Ma et al. uncovers an essential role of AR signaling in melanoma cell expansion and tumorigenesis, with loss of AR activity inducing cellular senescence, genomic DNA breakage, a STING-dependent inflammatory cascade, and immune cell recruitment, providing an attractive venue for new combination approaches to disease management. AR down-modulation elicits a shared gene expression signature associated with better patient survival, related to interferon and cytokine signaling and DNA damage/repair. AR loss leads to dsDNA breakage, cytoplasmic leakage, and STING activation, with AR anchoring the DNA repair proteins Ku70/Ku80 to RNA Pol II and preventing RNA Pol II–associated DNA damage. AR down-modulation or pharmacological inhibition suppresses melanomagenesis, with increased intratumoral infiltration of macrophages and, in an immune-competent mouse model, cytotoxic T cells. AR provides an attractive target for improved management of melanoma independent of patient sex.Melanoma susceptibility differs significantly in male versus female populations. Low levels of androgen receptor (AR) in melanocytes of the two sexes are accompanied by heterogeneous expression at various stages of the disease. Irrespective of expression levels, genetic and pharmacological suppression of AR activity in melanoma cells blunts proliferation and induces senescence, while increased AR expression or activation exert opposite effects.   Malignant melanoma is the fifth most common cancer in the world, and its incidence is rising. Among the many prognostic risk factors that have been proposed for the disease, one of the most intriguing and least understood is sex . In factAs for sexual dimorphism in other cancer types , even foIn experimental settings, estrogen signaling was found to restrict melanocyte proliferation, enhance differentiation, and suppress melanoma development . In spitThe androgen receptor (AR) is expressed in many cell types and, while most studies have focused on prostate cancer, AR signaling has been implicated in tumorigenesis in other organs, specifically breast, bladder, kidney, lung, and liver . SurprisIn this study, based on analysis of a large panel of clinical samples and melanoma cells from both male and female patients, we show that, irrespective of expression levels, genetic and pharmacological suppression of AR activity triggers melanoma cell senescence and limits tumorigenesis, eliciting a gene expression signature related to IFN and inflammatory cytokines and associated with better patients’ survival. Loss of AR activity in both melanoma cells and tumors is sufficient to cause massive chromosomal DNA breakage and leakage into the cytoplasm, with a stimulator of IFN genes (STING)–dependent inflammatory signaling cascade. Underlying these events, we find that AR is essential in melanoma cells for anchoring the DNA repair proteins Ku70/Ku80 to RNA polymerase II (Pol II) and preventing RNA Pol II–associated DNA damage. Although at different levels, androgens are produced in both male and female individuals, and AR targeting provides an attractive therapy approach for improved management of melanoma irrespective of patient sex.Melanoma tumors are characterized by distinct phenotypic states and display significant intra- and intertumor heterogeneity . Double Immunostaining of cultured cells also showed a variation in AR protein expression among various melanoma cell lines and primary melanoma cells derived from male or female patients, with AR levels being uniformly low in primary melanocytes . As obseVariations in AR expression were further confirmed by immunoblotting with two different antibodies, with a similar pattern of bands, and by quantitative RT-PCR (RT-qPCR) analysis of melanoma cell lines, early passage primary melanoma cells, and primary melanocytes, which were again found to express lower AR levels .AR expression in a panel of melanoma cells harboring either BRAF or NRAS mutations individually and in combination with TP53, PTEN, and/or CDK4 mutations . Mass infection of dCas9-KRAB–expressing melanoma cells with two lentiviruses with AR-targeting sgRNAs significantly reduced AR protein levels, decreased clonogenicity, and induced cellular senescence, reproducing the effects of AR gene silencing  system , wherebyilencing .AR is a fundamental target for therapy of metastatic prostate