocks was examined and the spatial location recorded. This location for each individual was used in all subsequent analysis. Any subjects without a global maximum within visual cortex for the localizer were not considered in subsequent analysis.2.4.2https://www.math.mcgill.ca/keith/fmristat/). In both cases, the 6 realignment parameters were used as effects of no interest and the smoothed realigned images were the input data. Separate GLM models were built for each of the 4 sessions (as the data had differing TRs) with 4 separate conditions  using the timing of individual checkerboard presentations as an event relate design. These were convolved with the canonical hemodynamic response function using the default model within SPM and fMRIstat.Analysis was performed both in SPM and fMRIstat2.5st order expansion (approximately ω = 0.2) that is fitted globally to the covariance. SPMs AR(fast) uses a dictionary of exponential covariance components that are fitted globally to the covariance. We compared these with 2 AR models available within fMRIstat, which allows the order of the AR model to be selected. We chose fMRIstat AR(1) to provide a comparison of consistency with the SPM AR(1), and AR(5) based on Sahib et al.We wished to investigate how t‐values were influenced by different autoregressive models. SPM provides an AR(1) model for standard TR values and AR(fast) for use with shorter TRs. SPMs AR(1) model uses an 12.6The V1 t‐value at each PR, TR, and AR model was entered into the statistical analysis. The mean and standard deviation of the t‐value across subjects for each TR and presentation frequency combination was calculated.https://www.ibm.com/pk-en/marketplace/spss-statistics). To test the effect of TR reduction with conservative control of potential t‐value inflation at shorter TRs,P < 0.05. Mauchly's Test of Sphericity was used to test that the variances of the differences between all combinations of related groups were equal. Posthoc paired t‐tests were run to compare t‐values obtained at each TR. Significance was again taken to be P < 0.05 after Bonferroni correction.A second level analysis using a 2‐way repeated measures analysis of variance with factors TR and frequency was used to evaluate their effect on the t‐values using SPSS version 24 . For each individual, session and threshold the group level mask was applied to voxels within the brain, and a voxel count was performed. True positive voxels were those with t‐values above the threshold within the mask; false negatives were all other voxels within the mask; true negatives were voxels outside the mask below the threshold; false positives were all other voxels within the brain outside the mask. Voxel counts were averaged across subjects and turned into percentage ROC curves plotted and fitted using a 4th order Taylor series in Matlab’s curve fitting toolbox (https://uk.mathworks.com), and areas under the curve (AUC) were then calculated.An analysis of sensitivity and specificity at each TR, frequency and AR model was performed. All subjects/sessions were normalized to MNI space using the ICBM template (European) in SPM. Brain areas were defined as task positive using the group response, evaluated at 2 inclusive levels of significance , and applied as a mask to each individual’s map. Individuals activation maps were thresholded at a range of 3Of the 10 volunteers, 9/10 showed clear activation to the visual localizer with the global maxima in an anatomical location consistent with primary visual cortex, met the criteria for the study, and so were included in subsequent analysis. Figure Figure 2(2) = 4.28, P = 0.515, and frequency of presentation χ2(2) = 3.9, P = 0.56. The main effects of TR and presentation frequency showed statistically significant differences in t‐value across subjects, F = 6.69, P = 0.002, and F = 34.497, P = <0.001, respectively. There was no interaction between TR and frequency of presentation, F = 1.446, P = 0.185.The effect of frequency and TR on the t‐values in V1 was tested with a repeated measured analysis of variance. The assumption of sphericity using Mauchly’s Test was met for TR, χTo determine the optimal TR value, posthoc paired t‐tests were performed with the results shown in Table Choice of autoregressive model made a substantial difference to the measured t‐values as expected. All AR models gave consistent results at the standard TR (2550 ms). The SPM AR(1) model had larger t‐values at shorter TR values. Interestingly, this effect was not solely attributable to the low AR model order, because both the fMRIstat AR(1) and AR(5) models showed a more modest t‐values increase at shorter TR values while the use of the higher order SPM AR(fast) model did not reduce the t‐values to those seen with either fMRIstat model. The AR model coefficients for fMRIstat AR(1) and fMRIstat AR(5) are displayed in Supporting Information Table ROC curves for each TR with the most conservative model (fMRIstat AR(5)) are shown in Figure ROC curves are shown for different autoregressive models at a fixed TR 842 ms) at the lowest , shorter TRs increased the t‐value for all autoregressive models; with a conservative model (fMRIstat AR(5)) the largest t‐value increase of 75% Table  was foun1 recovery within the TR. Therefore, it might be expected that imaging with a shorter TR has a punitive effect on image signal levels that in turn, will reduce fMRI sensitivity, which is consistent with our findings. Our findings demonstrate a more moderate reduction in TR is optimal compared with some previous studies even when a similar autoregressive model was used.At shorter TRs image signal is exponentially reduced due to reduced TOur results might indicate a subtle effect of stimulation frequency on the optimal TR . The impact of subject motion on sensitivity at different TRs remains unclear and shorter TRs could be beneficial in this context although image reconstruction is typically also reliant on calibration data that does not account for subject motion.There have been several studies investigating the efficacy of SMS sequences for fMRI at the group level; Todd et alOur findings suggest that increasing the speed of data acquisition is beneficial for modest TR reductions (1000 ± 200 ms) and MB factors (2‐3); however, likely owing to the rapid loss of image signal, there are not large advantages for acquisitions with a TR below 800 ms for event‐related fMRI designs at 3T. In the context of increasing artifact levels for greater reduction factors,FIGURE S1 ROC curves for each TR for the lowest (A) and highest (B) rate of presentation obtained with conservative autocorrelation estimates (fMRIstat AR5). ROC curves were also calculated for each autoregressive model at a TR of 842 ms for the lowest (C) and highest rate of presentation (D). All ROC curves were produced using a group level mask  to determine true/false positivesTABLE S1 Autoregressive model coefficients (AR + ) used by fMRIstat in AR(1) with one coefficient, and AR(5) with five coefficients demonstrating the weighting of the coefficients at higher AR orders by TRTABLE S2 Area under the curve values for all models and TR values at the highest and lowest rates of presentation produced using a group level mask Click here for additional data file.


Psammomys obesus (P. ob.), an animal model for type 2 diabetes and DR has been used. The erythrocyte and retinal AR activity of P. ob. individuals were, respectively, assessed monthly and at the 7th month during a 7‐month hypercaloric diet (HD) using a NADPH oxidation method. Meanwhile, the body weight and blood glucose of the gerbils were monitored. After 7 months, P. ob. individuals were fed with ATX (4.8 mg/kg of body weight) once a day for 1 week. The results showed that the HD‐fed animals developed significant obesity and hyperglycemia in comparison with controls. Erythrocyte AR activity showed a progressive and significant increase in the HD‐fed group compared with controls. Retinal AR activity was higher in the 7‐month HD‐fed group compared with controls. Erythrocyte AR activity was markedly decreased after ATX‐treatment in vitro and in vivo. These findings suggested that ATX inhibited the erythrocyte AR activity and could be used for DR prevention and/or early treatment.Astaxanthin (ATX) is a marine carotenoid known for its powerful antioxidant and neuroprotective properties. In this study, we investigated the in vitro and in vivo potential inhibitory effect of ATX on the aldose reductase (AR) activity, a key enzyme in the polyol pathway responsible for the pathogenesis of diabetic complications including diabetic retinopathy (DR). The gerbil  Psammomys obesus. Our results showed that astaxanthin may prevent and treat diabetes complications.We investigated the in vitro and in vivo potential inhibitory effect of astaxanthin on the aldose reductase (AR) activity, a key enzyme in the polyol pathway responsible for the pathogenesis of diabetic complications including diabetic retinopathy (DR) in  HyperglDiabetic retinopathy (DR) is a visual deficiency that is one of the major complications of long‐term diabetes affecting approximately 4.2 million people worldwide and representing a leading cause of blindness. It is a microvascular retinal disease characterized by vascular occlusions, increased capillary permeability, loss of pericytes, microaneurism, intraretinal hemorragies, macular edema, and neovascularization , the first and rate‐limiting enzyme in this pathway belonging to the aldo‐keto reductase superfamily. It reduces the excess of glucose to sorbitol using nicotinamide adenine dinucleotide phosphate (NADPH) as cofactor. Sorbitol is then metabolized to fructose by the sorbitol dehydrogenase , a semi‐desertic rodent, is an extensively used model for nutritionally induced diabetes and metabolic syndromes  is a target for the treatment of diabetic complications. Considerable effort has been devoted to the study of several AR inhibitors extracted from the biomass and which have shown promising effect by preventing and slowing the progression of DR  is a potent natural antioxidant belonging to the xanthophyll carotenoid family occurring in crustaceans, salmons, and crabs. It is used as a dietary supplement to promote health condition. ATX has been investigated for its anti‐inflammatory  with the authorization of Tunisian Agriculture Ministry . Gerbils were transferred to animal facilities and kept in standard laboratory conditions: 12 hr light and dark cycle, a constant temperature (25 ± 2°C), relative humidity was maintained at 70 ± 10% with free access of water and food. Animal experimentation was conducted in accordance with the ethical guidelines of the Pasteur institute ethics committee of Tunisia . Animals were used and handled according to the principles of the Association for Research and Vision Ophthalmology (ARVO) Statement for the Use of Animals in Ophthalmology and Vision Research.Experiments were performed in young adult 2.2n = 7) was fed with only halophilic plants, and a HD group (n = 14) received a standard laboratory rat chow . Both groups were followed up for 7 months with measurements of body weight (every week) and plasma glucose (once a month). The animals were considered