cancer, and inhibitors with multiple mechanisms of action and efficacy have been developed . TreatmeWe recently reported that suppression of AR activity in human dermal fibroblasts (HDFs) by a ligand-competitive inhibitor induces expression of a battery of tumor-promoting cancer-associated fibroblast effector genes, similarly to silencing of the gene . To asseConversely to the growth suppressing effects of the AR inhibitors, proliferation of primary melanocytes and melanoma cells in charcoal-stripped medium was significantly enhanced by treatment with the AR agonist dihydrotestosterone (DHT) in a dose-dependent manner . ProlifeBRAF and one with NRAS mutations, with or without AR silencing with two different lentiviruses. By gene set enrichment analysis , and IFIH1  was consistently up-regulated together with IL6, a potent proinflammatory cytokine  dataset Skin Cutaneous Melanoma (SKCM). Tumors were stratified as having positive or negative association scores with the ociation . The resociation , showing T cells .http://www.ilincs.org/ilincs/) portal allows comparative analysis of transcriptional profiles of various cell lines in response to different drugs. A significant concordance was found between the AR silencing gene signature and the iLINCS-derived transcriptional profiles of A375 melanoma cells treated with several AR inhibitors, as well as a number of DNA-damaging agents targeting the topoisomerase 2 (TOPO2) and TOPO1 enzymes  fragments into the cytoplasm, together with increased expression and aggregation of the STING protein, a cytosolic DNA sensor with an important role in innate immunity  in AR-silenced YUMM1.7 melanomas, consistent with what we observed with human cells in immune-compromised mice (+ T cells (CD45+ CD3+ CD4+) was not significantly different, that of CD4+ regulatory T cells (CD45+ CD3+ CD4+ FoxP3+) was significantly decreased in in AR-silenced YUMM1.7 melanomas (+ T cells (CD45+ CD3+ CD8+) did not vary consistently; however, the activated fraction (CD44+ population) was significantly increased, with a lesser expression of coinhibitory molecules, LAG3 and PD1, which are highly expressed by exhausted T cells  according to the manufacturer’s instructions. The details of the siRNAs used in this study are provided in For siRNA silencing experiments, melanoma cells were transfected with AR expression  or vector control. After selection, the AR-overexpressing melanoma cells were superinfected with an AR-silencing or corresponding lentivirus control and selected for puromycin resistance as described above. The cell proliferation assays were performed 5 d after the second infection.For AR overexpression and rescue experiments, melanoma cells were stably infected with a blasticidin-resistant lentiviral vector for constitutive AR expression, A375 melanoma cells were stably infected with a dCas9-KRAB–expressing lentivirus , Enzalutamide (Selleckchem), or DMSO solvent control as indicated. For DHT treatment experiments, melanoma cells were washed four times in PBS after seeding and cultured for 48 h in phenol red–free DMEM complemented with charcoal-treated FBS before treatments with DHT (MilliporeSigma) or vehicle control (EtOH) as indicated.Cell proliferation assays were performed by measuring the production of ATP using the CellTiter-Glo luminescent assay (Promega) as per the manufacturer’s instructions. The luminescence signals for each time point were normalized to the signal obtained at day 0.5-Ethynyl-2′-deoxyuridine (EdU) incorporation assays were performed using Click-iT Plus EdU Imaging Kit (Thermo Fisher Scientific) following the manufacturer’s instructions. The number of EdU-positive cells was analyzed, and the data were represented as percentage of EdU-positive cells.For clonogenicity assays, cells were plated on 60-mm dishes  and cultured for 7 d. Colonies were fixed with 4% formaldehyde and stained with 1% crystal violet. The number of clones was counted using ImageJ .For sphere formation assays, melanoma cells were plated onto 8-well chamber slides (Corning) precoated with Matrigel (Corning). In brief, chambers were coated with 100 µl Matrigel per well and incubated for 1 h at 37°C to polymerize. 1,000 melanoma cells were plated in each well. The number of spheroids was assessed 7 d after plating through an EVOS Cell Imaging System (Thermo Fisher Scientific).For IncuCyte cells proliferation assays, 1,000 melanoma cells per condition were seeded in triplicate into each well of a 96-well plate and allowed to attach for 12 h. The plates were mounted on IncuCyte Zoom System (Essen Bioscience), and cells were allowed to grow for the next 6 d. Images were captured at four different sectors of each well every 2 h for 6 d, and cell confluence was calculated by IncuCyte Zoom software.For apoptosis assays, dead and proapoptotic cells were assessed using the Annexin Kit (BD Biosciences). In brief, before fixation, cells were washed with annexin-binding buffer, followed by incubation for 15 min at room temperature (RT) with annexin-Cy5 dye for staining of proapoptotic cells. After annexin incubation, cell were fixed with 4% formaldehyde and counterstained with DAPI.Senescence-associated β-galactosidase  activity was assessed by the use of a commercially available chromogenic assay kit  as per the manufacturer’s instructions.AR silencing in individual melanoma cells was assessed using alkaline comet assay (single-cell electrophoresis) as described previously  or LDS buffer (Thermo Fisher Scientific). Equal amounts of proteins were subjected to immunoblot analysis. Membranes were sequentially probed with different antibodies as indicated in the figure legends, using an enhance chemiluminescence kit (Thermo Fisher Scientific) for detection. Details of antibodies used in this study are provided in PLAs were performed with a Duolink kit with provided reagents and buffers  using the following protocol. Melanoma cells were seeded on glass coverslips in a 24-well plate. After washing with PBS three times, cells were fixed with cold 4% paraformaldehyde for 15 min at RT. The fixed cells were washed with PBS, followed by permeabilization with 0.1% Triton X-100 in PBS for 15 min at RT, incubation in blocking buffer (provided with the kit) for 2 h at 37°C in a humidified chamber, and incubation with different primary antibodies  diluted in antibody diluents overnight at 4°C. Cells were subsequently washed in buffer A three times for 15 min and incubated with the PLA probes for 1 h at 37°C in a humidified chamber. This was followed by a 10 min wash in buffer A, a ligation reaction at 37°C for 1 h, and two more washes (10 and 5 min) in buffer A. Samples were then incubated with the amplification mix for 2 h at 37°C in a darkened humidified chamber, followed by washing with 1× buffer B (10 min) and 0.01× buffer B (1 min) and processing with mounting media. Cells were counterstained with DAPI, and images were acquired with a Zeiss LSM880 confocal microscope. The number of PLA puncta (dots) per cell/nucleus was quantified using the fluorescent particle analysis with ImageJ. Details of the antibodies used in PLA assays are provided in WM1366 melanoma cells were harvested by trypsinization. Cells were resuspended in ice-cold co-IP buffer  and lysed by mild sonication (three 5-s pulses). The cell debris were removed by centrifugation, and the supernatant was subjected to extensive DNase I digestion. Co-IP was performed by incubating 500 µg of the lysate with 4 µg of anti-AR  or anti-RNA pol II  antibodies in 500 µl co-IP buffer for 8 h at 4°C. A mock reaction was also performed by incubating rabbit IgG (as control) with the lysate. Prewashed Protein A magnetic beads were added, and the incubation was continued for another 1 h. The beads were washed three times with 1 ml of co-IP buffer, resuspended in SDS-PAGE sample loading buffer, and incubated for 20 min at 98°C. The samples were resolved on 8% SDS-PAGE, and immunoblotting was performed with anti-AR , anti-RNA pol II , and anti-Ku70  antibodies. VeriBlot IP Detection Reagent  was used as secondary antibody (1:200 dilution) to selectively detect target protein bands, without interference from the denatured IgG heavy and light chains. Details of the antibodies used are provided in AR-silencing with two different lentiviruses versus empty vector control were assessed by Clariom D GeneChip array analysis (Thermo Fisher Scientific). 5 d after infection, RNA was extracted from the melanoma cells using Direct-zol RNA MiniPrep kit (Zymo Research) coupled with DNase treatment, and RNA quality was verified by Bioanalyzer (Agilent Technologies). 