diabetic when their blood glucose levels >200 mg/dl.Animals were acclimated for a couple of weeks and received a natural vegetable diet, that is, halophilic plants rich in water and mineral salts . Data presented in this study came from two independent field excursions. Animals were divided randomly into the two following groups: a control group  and diabetic P. ob. (n = 4) was added to 90 µl of sodium phosphate buffer  containing 150 mM NaCl. The suspension was lysed by repeated freezing and thawing for three cycles  were separated by centrifugation at 5,000 2.3.2Animals were humanely sacrificed, euthanized by CO2 inhalation and then decapitated. Eyes were immediately enucleated, rinsed with alcohol and placed into binocular dissecting microscope. Lens and cornea were removed after cutting the anterior segment via an incision in the pars plana. The neural retina was gently isolated from the pigment epithelium and homogenated in 1 ml of potassium phosphate buffer . The homogenate was centrifuged at 15,000 r/min for 30 min, and the supernatant containing the enzyme fraction was kept in −20°C.2.3.3Aldose reductase activity was measured at 340 nm using a spectrophotometer and in the presence of D, L‐glyceraldehyde, a substrate of the enzyme. The assay mixture of 1 ml contained potassium phosphate buffer , 0.4 mM lithium sulfate, 5 mM mercapthoethanol, 10 mMglyceraldehyde, 10 mMNADPH, and the enzyme fractions preparations from erythrocytes or retina  and the 7‐month HD‐fed P. ob. group (n = 4) then processed as described previously. Measurement of AR activity was performed with or without 50 µg/ml of ATX  in the assay mixture dissolved in dimethyl sulfoxide (DMSO).To evaluate the effect of ATX i2.5P. ob. (n = 4) were fed 4.8 mg ATX per kg of their body weight during 7 days. To evaluate the effect of ATX on the AR activity of diabetic P. ob., blood was collected and AR activity was measured as described previously and compared with that of diabetic P. ob. untreated with ATX (n = 4) and to that of a control group (n = 4).After 7 months of HD, 2.6p value <.05 was considered statistically significant. Significance between 2 groups was determined by using two factors ANOVA for changes in body weight, blood glucose levels and the evolution of AR activity. Independent sample Student t test was used for the measurement of AR activity in retina. One way ANOVA followed by Tukey's post hoc test was used for the measurement of erythrocyte AR in vitro and in vivo. The tests were performed using the SPSS program (version 17).The results are presented as mean ± standard deviation. A 33.1P. ob. individuals of the control group did not change significantly throughout the 7‐month experimentation. Indeed, they maintained a roughly stable weight with an increase of approximately 38.06%, probably due to their condition of life in captivity (lack of activity) and/ or to a normal evolution of their weight according to age. However, the P. ob. individuals fed with HD developed a progressive increase of their body weight starting from the 2nd week of treatment with a significant gain (233.71%±34.13) of their body weight after 7 months (p < .05), in comparison with controls.The weight change, determined as a percentage of initial weight of both groups, is shown in Figure 3.2P. ob. are shown in Figure p < .05). Mean values increased from 119.75 ± 37.27 mg/dl at the start of the experimentation to 281.25 ± 95.18 mg/dl after 7 months and were classified as diabetic from the 3rd month  in AR activity compared with control animals ranging from 0.0008 U in the 4th month to 0.001 U in the 7th month in diabetic animals. Previous researches showed that the high activity of AR is caused by an increase of AR protein level  compared with P. ob. control AR activity (0.0007 U) even though the difference is not statistically significant  . Our results indicated that in vitro, ATX exhibited a significant direct inhibitory effect on erythrocyte AR activity probably by its particular structure via the polyene chain (the nonpolar part) binding to the hydrophobic site of AR slowing therefore its action.Data show a decrease of the erythrocyte AR activity of nt p > .0  in diabetics P. ob. which received a daily dose of 4.8 mg/kg of ATX for a week starting from the 7th month of HD compared with control diabetics  and reduced glial reactivity  contributed equitably to this work.All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.


The prognostic relevance of circulating tumour cells (CTCs) in metastatic breast cancer (MBC) patients has been confirmed by several clinical trials. However, predictive blood-based biomarkers for stratification of patients for targeted therapy are still lacking. The DETECT studies explore the utility of CTC phenotype for treatment decisions in patients with HER2 negative MBC. Associated with this concept is a plethora of translational projects aiming to identify potential predictive biomarkers. The androgen receptor (AR) is expressed in over 70% of hormone receptor-positive and up-to 45% of triple-negative tumours. Studies has indicated the promising nature of AR as a new therapy target with a clinical benefit rate for anti-AR treatment in MBC patients up to 25% The aim of this analysis was the characterization of CTCs regarding the expression of the AR using immunofluorescence.n = 67) an additional blood sample was used for immunomagnetic enrichment of CTCs using the CellSearch® Profile Kit prior to transfer of the cells onto cytospin slides. Establishment of immunofluorescence staining for the AR was performed using prostate cancer cell lines LNCaP and DU145 as positive and negative control, respectively. Staining of DAPI, pan-cytokeratin (CK) and CD45 was applied to identify nucleated epithelial cells as CTCs and to exclude leucocytes.MBC patients were screened for the HER2-status of CTCs in the DETECT studies. In a subset of CTC-positive patients . In 16 of these 37 patients (43%) AR-positive CTCs were detected. In eight out of 25 patients (32%) with more than one CTC, AR-positive and AR-negative CTCs were observed.In 43% of the analysed CTC samples from patients with MBC the AR expression has been detected. The predictive value of AR expression in CTCs remains to be evaluated in further trials. However, up to 45% of triple negative BC patients express the AR [Breast cancer (BC) is the most common malignancy in women, with almost 1.7 million new cases diagnosed per year . Therefos the AR . The rols the AR , 16. In s the AR –19, Mores the AR . In conts the AR . The abos the AR , 23. Thes the AR . Beyond s the AR . The clis the AR . The aimwww.detect-studien.de). DETECT III/IV study trial is a multicenter study program for patients with HER2-negative MBC and circulating tumor cells. The main objective of this study is to evaluate the efficacy of personalized breast cancer therapy based on the presence and phenotype of CTCs. The flow chart of our substudy is presented in Fig. Blood samples from 67 MBC patients, screened within the German DETECT III/IV trials  between 2012 and 2017 for the HER2-status of CTCs, were eligible for this analysis (for more information: Blood samples were drawn into 10 ml CellSave tubes (Menarini Silicon Biosystems), maintained at room temperature and processed within 72 h after collection. The CellSearch® Epithelial Cell Kit (Menarini Silicon Biosystems) was used routinely for enrichment and enumeration of CTCs as described previously . In a suCytospins were thawed at room temperature in a humid chamber for approximately 20 min and fixed with CellSave  for 10 min. After an initial wash step with PBS , cells were permeabilized with PBS containing 0.1% Triton X-100 for a period of 10 min prior to blocking with Protein Block solution  for another 10 min. The immunofluorescence stainings were performed using the Androgen Receptor (D6F11) XP rabbit monoclonal antibody  and the pan-cytokeratin (CK) antibody (C11) directly conjugated to fluorescein isothiocyanate (FITC)  for 60 min. Cytospins were subsequently incubated with a secondary donkey anti-rabbit antibody, labelled with Alexa Fluor 594  and an Alexa Fluor 647-conjugated CD45 antibody (35-Z6)  for 30 min. Nuclear DNA staining was performed with 4′6-diamidino-2-phenylindole (DAPI) in mounting media . Preparations of the prostate cancer cell line LNCaP mixed with PBMCs from a healthy volunteer served as a positive control for CK and AR staining. The AR-negative control slides of Du145/PBMC mixtures were also included with each batch of samples. CK positive, CD45 negative cells that contained an intact nucleus (DAPI positive) were identified as CTCs. Positive and negative control stainings are shown in Fig. p < 0.05 were considered statistically significant.The chi-squared test was used to evaluate the association between CTCs and clinicopathological factors. Statistical analysis was performed by SPSS (version 25). Values of Peripheral blood from 67 MBC patients screened for participation in the DETECT trial were eligible for this study. 55 patients 82%) had hormone receptor (HR)-positive/HER2-negative tumours, two cases (3%) had immunohistochemistry stainings indicating HR-positive/HER2-positive disease, and 10 patients (15%) had a triple negative breast cancer (TNBC). In 26 patients (40%) the blood draw was performed prior to the first line therapy for metastatic disease. The remaining 41 patients (60%) had progressive metastatic disease at blood sampling. The clinical data of the patients are summarized in Table % had horAt least one CTC was detected in 37 patients (56%). The CTC count ranged from 1 to 101 cells. In 16 out of the 37 CTC-positive patients (43%), AR-positive CTCs could be detected. The percentage of AR-positive CTCs among CTCs detected per patient ranged from 0 to 100% . In 5 out of 16 patients (31%) with AR-positive CTCs, the AR was localized in the nucleus whereas in 10 patients (62.5%) the AR signal was detected in the cytoplasm. Both nuclear and cytoplasmic localization were observed in only one patient (6.5%). Heterogenic AR localization in CTCs is depicted in Fig. There is growing evidence on the potential role of androgens and the AR in the pathogenesis of breast cancer. The majority of ER-positive breast cancers and up to 45% of TNBC express the AR in tumour tissue, making this biomarker an interesting therapeutic target –14. AR tThe phenotypic characterization of CTCs, which might serve as a real-time liquid biopsy, is gaining in importance. This necessitates the identification of new predictive markers for systemic treatment in patients with MBC. The AR represents such a potential therapy target, since it is being expressed in all BC subtypes. In the present analysis we established a triple fluorescent staining of the AR in CTCs. The established robust method allowed for the direct visualization of the tumour cell and showed that AR-positive CTCs can be detected in MBC patients. AR localization in CTCs can vary and may be detected both in the nucleus and cytoplasm. Whether AR-positive CTCs are suitable to serve as a therapeutic biomarker and whether the pleiotropic AR localization has an impact on the efficacy of anti-AR agents in MBC, need to be explored in future trials.