50 ng of total RNA was used as input for the preparation of single-strand cDNA using the GeneChip WT PLUS Reagent Kit (Thermo Fisher Scientific). Targets were then fragmented and labeled with the GeneChip WT Terminal Labeling Kit (Thermo Fisher Scientific) and hybridized on Human Clariom D GeneChip arrays (Thermo Fisher Scientific) at the iGE3 Genomics Platform, University of Geneva . Data obtained were analyzed using TAC software (v4.0). The data generated in this study have been deposited to the public functional genomics data repository GEO, accession no. GSE138486.The transcriptional changes elicited in WM1366, SKMEL28, and WM115 melanoma cells with or without http://www.broadinstitute.org/gsea/msigdb/). A list of enriched pathway gene sets is provided in GSEA for GeneChip microarray data was conducted using GSEA software with default parameters. Curated gene sets were obtained from the Molecular Signatures Database  and shAR (n = 6) conditions was performed with Limma (default parameters), pairing together samples from each cell line. The AR silencing signature was constructed as the list of genes up- or down-regulated upon AR silencing, i.e., genes showing an adjusted P value < 0.05 and an absolute log fold-change >1 in the overall analysis as well as in each cell line separately.Raw microarray expression data were preprocessed with TAC software, obtaining gene-level expression values from signal space transformation/robust multiarray average summarization. Ensemble IDs were mapped to gene symbols with Biomart. A paired differential expression analysis between control . In case both primary and metastatic samples were present for the same patient, only the primary sample was retained. TPM (transcripts per million) values were transformed as log2 (TPM + 1). Scores for the sets of genes up- and down-regulated were computed with the R package GSVA v1.30.0 using default parameters. The difference between these scores was computed to obtain a unified score for the total AR-silencing gene signature (comprising both up- and down-regulated genes) for each patient. Each tumor was assigned a positive (+) or negative (−) score relative to the unified AR-silencing gene signature.Level 3 gene expression and clinical data for TCGA SKCM projects were downloaded from the National Institutes of Health Genomic Data Commons Data Portal .The difference between the survival of patients with a positive (+) versus negative (−) score for the AR-silencing gene signature were tested with Wilcoxon rank-sum tests.Cell type fractions for bulk RNA-sequencing melanoma samples from TCGA SKCM were computed with EPIC v1.1.5 using default parameters and CIBERSORTx using LM22 signature matrix and B-mode batch correction. Differences between melanomas enriched and not enriched for the AR silencing gene signature and iLINCS chemical perturbagen signatures was performed by interrogating the iLINCS data portal (http://www.ilincs.org/ilincs/). Briefly, the iLINCS web application computes concordance as the Pearson correlation coefficient between the fold-changes of the genes in common (n = 21) between the query signature and the precomputed iLINCS signatures. Signatures with correlation >|0.2| and P < 0.05 are extracted and sorted by concordance. A list of top iLINCS signatures with concordance score >0.65 is shown in The analysis of concordance between our in-house 6 melanoma cells  infected with AR silencing versus control lentiviruses were injected (29-gauge syringe) with Matrigel  intradermally in parallel into the left and right side of mice. Mice were sacrificed, and Matrigel nodules were retrieved for tissue analysis 16 d after injection.Intradermal back injections of indicated melanoma cells were performed in 6–8-wk-old male and female NOD SCID mice . In brief, 106) were intradermally injected with Matrigel solution in the back skin of 10 male NOD SCID mice. 3 d after injection, mice were treated with either 100 µl of AZD3514  or Captisol (Ligand Technology) as vehicle control (group of four mice) for 12 consecutive days by oral gavage. The body weight of the mice was measured regularly during the treatment. Mice were sacrificed, and Matrigel nodules were retrieved for tissue analysis at the end of the treatment.For in vivo AZD3514 treatment experiments, RFP-expressing A375 melanoma cells  or DMSO for 12 h in culture and injected intradermally in mice together with Matrigel as described above. The