IPK is an endoplasmic reticulum (ER)-resident chaperone playing a critical role in facilitating protein folding and protein homeostasis. Previously, we have demonstrated that p58IPK is expressed broadly in retinal neurons including retinal ganglion cells (RGCs) and loss of p58IPK results in age-related RGC degeneration. In the present study, we investigate the role of p58IPK in neuroprotection by in vitro and in vivo studies using primary RGC culture and two well-established disease-relevant RGC injury models: retinal ischemia/reperfusion (I/R) and microbead-induced ocular hypertension. Our results demonstrate that in both in vivo models, p58IPK −/− mice exhibit significantly increased RGC loss compared to wild type (WT) mice. In vitro, p58IPK-deficient RGCs show reduced viability and are more susceptible to cell death induced by the ER stress inducer tunicamycin (TM). Overexpression of p58IPK by adeno-associated virus (AAV) significantly diminishes TM-induced cell death in both WT and p58IPK −/− RGCs. Interestingly, we find that loss of p58IPK leads to reduced mRNA expression, but not the protein level, of mesencephalic astrocyte-derived neurotrophic factor (MANF), a neurotrophic factor that resides in the ER. Treatment with recombinant MANF protein protects R28 retinal neural cells and mouse retinal explants from TM-induced cell death. Taken together, our study suggests that p58IPK functions as an endogenous neuroprotectant for RGCs. The mechanisms underlying p58IPK’s neuroprotective action and the potential interactions between p58IPK and MANF warrant future investigation.p58 Accumulating evidence suggests that disturbed protein homeostasis in the endoplasmic reticulum (ER), or ER stress, is a significant contributing factor to neurodegeneration in the central nervous system including the retina  genes XBP1 and ATF6 , an ER stress responsive neurotrophic factor.In the present study, we tested this hypothesis in two commonly used RGC injury models induced by retinal ischemia/reperfusion (I/R) or ocular hypertension and explored the potential mechanism of p58IPK knockout mice were previously described elsewhere  at 10∧12 GC/ml following standard procedures approved by the Institutional Biosafety Committee at the University at Buffalo. After 24 h, transduced cells were treated with 1 μg/ml tunicamycin (TM) or a vehicle control (0.05% DMSO) for an additional 16 h. Cell viability was examined using the live/dead cytotoxicity assay (Molecular Probes) following the manufacturer’s protocol. Images were analyzed for live cells (green) and dead cells (red), blind to treatment or genotype  system following a published protocol  was injected. Intraocular pressure (IOP) was recorded by bounce tonometer (Icare). Two weeks after microbead injection mice were sacrificed and retina whole-mounts were prepared for Tuj1 immunostaining  per manufacturer instructions. cDNA was made from 500 ng of total RNA using Bio-Rad cDNA kit followed by quantitative RT-PCR (qPCR) with Bio-Rad iQ Sybr Green Supermix. The following primers were used: MANF f1: 5’-CAC CAG CCA CTA TTG AAG AAG A-3’ with MANF r1: 5’-AGC ATC ATC GTG GTC CAA-3’; MANF f2: 5’-AAA GAG AAT CGG TTG TGC TAC T-3’ with MANF r2: 5’-CCA GGA TCT TCT TCA GCT CTT T-3’; 18sF 5’-GTA ACC CGT TGA ACC CCA TT-3’ with 18sR 5’-CCA TCC AAT CGG TAG TAG CG-3’.t-test for two-group comparisons and one-way ANOVA with Bonferroni post hoc test for three groups or more. Statistical differences were considered significant at a p value of less than 0.05.The quantitative data were expressed as mean ± SD. Statistical analyses were performed using Student’s IPK −/− and wild type (WT) mice using a variety of retinal cell type specific markers. We found that there was no significant difference in retinal expression of PKCα, Pax6, ribeye, or calretinin in p58IPK −/− and WT mice  followed by treatment with 5 μg/ml TM, or vehicle, for 24 h. We find TM treatment induces cell death in 43% of R28 cells in the absence of MANF treatment Figure . With MAexplants .IPK in protection of RGCs in conditions of ER stress, acute ischemia and ocular hypertension. Previous studies, including our own, have implicated p58IPK in a broad range of neurodegenerative diseases and diabetes (Ladiges et al., IPK, suffer from diabetes and multisystemic neurodegeneration (Synofzik et al., IPK results in increased ER stress and oxidative stress, decreased β cell function, progressive cell death and diabetes in male p58IPK KO mice (Ladiges et al., IPK in diabetes, how p58IPK regulates neuronal function remains unexplored. Herein, we examined the impact of p58IPK deficiency on RGC survival in disease-relevant models. Our data clearly indicate an important role of p58IPK in RGC survival during acute retinal ischemia and in ocular hypertension. Notably, we used young adult p58IPK KO mice that demonstrate no significant morphological defects in the retina compared to their age-matched littermate controls. In addition, most of our experiments were carried out in female mice at 2 months of age, which do not experience increased blood glucose levels as some male p58IPK KO mice do with age.The findings from the present study provide strong evidence for an endogenous role of p58in vitro results suggest a therapeutic potential of overexpressing p58IPK or enhancing its function for neuroprotection of RGCs, which warrants an in vivo study in disease models. Another interesting finding is that there is likely a reciprocal regulation between p58IPK and MANF in retinal cells undergoing ER stress. Recent studies show that MANF protects CNS neurons (Voutilainen et al., IPK and MANF are upregulated during ER stress; interestingly, overexpressing p58IPK reduces ER stress-stimulated MANF upregulation. This suggests a potential interaction between the two chaperones, which both bind to GRP78 and regulate the UPR, although it remains unclear whether MANF secretion is affected by p58IPK manipulation. Future studies will investigate how MANF and p58IPK are regulated in RGCs and whether overexpression of p58IPK and MANF would synergistically promote RGC survival and function.Our TM designed and performed the experiments, analyzed the data and drafted the manuscript. ND and JL performed the experiments, analyzed the data and revised the manuscript. JW and SZ conceived and designed the study, reviewed all the data, drafted and revised the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Immune checkpoint inhibitors PD-1, PD-L1, and CTLA-4 were significantly upregulated in both overall “QNBC” and AA “QNBC” patients as well. Thus, AR could be used as a prognostic marker for breast cancer, particularly in AA “QNBC” patients.There is increasing evidence that Androgen Receptor (AR) expression has prognostic usefulness in Triple negative breast cancer (TNBC), where tumors that lack AR expression are considered “Quadruple negative” Breast Cancers (“QNBC”). However, a comprehensive analysis of AR expression within all breast cancer subtypes or stratified by race has not been reported. We assessed AR mRNA expression in 925 tumors from The Cancer Genome Atlas (TCGA), and 136 tumors in 2 confirmation sets. AR protein expression was determined by immunohistochemistry in 197 tumors from a multi-institutional cohort, for a total of 1258 patients analyzed. Cox hazard ratios were used to determine correlations to PAM50 breast cancer subtypes, and TNBC subtypes. Overall, AR-negative patients are diagnosed at a younger age compared to AR-positive patients, with the average age of AA AR-negative patients being, 49. AA breast tumors express AR at lower rates compared to Whites, independent of ER and PR expression (p<0.0001). AR-negative patients have a  odds ratio of being basal-like compared to other PAM50 subtypes, and this is associated with an increased time to progression and decreased overall survival. AA “QNBC” patients predominately demonstrated BL1, BL2 and IM subtypes, with differential expression of E Among women in the United States, breast cancer is the second most common cancer. African-American (AA) women have historically had lower incidence rates relative to White women; however, recent statistics indicate that incidence rates for AA women have converged with those of White women . RelativBreast cancer is currently divided into four molecular subtypes by the presence or absence of hormone receptors [ and progesterone (PR)], along with human epidermal growth factor receptor 2 (HER2). This classification influences treatment options and correlates with clinical outcomes such as overall survival (OS) and/or recurrence-free survival , 4. VariTo determine the expression of AR and its relationship to breast cancer subtypes, we compiled a series of Gene Expression Omnibus (GEO) profiles that contained racial and clinical outcomes data totaling 1061 patients. Expression of the AR protein level was confirmed in an additional multi-institutional cohort of 197 breast cancer patients, for a total of 1258 patient evaluated. Relative to White women, AA women had higher percentage (81%) of AR-negative tumors, and, for both races, AR-negative tumors correlated with the basal subtype, a shorter time to progression, and worse OS compared to White women. For AA patients, AR-negative tumors demonstrated a distinctive molecular profile that was enriched for immune genes. 100% of AA TNBC patients were AR-negative. Use of the TNBC subtyping tool showed that, relative to White women, AA women had higher expressions of the basal-like 1 (BL1), basal-like 2 (BL2), and immune modulatory (IM) signatures. These findings suggest that AR is a prognostic marker and should be used routinely along with the standard assessments of ER, PR, and HER2 status to determine tumor aggressiveness, particularly for AA women.We assessed AR expression in a total of 1258 patient at both the mRNA and protein levels, and found that loss of AR is associated with earlier breast cancer diagnosis , a shorter time to progression, and a worst overall survival. We also observed that the absence of AR expression is more prevalent in AA women in all breast cancer subtypes, however AR loss is most frequently observed in TNBC patients, which is referred to as “QNBC”. AA “QNBC” patients have increased basal-like and immune signatures, with the IL12, CCR5, and B-cell response pathways as drivers of this signature. Our data suggest that AR should be added to the current set of ER, PR, and HER2 markers for breast cancer classification, and AA “QNBC” breast cancer patients could be candidates for immune targeted therapies.The Institutional Review Board (IRB) at Tuskegee University and the University of Alabama at Birmingham approved the experimental protocol prior to initiation of the investigation. The BMaP TMA obtained informed consent for all patients used in the generation of TMA from each institution.https://gdc-portal.nci.nih.gov/ accessed on 4/12/2016). AR-status was empirically determined using quantile ranking of AR expression across all samples, and selection of positive vs negative samples was determined by quantile thresholds. Specifically, the subsets of samples below the 25th and above 75th quantiles of the ranked data were determined to be the lowest and highest expression level categories, respectively, corresponding with negative and positive AR status , Tulane Medical Center, the University of Mississippi, Emory Medical School, Ponce Medical School, and Moffitt Cancer Center contributed tumors. All tissue microarray (TMA) slides were stained with hematoxylin and eosin (H&E), and stained slides were submitted to the analytical microscopy core for imaging and filing. The biomarker status obtained from Cancer Registry data was confirmed with stains for Her2, PR, and ER using the following antibodies from Ventana Medical Systems: 790–4324 CONFIRM anti-ER (SP1), 790–2223 CONFIRM anti-PR (1E2), 790–100 PATHWAY anti-HER-2/neu (4B5), and . IHC was performed in the Histology Laboratory at the Moffitt Cancer Center using the Ventana Benchmark XT platform following the manufacturer’s specifications.2, and the cells were grown (cell simulation at 2 μm) in all directions. Image analysis for AR-stained cores was performed using an Aperio Positive Pixel Count® v9. algorithm with the following thresholds:  to segment positive staining of various intensities. The algorithm was applied to the entire digital core image to determine the percentage of positive biomarker staining by applicable area and marked as “Percent Expression.” IHC was performed at Tuskegee University and the University of Alabama at Birmingham under IRB-approved protocols.Each core was analyzed individually using the TMA block software associated with Spectrum, then loaded into Tissue Studio v4.0 . Each core was segmented into tumor and non-tumor components using the Composer functionality for computationally supported histology pattern recognition. This process was manually trained, and quality controlled for accuracy on each core by a pathologist at Moffitt Cancer Center. Within each region (tumor and non-tumor) individual cells were identified using hematoxylin thresholding (0.02), the typical nucleus size was set to be 20 μmhttp://cbc.mc.vanderbilt.edu/tnbc/. The results were then merged to the clinical data using TCGA IDs.Samples with values ranging between 0 and 1 were not used. All signature thresholds were set using the Cancer Browser Signatures and Statistics tool. The cutoff range was based on the same principle as the log transformed thresholds, taking the highest and lowest 25–30 percentiles as positive and negative status, respectively. TNBC type data for the TCGA file was obtained by submitting the TNBC patient RNA-seq RSEM values in the illuminahiseq_rnaseqv2-RSEM_genes (MD5) file to P values. The probabilities of overall survival were calculated using the Kaplan–Meier method and were compared using the log-rank test to calculate P values.For cumulative incidence plots, AR status was determined by its median status and noted as AR-positive or AR-negative. Cumulative incidence plots for time to progression were constructed for all tumors and for basal and non-basal subtype by race. Log-Rank test was used to calculate The distribution of each clinical variable including age, HR-status AR-status (defined by IHC scores or RNA-seq threshold), race, and stage/grade of the tumor were determined using standard t-tests, ANOVA, and odds ratios with a significance threshold alpha of 0.05. Specific comparisons between continuous variables  or categorical variables  were measured with a bivariate fit analysis that incorporated a least-squares regression analysis between the two variables.https://genome-cancer.ucsc.edu/). TCGA breast carcinoma data were stratified by AR expression levels and dichotomized using a split cut-off based on relative positive or negative (log2 transformed) expression levels.PAM50 , 14 subtAR tumor status associations with clinical, demographic variables, and gene expression were determined using pair-wise logistical regression analyses (among continuous variables) or one-way ANOVA/t-tests . Race and AR-status multiple-testing corrections were applied (Bonferroni) to association p-values with a cutoff of 0.05 to establish significant association. Chi square distributions were used for other categorical variables.http://cran.fhcrc.org and DANTe Inferno RDN interfaces [Clustering analyses were used to correlate gene expression trends and discover expression signatures related to AR tumor status. The top 1000 AR-associated genes were analyzed with hierarchical and K-means clustering using R packages obtained from terfaces .Whole-genome expression data from primary breast cancers were obtained from public databases, screened for samples annotated for race information, and analyzed for associations with AR-status among breast cancer subtypes and racial groups . The resIn the TCGA dataset, we found that AA women with either non-TNBC or TNBC tumor types had lower AR gene expression compared to their White counterparts . AdditioAR status was independent of ER-or PR expression status, and AA tumor had highly significant differences in AR status compared to White patients (p<0.001), . HoweverSimilar to TCGA data, IHC analysis of TMA showed that of TNBC patients, AA patients had lower AR protein expression compared to White patients , and thiWe observed a significant difference in the age of diagnosis between AR positive vs negative patients with the average age for AR positive patients 59 and AR negative patients had an average age of 56 (p<0.0001) . A largeCumulative incidence analysis showed that AR-negative patients within all subtypes had shorter times to progression than those for AR-positive patients . The median time of survival was 1700 days for AR positive tumors and 990 days for AR negative tumors . SimilarAge and Stage adjusted patients with AR-negative tumors (QNBC) had more basal-like tumors than those with AR-positive tumors (TNBC) (70.8% v 3.2%) and a higher odds ratio  . These pCCNB1 and BIRC5. Thus, inclusion of AR status can help classify patients that are not able to be classified by PAM50 designations.To determine if the underlying gene signatures of the PAM50 subtypes correlated with AR-status, we compared it to each gene in the PAM50 panel . Each PATo determine the specific gene expression profile for AR-negative tumors, we first correlated gene expression trends to AR-status. Significantly associated genes were further analyzed for specific expression patterns using clustering algorithms . Based oCBL, CCL2, E2F1, and NFKBIL2 genes all show a significant difference in expression between race groups . CBL and E2F1 showed the most significant expression difference in the AR-negative subtype. Certain groups in general or AR negative group had distinct functional categories. T-cell differentiation had the highest fold enrichment , followed by the B-cell receptor signaling pathway  and cytokine binding   . The can.53E-05) . This inE2F1, NFKBIL2, CCL2, TGFB3, CEBPB, PDK1, IL12RB2, IL2RA, and SOS1 (p<0.001)  . Functiop<0.001) . Since tp<0.001) , as wellp<0.001) The addition of AR to the classical triad biomarkers for breast cancers, particularly TNBCs, appears to add a prognostic benefit for clinicians to determine which tumors will be non-aggressive or aggressive , 10. FewAR tumor status is associated with younger ages and there is a clear shift in the age groups between each AR status. The shift indicates that AR-negative status is associated with younger ages. The differences in the mean age of each groups crosses the presumed menopausal status. The median age of AR positive subtypes is 62 (mean = 59), and the median age of AR negative subtypes is 56 (mean = 56). This results in a statistically distinct age range between AR positive vs. negative tumor types. African Americans have a different age distribution among AR-negative cases. Separating the AR status into race, shows a distinct distribution of age between race groups, within AR tumor status categories. There is a significant difference in the age trends for AR negative AA (p = 0.034) as compared to AR positive category but the low case numbers in the AA limit the ability of this analysis to determine if the younger-age trend in AA’s is unique to AR negative status.Although basal-like tumors account for only about 15% of breast tumors, they are considered as a more aggressive subgroup , 22. PriMost studies examining the expression of AR in breast cancer have concentrated on the TNBC subtype. TNBC, a heterogeneous subtype, has distinct molecular profiles that contribute to clinical outcome and response to therapy . Lehman CCL2 and CCL5, which are associated with macrophage recruitment to the tumor, were associated with tumors of AA women and increased in AA QNBC patients [NFKBIL2, CCL2, TGFB3, CEBPB, PDK1, IL12RB2, IL2RA, SOS1 are differentially expressed in AA QNBC tumors and could act as drivers of this immune response. Of note, for several of these , the trends are in opposite directions in relation to race, indicating that regulation of these genes, in the context of AR status, may be dependent on genetic ancestry/ethnicity. The fact that these genes are molecular drivers within the IL12, CCR5, and B-cell response pathways confirms that, in AA women, immune genes associate with the more aggressive subtypesTo determine if AR-negative tumors have a distinctive gene signature, K-means clustering was performed after sorting for PAM50 genes and for AR-positive and -negative status. AR-negative, basal-like tumors had a gene profile distinct from all other subtypes. Analyzing these with gene ontology, we found that, within the basal-like/AR-negative set of patients, AA patients had a distinctive gene signature that could be subdivided into five signatures. Down-regulated genes were enriched in the AR pathway, T cell response, and cancer B cell response. Up-regulated genes occurred in gene sets enriched for stem cells and hormone receptors. There was a difference in immune response and vitamin D signaling. Although NFKB signaling is involved in AA breast cancers , two obspatients . Furtherpatients . There wpatients . Most AAAlthough a clinical threshold that determines AR positivity and negativity for breast cancer patients has not widely established, this is the first report to evaluate the expression of AR, and link the absence of AR to a distinctive gene signature stratified by race. Our results add to the reports suggesting that IHC of AR should be added to the current set of ER, PR, and HER2 markers. More work should be accomplished to determine if the loss of AR is associated with ancestry markers. Immunotherapies to restore T-cell responses, such as PD-1, PD-L1, and CTLA-4, are emerging as anti-tumor therapies for various cancer types, including breast cancer. Although these agents are in ongoing clinical trials for breast , our finS1 FigA. Comparisons of AR expression between each pair of tumor subtypes. The distribution of AR expression, by ranked quantiles, is shown for each molecular tumor subtype category. This analysis indicates that the TNBC subtypes are composed mainly of the lower quantile cases. There is a shift for Luminal B and Unclassified  tumor subtypes to contain lower quantile AR-expression cases as well. The table inset indicates the significance (pairwise regression) of differences in AR expression between each subtype. The Student's t ordered differences report for the paired comparisons of AR distribution curves in each subtype  between Luminal A vs. unclassified; p = 0.038 between HER2+ and unclassified is shown).(TIF)Click here for additional data file.S2 FigA. 1258 patients were assessed in our test and validation sets B. AR Expression stratified by Race in TCGA database C. AR Expression stratified by Race in TCGA TNBC population. D. Overall AR Expression stratified by Race in GSE 37751 database E. AR Expression stratified by Race in TNBC population of GS.(TIF)Click here for additional data file.S3 FigAR expression was correlated with classical markers ER, PR or HER2. Due to small sample numbers, racial differences in AR expression in the HER2-positive tumor category could not be assessed–of the 46 potential cases, 38 were White women.(TIF)Click here for additional data file.S4 FigA. IHC staining were digitally scored and box plots show AR protein expression stratified by race in TMA TNBC and non-TNBC patient samples.(TIF)Click here for additional data file.S5 FigP values, and significance was determined (p<0.05).A. kmplot.com was used to generate a Kaplan Meier plot shows the overall survival probability in AR-positive and AR-negative patients in 1,764 cases of breast cancer samples across all subtypes. AR Positive vs negative was determined by mean cutoff and Log- Rank test was used to calculate (TIF)Click here for additional data file.S6 FigA. A subset of genes related to the Immunomodulatory TNBC subtype display statistically significant differences in expression between race groups when comparing expression in AR-high and AR-low categories.(TIF)Click here for additional data file.S7 FigP values, and significance was determined (p<0.05).A. Genes related to immune checkpoint inhibitors were determined in non-QNBC (nQNBC) and QNBC patients. B. Genes related to immune checkpoint inhibitors were determined in AA versus CA QNBC patients. Students Test was used to calculate (TIF)Click here for additional data file.S1 TableOut of the five GMaP/BMaP regions within the United States, Region 3 consists of Alabama, Georgia, Florida, Mississippi, Louisiana and Puerto Rico. Each institute donated to construct the Breast Cancer TMA. B. Immunohistochemical Staining of AR on TMA slides was performed on tumors from a multi-institutional cohort of 197 patients (74 AA and 123 White) and Chi-Square analysis was performed to determine correlation with clinical pathological features of breast cancer and race.(DOCX)Click here for additional data file.S2 TableAR and IM associated genes were analyzed for pathway enrichment. The table shows the enrichment of immunological categories. Upregulated functional pathways in relation to AR-negative status. Nodes were collapsed into two over-arching categories to increase statistical power to identify general trends in pathways. Downregulated functional pathways in relation to AR-negative status. Nodes were collapsed into two over-arching categories to increase statistical power to identify general trends in pathways.(DOCX)Click here for additional data file.S3 TableEach gene set from the distinct node groups was further analyzed for functional pathway and gene ontology enrichment. Selected functional annotations and Gene Ontologies from each AR status signature node. Certain groups have distinct functional categories. Node 2 includes cancer enrichment and immunological responses. Node 5 includes hormone receptor binding target genes, with the highest enrichment in Vitamin D Receptor targets.(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.