tumors were allowed to grow for 2 wk, and nodules were retrieved for tissue analysis at the end of the treatment.5 melanoma cells infected with AR silencing versus control lentiviruses were injected with Matrigel  intradermally in parallel into the left and right side of mice. Mice were sacrificed, and Matrigel nodules were retrieved for flow cytometry analysis 14 d after injection. All mice were housed in the animal facility of the University of Lausanne.Intradermal back injections of YUMM1.7-RFP cells were performed in 6- to 8-wk-old male and female mice . In brief, 5 × 10g, 30 min) at RT with 48% and 80% Percoll  and collected from the interphase of the gradient. FACS analysis was performed using an LSRII (BD Biosciences). Data were analyzed using FlowJo. The following antibodies were used for flow cytometry: anti-CD3 (17A2), anti-CD4 (RM4-5), anti-CD8α (53-6.7), anti-CD11b (M1/70), anti-CD45 (104), anti-Gr-1 (RB6-8C5), anti-FoxP3 (FJK-16s), anti-CD44 (IM7), anti-F4/80 (BM8), anti-LAG3 (C9B7W), anti-PD1 (RMP1-30), and anti-Arg1 (A1exF5). Cell populations were identified based on the following expression markers: CD4 T cells, CD45+ CD3+ CD4+; CD8 T cells, CD45+ CD3+ CD8+; regulatory T cells, CD45+ CD3+ CD4+ FoxP3+; and macrophages, CD45+ Gr-1− F4/80+ CD11b+. Antibody details, including commercial sources, are provided in Tumors were minced in RPMI with 2% FBS, i.v. collagenase , and DNase  and digested at 37°C for 45 min. The digested samples were then filtered through a 70-µm cell strainer and washed with FACS buffer (PBS with 2% FBS and 2 mM EDTA). The cell pellets then incubated with ACK lysis buffer (Invitrogen) to lyse red blood cells. Next, viable cells in single-cell tumor suspensions were further enriched by density gradient centrifugation . Data are presented as mean ± SEM or SD, as indicated in the legends. Statistical significance for comparing two experimental conditions was calculated by two-tailed Melanocytes were prepared from discarded human skin samples from abdominoplasty or circumcision at the Department of Plastic Reconstructive Surgery or Pediatrics, Lausanne University, with required institutional approvals (UNIL: CER-VD 222/12) and informed consent. Benign nevi, dysplastic nevi, primary and metastatic skin sections, and melanoma tissue microarray slides were obtained from the Live Cell Biobanks of the URPP “Translational Cancer Research” . All samples were obtained as surplus material from consenting patients (Ek. 647/800), and the experiments were approved by the Kantonal ethics committee of Zürich . No access to sensitive information was provided. All animal studies were performed according to Swiss guidelines for the use of laboratory animals, with protocols approved by the University of Lausanne animal care and use committee and the veterinary office of Canton Vaud .AR mRNA expression in different melanoma cell lines and primary human melanocytes. AR in different melanoma cell lines; suppression of melanoma proliferation and self-renewal potential by AR silencing; and EdU incorporation assay in melanoma cells with or without AR silencing. AR silencing; that AR overexpression suppresses AR silencing effects; growth-suppressive effects of AR inhibitors on melanoma cells; and growth-stimulatory effects of DHT treatment of melanoma cells. AR-silencing gene signature; that AR silencing inhibits WM1366, A375, and SKMEL28 melanoma tumorigenesis; and that AZD3514 pretreatment inhibits WM1366 melanoma tumorigenesis. AR silencing in three melanoma cell lines  from transcriptomic profiling. AR gene silencing. AR signatures, including the associated P values from iLINCS database. Table S1is a summary of patient information of tissue microarray .Click here for additional data file.Table S2is a summary of a panel of human melanoma cell lines used in this study .Click here for additional data file.Table S3lists 155 genes up- or down-modulated by AR silencing in three melanoma cell lines  from transcriptomic profiling .Click here for additional data file.Table S4lists gene sets significantly associated with differentially expressed genes in melanoma cells upon AR gene silencing .Click here for additional data file.Table S5lists perturbagens with concordance with AR signatures, including the associated P values from iLINCS database .Click here for additional data file.Table S6lists reagents and resources.Click here for additional data file.