Background: Rehabilitation therapy is the only available treatment for stroke survivors presenting neurological deficits; however, the underlying molecules and mechanisms associated with functional/motor improvement during rehabilitation are poorly understood.Objective: Our aim is to study the modulation of angiogenin and endothelial progenitor cells (EPCs) as repair-associated factors in a cohort of stroke patients and mouse models of rehabilitation after cerebral ischemia.Methods: The clinical study included 18 ischemic strokes admitted to an intensive rehabilitation therapy (IRT) unit, 18 non-ischemic controls and brain samples from three deceased patients. Angiogenin and EPCs were measured in blood obtained before and up to 6 months after IRT together with an extensive evaluation of the motor/functional status. In parallel, C57BL/6 mice underwent middle cerebral artery occlusion, and the pasta matrix reaching-task or treadmill exercises were used as rehabilitation models. Angiogenin RNA expression was measured after 2 or 12 days of treatment together with cell counts from EPCs cultures.Results: Brain angiogenin was identified in both human and mouse tissue, whereas serum levels increased after 1 month of IRT in association with motor/functional improvement. EPC populations were increased after stroke and remained elevated during follow-up after IRT. The mouse model of rehabilitation by the task-specific pasta matrix exercise increased the number of EPCs at 2 days and increased angiogenin expression after 12 days of rehabilitation.Conclusions: Angiogenin and EPCs are modulated by rehabilitation after cerebral ischemia, suggesting that both angiogenin and EPCs could serve as biomarkers of improvement during rehabilitation or future therapeutic targets. Stroke is one of the leading causes of death and long-term disability worldwide and leads to 5 million people becoming permanently disabled annually –3. Even Rehabilitation after stroke needs an inter-disciplinary care-team including physiotherapists, occupational therapists, language, and speech therapists, working under the direct supervision of a physiatrist, who might be assisted in medical decisions by the use of biomarkers monitoring the neurorepair process . The useAngiogenesis and vascular remodeling are mechanisms activated early after stroke which remain elevated from days to several weeks as a response to increased collateral blood supply and tightly coupled to neurogenesis and oligodendrogenesis as part of the endogenous neurorepair response –16. MoreOur hypothesis is that angiogenin and EPCs are modulated during rehabilitation after cerebral ischemia serving as biomarkers of functional/motor outcome related to their participation in plasticity mechanisms during neurorepair. To test this hypothesis, our study combines a cohort of stroke subjects under intensive rehabilitation therapy (IRT) in which angiogenin and circulating EPCs levels are analyzed. Additionally, the neurological status is monitored in patients using a battery of tests during a 6-month period. Further, two rehabilitation models in mice after cerebral ischemia  are used, where brain and circulating angiogenin determinations together with EPCs cultures are analyzed.n = 24), malignant infarction (n = 13), global aphasia (n = 10), human immunodeficiency virus infection (n = 1), or carotid tumor (n = 1), time to IRT > 3 weeks (n = 1), or denied the informed consent (n = 3). The included patients followed a comprehensive intensive rehabilitation program, including physiotherapy, occupational therapy, speech therapy, and/or neuropsychology, if required, for a minimum of 3 h/day and 5 days/week as recommended by the clinical practice guidelines for the management of stroke in our health care system (Stroke and control cohorts are part of the Studying Markers of Angiogenesis during Rehabilitation Therapy after Stroke (SMARTS) study . In the e system .The protocol started with a physiatrist assessing patient's deficits within the first 48 h after stroke and designing an initial rehabilitation program. Passive mobilizations performed in bed started within the first 24 h after stroke if there were no medical conditions that contraindicate it, and at 48 h patients started a moderate-intensity rehabilitation program. Those patients who presented severe or moderate deficits in ≥2 functional areas and who met the inclusion criteria for an intensive rehabilitation program were transferred to the neurorehabilitation unit for inpatient IRT, whereas those patients who were able to walk with some support/assistance were released to their household and started the daily IRT at the day hospital of the neurorehabilitation unit. IRT continued until completion of a minimum of 75% of the proposed objectives or when functional stability was achieved. If there were further objectives, the patient continued a high- to moderate-intensity outpatient rehabilitation program.In parallel, 18 non-ischemic healthy individuals without any known neurological, malignant, infectious, or inflammatory diseases volunteered to participate as the non-stroke cohort; a portion of the individuals were subjects with hypertension studied in the Investigating Silent Strokes in Hypertensives Study  or patieThe study protocol was approved by the local clinical research ethics committee (Num. 317/2013), and all patients/healthy volunteers signed the corresponding informed consent in accordance with the Declaration of Helsinki.Of the 18 included stroke patients, 1 patient was excluded during the follow-up after having a recurrent stroke, whereas 2 other patients chose to withdraw from the study during the follow-up visits  scans performed 24–48 h after stroke by an experienced neurologist, blinded to clinical information, angiogenin levels, and cell populations of interest. Infarct volume was measured according to the formula AxBxC/2, where A and B represent the largest perpendicular diameters through the hypodense area on CT scan, and C represents the thickness of the infarct .Baseline and follow-up visits included different functional/motor tests: the modified Rankin scale (scores 0–6), the Granger modified Barthel Index (BI) (scores 0–100)  and depeImprovement classifications were obtained after comparing the scores during follow-up visits vs. baseline scores: Rankin improvement was defined as a decrease of ≥1 points. For the FMA, improvement was defined as an increase ≥10 points, described previously as the minimal clinical important difference . For thead libitum, but 7 days before habituation and throughout the entire experimental procedure, food was restricted to 2–2.5 g/animal/day of chow pellets in order to increase the motivation for the specific task, while weight was controlled during the entire procedure. Experimental procedures were approved by the Ethics Committee of Animal Experimentation of the Vall d'Hebron Research Institute (protocol number 21.16) and were conducted in accordance with Spanish legislation and the Directives of the European Union.A total of 88 C57BL/6 mice  purchased from Janvier laboratories  were used in this study. The mice were housed in groups of 3–5 animals in a temperature/humidity-controlled room and maintained on a 12-h light-dark cycle. All animals were given water and food All animals were habituated and trained on the pasta matrix reaching task with a protocol adapted from Kerr et al.  or habitThe habituation protocol for the treadmill was conducted after the pasta matrix training described below. Briefly, from 3:00 to 6:00 p.m., all mice were placed in a treadmill apparatus 10 min/day for 3 consecutive days, to avoid posterior stress responses from a new environment during rehabilitation.After the pasta matrix habituation, limb preference was established by testing the mice for a minimum of 3 days between 9:00 a.m. to 1:00 p.m. Mice were placed in the testing chamber with a matrix full of pasta in the front, and they were encouraged to reach pasta pieces from the aperture for 10 min or a maximum 10 attempts. The number of attempts with the right or the left forelimb was recorded and the limb preference was determined by the 70% of limb dominance. After individual laterality preference was established, mice were trained for their preferred forelimb by filling only half of the matrix with pasta , death during surgery (n = 3), and infarct volume < 5 mm3 .Permanent cerebral ischemia was performed on 84 mice as previously described  by the p2/21%O2) and body temperature (36.5–37°C) was controlled by a probe thermometer with mice laying on a heating pad. Mice eyes were protected from corneal damages during surgery using an ophthalmic lubricating ointment . An incision was made between the left eye and ear under an operating microscope  and the temporal muscle was cut and divided exposing the left lateral part of the skull. The MCA was identified through the semi-translucent skull, and a small burr hole (2–3 mm diameter) was made using a high-speed microdrill at the level of the inferior cerebral vein to expose the M1 portion as described  for a maximum period of 30 min via face-mask ; Pasta Matrix (PM), where the reaching-task consisted of performing 100 attempts with the affected limb inside the chamber; and Treadmill, where mice received 30 min of exercise by increasing the speed every 10 min  without any aversive stimulus (such as the electric shock). For the running procedure, a plastic barrier was placed between the shock grid and the treadmill line to prevent animals from resting on the top of the grid during the rehabilitation protocol. All mice were weighed every session, which consisted of 2 (short-term) or 12 (long-term) days of rehabilitation Figure . FinallyThe maximum forelimb force was assessed with the grip test as previously described . For the3).Animals were euthanized after 4 days of pMCAo (2 days after RHB) by transcardial perfusion of cold saline with deep anesthesia as described. Brains were removed and cut into 1 mm-thick coronal sections and stained with 2,5% of 2,3,4-triphenyl-2H-tetrazolium chloride  for 10 min at room temperature (RT) when TTC solution was replaced by cold saline and images acquired for infarct quantification. Afterwards, ipsilateral and contralateral cortex were dissected for further molecular analyses, snap frozen in dry ice and stored at − 80°C until use. A treatment-blinded researcher measured the infarct volume by the ImageJ free software as described previously . FinallyTM G+).Glucose levels were monitored in a sub-group of animals before and after food restriction together with pMCAo (24 h and 4 days). Blood was obtained by making a small incision on the tail vein of mice, placing one droplet of blood on a glucose test strip and using a glucometer (GLUCOCARDn = 18), after 1 month (n = 15), 3 months (n = 15), and 6 months (n = 15) of rehabilitation intervention, while 13 samples were tested for the non-ischemic control cohort . Samples from strokes were obtained before IRT n = 8, after For mouse samples, venous blood was obtained from cardiac puncture under deep anesthesia and collected in EDTA tubes at day 2 or 12 post-rehabilitation and after sham surgery Figure . After cSD) of each plate and adding three units to avoid results below zero in any sample.All samples were tested by duplicate and only values with a coefficient of variation < 20% were accepted for the statistical analysis. For those plates in which the inter-assay CV was higher than 20%, values were standardized prior to statistical analysis by calculating the Z-score value by substracting the mean and dividing by the standard deviation . Cells were centrifuged for 30 min (400 g) at RT. Mononuclear cell (MNC) layer was isolated and centrifuged for 5 min at RT (400 g) to discard the supernatant. Then, cell pellets were resuspended in 3 ml of PBA buffer  and 1 ml of blocking reagent was added  and incubated for 10 min. Afterwards, 3 ml of the total mixture were used to incubate with primary antibodies and 1 ml was also incubated with corresponding fluorescent isotype control antibodies in order to control the non-specific antibody binding. Primary antibodies and isotypes were incubated for 45 min at RT . Tubes were centrifuged for 5 min at RT (350 g), discarding the supernatant, the cell pellet was resuspended in PBA buffer (0.8 ml for the sample and 0.5 ml for isotype) and transferred into 5 ml poliestirene plastic tubes. Before being analyzed, the samples were filtered through 30 μm Cell Tricks filters . Finally, 106 events per sample and 1 to 2 × 104 events for isotypes were analyzed using the BD LSRFortessa™ cell cytometer . CD34+ and CD34+KDR+CD45− populations were analyzed using FCS Express™ version 3, Research Edition . Extreme values represented in box-plots were excluded from the analyses.Blood (4 ml) was diluted with 8 ml of PBS containing 2% of fetal bovine serum  and the diluted blood was carefully placed over 5 ml of Ficoll-Paque Plus4Cl, 10 mmol/L NaHCO3 and 0.1 mmol/L EDTA in distilled water) and gently washed with complete endothelial growth medium-2 , which is composed of endothelial basal medium (EBM) containing 20% fetal bovine serum (FBS), human epidermal growth factor (hEGF), vascular endothelial growth factor (VEGF), human basic fibroblast growth factor (hFGF-B), insulin like growth factor 1 (R3-IGF-1), GA-1000 (gentamicin and amphoterecin-B), heparin, hydrocortisone, and ascorbic acid. Isolated MNCs were finally resuspended in EGM-2 and 107 MNCs were seeded on fibronectin-coated 12-well cell culture plates and incubated in 5% CO2 at 37°C. Under daily observation, first media change was performed 3 days after plating and, thereafter, media was changed every 2 days. At day 5, images from four representatives fields/well were taken at 100X magnification . Before data analysis, extreme values were excluded by mean ± 2 SD criteria.Mouse spleens were used to obtain early EPCs as previously described . SpleensTM with DAPI  to stain the cell nuclei and analyzed with Olympus BX61 microscope . Finally, two slices of infarct and healthy contralateral areas from three stroke patients were double-stained for NeuN/angiogenin and lectin/angiogenin and the total angiogenin positive area was calculated using ImageJ free software.IHC was performed in human and mouse brain slices for angiogenin, NeuN antibodies, and lectin blood-vessel marker. For human tissue, post-mortem brain samples from stroke patients , and 0.5% aprotinin . Lysates were collected from the supernatant after centrifugation at 15,300 g for 12 min at 4°C and PierceTM Comassie (Bradford) assay was used to determine the total protein content . A total amount of 40 μg for human samples and 10 μg for mouse samples was diluted in Laemmli Buffer , incubated 5 min at 95°C and run into 12% polyacrylamide gel electrophoresis, transferred into PVDF membranes , blocked for 1 h with 10% non-fat milk  and incubated overnight at 4°C on a shaker with anti-angiogenin  or β-actin . The membrane was then washed three times (PBS-0.1% Tween) and incubated with secondary antibodies  anti-rabbit-horseradish peroxidase from donkey or anti-mouse horseradish peroxidase from sheep  for 1 h at RT with gentle agitation. Finally, membranes were washed three times (PBS-0.1%Tween) and incubated with Pierce® ECL Western Blotting Substrate  and signal visualized with Fujifilm FPM-100A films. Scanned western blots were quantified using the ImageJ free software. Results are expressed in arbitrary units and angiogenin band-intensities were corrected by actin band-intensities. Molecular weight markers were also run for reference values.Western blot analysis for angiogenin was performed in human and mouse ischemic and non-ischemic brain cortex homogenates. Human stroke brain homogenates , following the manufacturer's procedure. The quality and quantity of RNA was measured using Nanodrop Spectrophotometer and cDNA was synthesized using a High-Capacity cDNA Reverse Transcription Kit . RT-PCR reaction was performed using a mixture of 5 μL of TaqMan® Universal PCR Master Mix , 0.5 μL of TaqMan® Gene Expression Assay : Mm01316661_m1; Applied Biosystems, Foster City, CA, USA), 3.5 μL of RNase-free water and 1 μL of cDNA sample. A sample calibrator was used to compare samples between different assay plates. Samples were run in triplicate using 384-well plates on 7900HT Fast Real-Time PCR System . Gene expression results were expressed in RQ (relative quantification).Mice tissues from 2 and 12 days of rehabilitation were used for angiogenin RNA isolation with the PARIS N < 30) and Kolmogorov-Smirnov (N ≥ 30). Normally distributed variables were analyzed by the ANOVA and LSD post-hoc or t-test, while Mann-Whitney U-test or Kruskal Wallis test were used for non-normally distributed variables. For the analysis of repeated measures, paired t-tests or repeated measures ANOVA followed by the Bonferroni post hoc test were performed for normally distributed variables, while the Friedman followed by Wilcoxon tests were used for non-normal distributions. Bar graphs represent mean ± SEM or IQR according to normal or non-normal distribution. For correlation analysis, Pearson  or Spearman  tests were used. Results with a p < 0.05 were considered statistically significant. Statistical trends (p < 0.1) are also reported in the results section.The SPSS 20.0 package was used for statistical analyses. Descriptive statistics were used to define demographic data and risk factors, stroke characteristics, functional scores, angiogenin, and cell analysis results. Chi-square tests were conducted for categorical variables. The normality of continuous variables was assessed by the Shapiro-Wilk test (p = 0.002), had higher alcohol intake (p = 0.034), had a higher body mass index (p = 0.019) and were more often on antihypertensive drugs (p = 0.04) than stroke patients.The baseline characteristics of the stroke rehabilitation cohort and control subjects are described in Table Table +, Figure +, Figure More brain angiogenin content was found during the acute phase of stroke in infarct tissue compared to the contralateral hemisphere  and compared to pre-rehabilitation values (p = 0.036), decreasing after 3 months (p = 0.001) and 6 months (p = 0.002) of IRT as shown in Figure + and CD34+/KDR+/CD45− cells increased after stroke compared to controls  and were elevated during the follow-up (3–6 months) compared to controls  despite a decrease in CD34+/KDR+/CD45− cells compared to pre-IRT levels .In the context of post-stroke rehabilitation, circulating angiogenin levels were significantly increased after 1 month of IRT compared to controls . Additionally, the increased angiogenin levels observed at 1 month were not associated with baseline infarct volume , and patients with higher Barthel Index scores (mild and complete independence) presented the highest angiogenin levels ; see Figures p = 0.043; Figure p = 0.07; Figure Neither baseline angiogenin nor EPC populations were associated with the baseline NIHSS score or infarct volume , whereas the highest baseline levels of CD34+/KDR+/CD45− cells were observed in those patients presenting a Rankin improvement at 1 month , infarct volumes were similar among groups , but angiogenin did not correlate with the infarct volume (data not shown). Importantly, angiogenin remained elevated in the ipsilateral hemisphere only in mice performing the pasta-matrix-reaching task for 12 days compared to the contralateral hemisphere (p = 0.043) and compared to the ipsilateral of non-RHB mice (p = 0.016). The contralateral hemispheres from the pasta matrix and treadmill groups also showed higher levels of angiogenin than the contralateral of non-RHB mice ; see Figure p = 0.045), whereas ipsilateral angiogenin from the pasta matrix and treadmill groups remained elevated over time, and contralateral angiogenin increased in both rehabilitation groups .RNA expression of angiogenin increased early after rehabilitation in the ipsilateral hemisphere in all groups (p = 0.003), with a mean fold increase of 4.6, as shown in Figure We validated the RNA findings in the pasta matrix reaching-task model at the protein level by IHC, confirming that angiogenin was increased in the ipsilateral vs. the contralateral hemisphere after 12 days of rehabilitation (p = 0.029 vs. short-term rehabilitation), while the pasta matrix and treadmill presented an increase at the beginning of rehabilitation that remained elevated at the end of the treatment; however, these differences were not significant ; however, there were no differences between groups after rehabilitation.Forelimb force was decreased 24 h after ischemia (p = 0.025). In the long-term, the number of cells decreased compared to that in the non-rehabilitation group (p = 0.025); see Figure Finally, spleen-derived EPCs from the pasta matrix reaching-task rehabilitation group showed an increase in the number of spindle-shaped cells compared to the non-rehabilitation in the short-term  enhanced more axonal plasticity and motor recovery than forced exercise via running wheels , suggestUnfortunately, we could not demonstrate a functional improvement on the grip strength meter test in the mice with overexpressed brain angiogenin that received rehabilitation. We attribute this result to the spontaneous recovery observed in mice  and the Finally, EPCs have been investigated as key elements of neovascularization and for their use as biomarkers after stroke during rehabilitation. These cells have the capability to form new vessels in the adult, can mobilize to specific areas in response to ischemia and differentiate to endothelial cells , 26, 41.In conclusion, we have described for the first time the modulation of angiogenin and EPCs in stroke patients under IRT and in a mouse model of post-stroke rehabilitation task-oriented exercise. Our findings suggest that these molecules may be novel biomarkers to monitor and predict stroke recovery.It is important to remark that the main limitation of our study is that we have not included a control cohort of stroke patients of similar characteristics who did not receive IRT to truly elucidate the role of rehabilitation in the modulation of angiogenin and EPCs. Ethical principles demand that all patients admitted to our hospital who are candidates for receiving IRT must be enrolled in the program. Future multicentric studies including other rehabilitation programs, and enlarging the number of studied patients should be designed in the future. As an approach to this non-rehabilitation condition after stroke, we have presented a pre-clinical model of stroke with or without rehabilitation intervention. The multicentric approach should be also considered for future pre-clinical studies including different occlusion models and