The introduction of organic solvents in the pretreatment can reduce over-degradation of cellulose and hemicellulose, but significance of organic solvent addition in pretreatment of different parts of sorghum stem is still unclear. Valorization of each component is critical for economy of sorghum biorefinery. Therefore, in this study, NaOH–ethanol pretreatment condition for different parts of the sorghum stem was optimized to maximize p-coumaric acid release and delignification efficiency, but significantly reduced hemicellulose deconstruction in NaOH–ethanol pretreatment. Optimization using the response surface methodology revealed that the pith, rind and whole stem require different NaOH–ethanol pretreatment conditions for maximal p-coumaric acid release and xylan preservation. By respective optimal NaOH–ethanol pretreatment, the p-coumaric acid release yields reached 94.07%, 97.24% and 95.05% from pith, rind and whole stem, which increased by 8.16%, 8.38% and 8.39% compared to those of NaOH-pretreated samples. The xylan recoveries of pith, rind and whole stem reached 76.80%, 88.46% and 85.01%, respectively, which increased by 47.75%, 15.11% and 35.97% compared to NaOH pretreatment. Adding xylanase significantly enhanced the enzymatic saccharification of pretreated residues. The total reducing sugar yields after respective optimal NaOH–ethanol pretreatment and enzymatic hydrolysis reached 84.06%, 82.29% and 84.09% for pith, rind and whole stem, respectively, which increased by 29.56%, 23.67% and 25.56% compared to those of NaOH-pretreated samples. Considering the separation cost of the different stem parts, whole sorghum stem can be directly used as feedstock in industrial biorefinery.Ethanol addition improved These results indicated that NaOH–ethanol is effective for the efficient fractionation and pretreatment of sorghum biomass. This work will help to understand the differences of different parts of sorghum stem under NaOH–ethanol pretreatment, thereby improving the full-component utilization of sorghum stem. Lignocellulosic biomass is an important feedstock for the production of biofuels and biochemicals . CelluloIn general, the purpose of the pretreatment is to remove lignin and hemicellulose, thereby increasing the enzymatic hydrolysis efficiency of cellulose . Xylan ip-coumaric acid , which is far higher than other agricultural waste biomass such as rice straw  [pCA is widely used in the health and pharmaceutical industries because of a variety of physiological functions such as anti-inflammatory, antineoplastic, and antimicrobial activities [pCA is also a precursor for the production of value-added aromatic chemical products [pCA is attached to lignin via an ester linkage [pCA and more than 90% of pCA can be released from agricultural residues [Sorghum is one of the main bioenergy crops, and the biorefinery of its soluble sugar and bagasse residue for biofuels and biochemicals has attracted much attention in recent years –20. Besil walls) , 22. pCAtivities . Its phetivities . pCA is products . In lign linkage . The estpCA in different parts of sorghum stem, but minimize the degradation of sugar polymers (cellulose and hemicellulose) as much as possible, and therefore enhance the total reducing sugar recovery. The processing conditions  were optimized using response surface methodology. Structural characterizations of raw and pretreated sorghum sample were investigated by Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM) and X-ray diffraction (XRD).Previous studies have reported the recalcitrance to enzymatic digestion in different parts of internodes from sugar cane due to cell type and chemical composition . The sugpCA in pith was 2.21%, which was slightly higher than that in rind (2.08%). The content of cellulose (40.64%) and lignin (24.04%) in rind was slightly higher than that in pith , while the xylan content of the rind (17.33%) was slightly lower than that of the pith (18.51%). The total carbohydrates including glucan, xylan, and arabinan in rind and pith reached 60.29% and 58.25%, respectively. It was worth noting that other components such as ash, extractives and lower content of sugars also exist in sorghum stems according to previous report [The composition of raw pith, rind and whole stem