other rehabilitation models.MG-S and AR conceived and designed the experiments; MG-S, AR, XB, NG, and SR organized the database and contributed to data collection; MG-S and DG performed the statistical analysis; MG-S, AM, GC, AF, and AB participated in data acquisition. MG-S and AR wrote the first draft of the manuscript. JM contributed to review the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Neurological impairments such as stroke cause damage to the functional mobility of survivors and affect their ability to perform activities of daily living. Recently, robotic treatment for upper limb stroke rehabilitation has received significant attention because it can provide high-intensity and repetitive movement therapy. In this review, the current status of upper limb rehabilitation robots is explored. Firstly, an overview of mechanical design of robotics for upper-limb rehabilitation and clinical effects of part robots are provided. Then, the comparisons of human-machine interactions, control strategies, driving modes, and training modes are described. Finally, the development and the possible future directions of the upper limb rehabilitation robot are discussed. Stroke is one of the leading causes for disability. In China, there are more than 2 million new cases every year. More than 1.5 million people die from stroke each year, and three quarters of the survivors have varying degrees of sequelae [With the development of robot technology, the application of robot in rehabilitation has aroused wide concern in the international community. A series of intelligent rehabilitation robots including artificial prosthesis and external mechanical auxiliary system have successfully developed to help patients to achieve functional recovery or compensation for the loss of motor function –5.There are two types of rehabilitation robot for upper extremity: one is end-effector upper limb rehabilitation robots, another is exoskeleton rehabilitation robot . These rThis paper gives a systematic review of research status in an upper limb rehabilitation robot. In order to review the development of the robot in more detail, we divide following chapters to present. Firstly, we provide a classification of typical mechanisms and clinical effects of part robots. The next section introduces the comparisons of human-machine interactions, control strategies, driving modes, and training modes. Then, the third section gives an overview of development and the possible future directions of the upper limb rehabilitation robot.A wide literature search from 1985 until December 2017 has been conducted resorting to the main databases, such as Web of Science, Google Scholar, and IEEE Xplore databases. The keywords used for the electronic search were upper limb, exoskeleton, end-effector type, and rehabilitation robotics. The studies that satisfied these criteria were (1) technology of part of the rehabilitation robot system, (2) robot that is able to assist the stroke patients to exercise upper limb movement, (3) focus on upper-limb functional abilities, and (4) control strategy and man-machine interaction. A total of 230 papers have been gathered by using the aforementioned search method; 117 papers have been excluded since they did not meet the inclusion criteria.The rehabilitation training robot was used to assist patients to complete the rehabilitation training. It has different design requirements of general industrial robots because of special working objects and environment. Usually, rehabilitation robots can be divided into end-effector type and exoskeleton according to the robot's different ways of supporting and pulling the limb. Specifically, the end-effector rehabilitation robot can be divided into rigid rod traction type and rope traction type , 12. ComThe end-effector rehabilitation robot system consists of ordinary connecting rod and series robot mechanism. In the working state, the robot drives the movement of the upper limbs by connecting with the patient's arm to achieve the rehabilitation training. The robot system is relatively independent of the patient, which only connects to the end of the robot.The upper limb rehabilitation robot firstly appeared in 1993. Lum et al. developed a “hand-object-hand” system used in the upper limbs of hemiplegic stroke patients after a period of time of rehabilitation . The patIn 1995, Lum et al. developed a hand-lifting recovery machine  to train patients with both hands [P ≤ 0.20) and motor power scores (P ≤ 0.10), motor status score (P ≤ 0.05)) [Since 1995, Krebs et al. of the United States have developed MIT rehabilitation robots and expanded their function. So far, the mechanical parts of the robot have three modules: graphic module, wrist module, and hand module. The robot assists patients to complete the drawing of the elbow, forearm, and wrist joint movement and hand grasping training. Twenty hemiparetic stroke patients were divided into a control group and an experimental group in the clinical trial. The latter were required to execute traction movement of the shoulder and elbow with a machine. Results indicated that patients in the experimental group improved further and faster  technology with electrical stimulation technology to complete the training on the shoulder, elbow, and wrist, achieving good healing properties. Eleven healthy subjects and five stroke patients participated in the experiment. The results confirmed that striking improvement has been seen for the anterior deltoid .The Arizona University at United States developed 5-DOF upper limb rehabilitation robot RUPERT and artificial 4-DOF robot driven by pneumatic muscle (PM). Movement driven by the pneumatic muscle is more flexible, because of similar muscle function and movement characteristics. The modified Wolf Motor Test and the Fugl-Meyer upper motor assessment test were utilized. Eight healthy subjects and two stroke patients participated in this experiment. Four healthy subjects improved in both the simple and complex tasks, and two patients improved the limb function –30.Perry from the University of Washington developed a 7-DOF arm rehabilitation robot named CADEN-77 driven by rope besides forearm rotation , 32. It The University of California and the University of Irvine developed 5-DOF T-WREX (training Wilmington robotic exoskeleton) , 35 and Rice University developed a composite group organization 5-DOF forearm rehabilitation robot named MAHI Exo II . The firNorthwestern University in collaboration with the Rehabilitation Institute of Chicago studied a 10-DOF (8 + 2) of the upper limb rehabilitation robot named IntelliArm . It can Queen's University designed the 6-DOF upper limb rehabilitation robot MEDARM driven by a rope . SternocCanada's ETS cooperation with McGill University has developed a 7-DOF arm rehabilitation robot system named MARSE ETS –42. It cThe Swiss Royal Institute of Technology cooperation with the affiliated hospital of Balgrist University developed the famous 6-DOF arm rehabilitation robot ARMin . It can In summary, the exoskeleton robot can realize more accurately the assist motion, and the end-effector rehabilitation robot has better performance on feedback and evaluation. The exoskeleton has parallel motion range and space with human joints, so it can reduce inertia more effectively and have a more compact structure. However, the end-effector is a series mechanism, which has larger movement space and more freedom. The end-effector is more suitable for multifreedom training tasks. Besides, the end-effector can effectively solve the joint coincidence problem, but underactuated exoskeleton can also realize it. Exoskeletons are increasingly becoming a major option in clinical treatment compared to the end-effector.The overview of end-effector upper limb rehabilitation robots and exoskeleton upper limb rehabilitation robots is shown in Tables Human-machine interaction is an important part of the robot system, which can influence the recovery effect and treatment process largely. This paper argues that human-machine interaction refers to communication methods, which are distinguished by the type of control signal. From this point of view, human-machine interaction can divide into bioelectric signal interaction method and physical signal interaction method.BCI technology is one of research hotspots in recent years that formed in the 1970s . The priWhen the brain is doing conceptual work, creating motion mind, or receiving outside stimulation, the nerve cells will produce dozens of millivolts of microelectrical activity. The electrical activity of a large number of nerve cells transmitted to the surface of the scalp to form brainwaves. This EEG  will reflect some characteristics of rhythm and spatial distribution and can be detected by a certain method. By signal processing, the intention signal of humans is discriminated and converted into a control command to realize controlling of external equipment and communication with the outside .  FigureThe two kinds of signal acquisition methods commonly used in the BCI system are intrusive and noninvasive. The signal collected by the equipment is amplified by amplifiers and pretreated by the processor, which is converted into digital signals and is stored in the computer. In BCI, the following signals are often collected: visual evoked potential (VEP), event-related potential (ERP) P300, slow cortical potential (SCP), spontaneous EEG Alpha wave, and Mu and beta rhythm signal.With the development of neuroscience, scientists found that in the whole process of life, the function of the damaged central nervous system can restore through the action of reasonable physiological potential –50. We cThe surface electromyogram signal produced by the contraction of the muscle is obtained by the surface electrode from the muscle surface of the human body. The electrical control system obtains multichannel sEMG from the human skin surface by the electrode and then performs eigenvalue extraction and action discrimination. The processor determines the motion state of the corresponding joints and muscles according to the identification results. And then it can control peripheral devices.Researches show that in the process of joint movement, sEMG can not only reflect the muscle information such as fatigue state and contraction intensity but also reflect movement intentions and other information in the process of different body joints movement .The identification of motor intention relies heavily on the selection of the signal acquisition site. After extracting and processing the EMG signal, the upper limb rehabilitation robot estimates joint torque and designs moving targets, then the processor controls the robot to complete the corresponding movement according to the instruction. Niigata University developed the upper limb rehabilitation robot based on the electromyogram signal control. The robot consists of seven DC motors, encoder, point meter, and the force and torque sensors, which can assist patients to complete seven degrees of freedom movement and training .Compared with bioelectric signals, the motion parameters' interactive signals have advantages of accuracy and reliability. The ways of motion parameters are force control, position control, and force/position hybrid control. Force sensors in real time, which are processed, judged, and translated into instructions to