on a dry matter basis is shown in Table  rind 2.0%. The copCA and the recovery of xylan in residues.Box–Behnken models were designed to optimize various process parameters  in NaOH–ethanol pretreatment of different sorghum stem parts. The following equations were derived for the analysis of the release of pCA and the recovery of xylan in residues from different sorghum parts were investigated. Overall, NaOH concentration and ethanol content were the first and second most influential factors on the pCA release yield and xylan recovery yield, respectively. As shown in Table pCA from the sorghum stem were strongly depended on the NaOH concentration; however, some variation existed among different stem parts. At a low NaOH concentration , the release of pCA was very low, but significantly higher pCA was released from the pith than from the rind under the same conditions. As the NaOH concentration increased and the ethanol content exceeded 40% (v/v), the release of pCA from the rind slightly exceeded over that from the pith under the same conditions. NaOH concentration is also the key factor affecting the xylan dissolution, and more xylan was dissolved as NaOH concentration increased. In general, xylan was more resistant to be dissolved from the rind than from the pith in the same NaOH–ethanol conditions. This may be related to the difference in cell types and chemical composition in different sorghum stem parts. The pith is rich in parenchyma cells and the rind contains more vascular bundles. Parenchyma cells in pith have bigger lumens and thinner cell walls, and vascular bundles in rind are composed of tightly packed vessel elements [pCA and the recovery of xylan in residues for both pith and rind . As shown in Table pCA, and in turn shortening the processing time.The regression coefficients of the model were determined by analysis of variance (ANOVA) in Additional file pCA and the maximum recovery of xylan in residues for the pith, rind and whole stem in further experiments: 1.63% NaOH, 70% ethanol, 66 °C, 3.18 h; 1.90% NaOH, 70% ethanol, 69.8 °C, 1.00 h and 1.46% NaOH, 70% ethanol, 70 °C, 2.19 h, respectively. NaOH pretreatment was also carried out in same conditions (except ethanol) to further understand the significance of ethanol in NaOH–ethanol pretreatment. The solid recovery, pCA release and content of each component in solid residues are shown in Table pCA release and the glucan and xylan content of NaOH–ethanol-pretreated residues were relatively higher than the corresponding NaOH-pretreated residues, but the lignin content was lower than the NaOH-pretreated residues. These results suggested that ethanol addition promoted the release of pCA and delignification to a certain extent, but obviously prevented the deconstruction of xylan and cellulose. Compared to NaOH pretreatment, the release yields of pCA in pith, rind and whole stem by NaOH–ethanol pretreatment were increased by 8.16%, 8.38% and 8.39%, respectively ) and ferulic acid in pretreated liquid fractions were analyzed. The data showed that acetic acid and ferulic acid were the main inhibitors produced during pretreatments  were calculated. In above condition, the totalGlu. yields of NaOH–ethanol-pretreated pith, rind and whole stem were 87.92%, 84.14% and 85.72%, respectively  was calculated according to X-ray diffractograms. XRD analysis of untreated and pretreated sorghum samples is shown in Additional file pCA, respectively. Macroporous adsorption resin D101 was used to recover pCA, and the adsorption rate and desorption rate reached 96% and 91%, respectively. After desorption from resin column, the recovered pCA were 0.36 g, 0.35 g and 0.36 g, which accounted for 81.45%, 84.13% and 84.51% of the esterified pCA in sorghum pith, rind and whole stem, respectively. Since the macroporous adsorption resin also has an adsorption capacity on other hydroxycinnamic acid derivatives such as ferulic acid in liquid fraction, further purification procedure will be needed to obtain high purity of pCA. In this study, optimization using the response surface methodology revealed that the pith, rind and whole stem require different NaOH–ethanol pretreatment conditions for maximal pCA release and xylan preservation due to the difference in cell type and chemical composition of the pith and rind. From the perspective of pCA release yield