control the machine, often collect signals. Similarly, the variation of the position signal is used as the control signal. These different kinds of way of interaction often use the impedance control algorithm, PID control algorithm, and trajectory tracking control algorithm.In recent years, the interactive mode of motion parameters are often combined with virtual reality technology and applied in the field of motion rehabilitation. It shows that using virtual reality (VR) and computer game techniques in post-stroke upper limb rehabilitation may enhance neuronal plasticity –57. ReceIn summary, the interaction mode based on bioelectric signal has better effects on nerve rehabilitation treatment and has greater clinical application potential. The physical signal interaction method is more suitable for patients with some motion capability and has more potential in the application of family rehabilitation. Bioelectric signal interaction can express the patient's needs and physical condition at the neural level, especially brain signal interaction which has crucial significance in clinical neurological rehabilitation. Though physical signals are more stable and accurate, they cannot better represent people's intentions. In the future, the rehabilitation robot will be controlled based on the brain signals combined with physical feedback and virtual reality environment so that the user's neural activity can be better activated.In recent reviews, many researchers summarized human-machine interaction, training modes, and control strategies into one type to categorize and compare . This paDifferent control strategies of robot can be realized by the processing of human-machine interaction signals in different methods and algorithms. The control strategy can be divided into following parts.The position control is also known as trajectory tracking control. The angular displacement of each joint is determined by the kinematic inversion of the planned trajectory that controls the torque output of the motor in the process of computer operation to drive the motion of each joint and realize the movement along the planned trajectory .Each joint moment sensor captures the motion of the upper limbs of hemiplegic stroke patients in real time. The control system can convert joint torque to the equivalent force of the end effector according to the characteristics of institutions. Then, the controller can drive the motor to achieve the multijoint motion of the upper limb according to this equivalent force. Some researchers have also validated the clinical efficacy of force feedback. Johnson et al. designed the experiment to research the effect of using force-feedback control in robot-assisted stroke therapy .Researchers put forward that independently the control force and position at the same time are the optimal schemes of the robot control method. In theory, the free force space and position free space of the robot is two complementary orthogonal subspaces; the parameters are independently controlled in each space. The constraint environment is considered as a geometric problem with no deformation at this time –74.Impedance control is proposed by Hogan, who points out that the relationship between the position and the force can be described by a generalized nonlinear impedance model with a property of inertia, damping, or stiffness , 76..The relationship between speed and force is called mechanical impedance. The objective of impedance control is to mediate the mechanical impedance of the robot to maintain the ideal dynamic relationship of the contact force and position between the end-effector and the environment . TherefoIn a word, position control can effectively control joint angles and provide real-time feedback. For different patients, position control can make the training more personalized. Force control requires accurate acquisition of muscle and machine interactions so it relies more on the layout of the sensor. Impedance focuses on realizing the flexibility of the rehabilitation robot which avoids excess between mechanical structure and limbs. This method could provide a natural, comfortable, and safe touch interface and avoid secondary damage effectively. In practical applications, force/position hybrid control is a better control method in passive training mode and impedance is more suitable in active training processes.There are three common driving modes for upper limb rehabilitation robots: motor drive, hydraulic drive, and pneumatic muscle drive. The advantages and disadvantages of the three driving modes are shown in Robotic intervention therapy for stroke patients shows clear improvement of scores and strength, but these progresses are not reflected daily. It is necessary to focus on the targeted stage of recovery . TherefoPassive training is almost performed by a physical therapist or by a device. It requires the movement of joint in the regular range and prevents contractures to maintain the static length of the muscles . The pasThere is a limitation of passive training mode because patients cannot make effort to engage training . Two typIn the active rehabilitation training, the main motion form is autonomous movement of the patient, and the robot can judge the patient's motor ability according to the movement information of the patients to provide appropriate assistance. Active rehabilitation training can be divided into active power mode and active impedance. The robot can judge the sport ability and recovery degree by gathering motion information of the interaction between the robot and the patient and decide to provide assistance or resistance.In the past few decades, the upper limb robots applied to clinical rehabilitation have brought positive significance to stroke patients. In this paper, the development of upper limb rehabilitation robot, human machine interaction, training mode, driving mode, and control strategy is reviewed. The upper limb rehabilitation robots have shown encouraging clinical outcomes and rehabilitation efficiency. Previous researchers have accomplished a lot of work to promote the development of this technology. However, this study still faces many challenges.In terms of mechanical structure design, the complexity of the upper limb joints and redundancy DOFs bring many difficulties. The simplified model of arm exoskeleton movement usually may lead to several possible problems. During the training process of physical therapy, the unanticipated force generated during the man-machine collaboration may reduce the comfort level of humans and robot system. It may be better to optimize and improve institutional material and guarantee the flexible contact between patients and robots. Wearable robots often require as little weight as possible, but the simplified model may reduce the working space of the upper limb exoskeleton system thereby limiting its application scope. Most equipment is stationary; the patients cannot flexibly use rehabilitation equipment anytime and anywhere because of the style of installation of equipment. It cannot satisfy the portable, mobile, and other requirements and greatly affect patient rehabilitation experience, so it is necessary to make machine more lightweight and portable in the future study.Among the upper limb joints, the shoulder joint is a complex joint because the center of rotation is moving with nonlinear trace in the process of movement. Therefore, it is necessary to solve the problem that the rotation center of machine misalignment with the rotation center of the human body in future studies. Compared with end-effector rehabilitation robots, the exoskeleton has better bionic characteristics, because its motion is similar to human joint motion. In the future, the exoskeleton should be more anthropomorphic and the design of motion should be similar to biomechanical joint motion.From the perspective of the human biomechanics aspect, one of the important features is the physical properties of the musculotendinous and their resulting impedance. Therefore, exoskeletons should accordingly adapt to these variations of impedance to guarantee the smoothness of contacting and preventing spasm. In the process of active control, the exoskeleton mechanism singularity exists in its working space, increasing the difficulty of the control algorithm. It is helpful to reduce the complexity of the control algorithm to avoid the singularity in the actual workspace by optimizing a machine design.In the process of working conditions, it is essential for a rehabilitation robot to guarantee the patient's safety. Therefore, the robot should guarantee the safety of the subject from the following aspects: using the joint sensor to monitor the force information of the subjects during the movement, when the reaction force caused by the muscle tension is too high. When the patient appears with muscle spasm, the robot should automatically stop the current movement so as not to cause the muscle strain. The working space should be limited in the reasonable range by limiting the switch in order to avoid the repeated injury for the patient. The movement speed and displacement of the robot should also be limited by software. The operator should reasonably set the parameters of the driving device and monitor the robot motion state in real time. A press-and-stop button is extremely important to avoid accident situations. Also, self-locking of robot should be taken into account to avoid the damage by the rotation of the joints caused by gravity.It has been shown that using virtual reality (VR) and computer game techniques in stroke rehabilitation may enhance the function of neuronal plasticity. Further, enhancing patient sensorial state can be accomplished by merging together with VR, haptic and vibrotactile feedback. However, real-time synchronization of signals that is dedicated to reconstruct VR may be delayed due to the large number of required devices. This may lead to a bad real-time environmental reconstruction, thus increasing the task difficulty. It is also necessary to improve the response speed of the signal to ensure the timeliness of the interaction between the virtual environment and humans.BCI technology provides a new way of communication and control without language or body movement. It can directly express ideas or manipulate machine by the brain that has profound research significance in neurological rehabilitation. However, there is a difference in physiological characteristics of the brain between patients and normal individuals. Heterogeneity in post-damage expression inevitably complicates the decoding of brain signals responsible for neuronal plasticity recovery; this may lead to complicate extraction of suitable control inputs. The best way is integrating BCIs with actual rehabilitation methods to establish a powerful and accurate rehabilitative scenario. So far, there are BCI systems that hardly exist that can provide a high-accuracy control .It is often thought that the rehabilitation of the proximal arm may benefit the distal arm. As revealed by many studies, the proximal improvements in the arm do not necessarily transfer to the distal arm or vice versa and that arm improvements do not manifest as improved ADL performance. Therefore, how to design a more reasonable device to ensure the best recovery of the proximal and distal end is also a problem that needs to study.