and total sugar yield, however, there were no huge differences between the pith and rind if they were pretreated by respective optimal NaOH–ethanol conditions. Considering the separation cost of the different stem parts, whole sorghum stem can be directly used as feedstock for biorefinery.The process of pretreatment and enzymatic saccharification of sorghum samples (20 g) is shown in Fig. Moreover, the hemicellulose obtained from the liquid fractions of the pretreated pith, rind, and whole stem was 0.74 g, 0.38 g and 0.51 g, respectively, which contained 42.64%, 44.29% and 40.97% of xylan, respectively. The hemicellulose was collected and subjected to enzymatic hydrolysis for production of xylooligosaccharides (XOS). EpXYN1 displayed the best enzymatic hydrolysis efficiency, and the total XOS (xylobiose to xylohexaose) yields based on xylan from the pretreated pith, rind and whole stem were 31.19%, 32.71% and 30.28%, respectively  recovery. All the results suggested that NaOH–ethanol pretreatment is a promise pretreatment method of sorghum biorefinery for product fermentable sugars and value-added products.In this study, NaOH–ethanol pretreatment was used to treat different parts of the sorghum (pith and rind) to enhance the release of ® CTec2 (89 FPU/g) and β-glucosidase  were purchased from Novozymes China . Commercial xylanase  was purchased from Sigma-Aldrich . The xylanase EpXYN1 (130 BXU/mL), EpXYN3 (722 BXU/mL) and XynII (546 BXU/mL) were prepared according to our previous researches [Sorghum stem was obtained from Hengshui, Hebei Province, China. The pith and rind were separated by manual peeling with a sharp knife and washed three times with tap water to remove field dirt. After drying at 65 °C, sorghum samples were ground and passed through 40-mesh sieve. Cellulase Cellicsearches , 44. Oth3 (100 mg/L) prevents oxidation of the phenolic acid. The whole slurry was separated by vacuum filtration and washed by equal volume of water, then the liquids were combined. The treated solid was washed with water until the filtrate reached a neutral pH and then dried at 65 °C for the following experiments. The pH of NaOH–ethanol-extracted liquid fraction was adjusted to 1–2 with HCl, and then 1.5 times the volume of absolute ethanol was added to precipitate hemicellulose and allowed to stand at 4 °C for 24 h. The precipitate was collected as extracted xylan by centrifugation and dried at 65 °C for the following experiments. The liquid fraction was rotary evaporated to recover ethanol, and then the pCA was analyzed by high-performance liquid chromatography .The NaOH–ethanol pretreatment experiments were carried out with different temperature (60–70 °C) and time (1–4 h) in a plastic centrifuge tube. One gram of sorghum stem was suspended in 20 mL of mixed solution of NaOH  and ethanol . Addition of NaHSOpCA release, xylan recovery, glucan recovery, and delignification were calculated according to the following equations, respectively:The solid recovery, ® CTec2 cellulase (15 FPU/g substrate), β-glucosidase (30 CBU/g substrate) with/without xylanase (Sigma X2629-100 g) in a shaking incubator at 150 rpm.The pretreated residue was enzymatically hydrolyzed in a conical flask with phosphate buffer (pH 4.8), and the substrate was added at 2% (w/v). Sodium azide (10 mM) was also added to the solution to prevent microbial contamination. The enzymatic hydrolysis was conducted at 50 °C for 72 h in the presence of CellicThe glucose enzymatic hydrolysis yield, xylose enzymatic hydrolysis yield, total glucose yield, and total xylose yield were calculated according to the equations as follows:The enzymatic hydrolysis of extracted xylan from the liquid fraction of NaOH–ethanol-pretreated samples was carried out in phosphate buffer with a final solid loading of 5% (w/v) and 20 BXU/g substrate of xylanase. Sodium azide (10 mM) was added to the solution to prevent microbial contamination. The enzymatic hydrolysis process was incubated at optimum pH and optimum temperature for each enzyme  at 150 rpm in a shaking incubator for 24 h. The XOS in the supernatant was analyzed using ion chromatography .pCA release yield (%) and xylan recovery yield (%). A total of 29 runs were designed and 5 replicates were performed at the center point.The various process parameters involved in NaOH–ethanol pretreatment of different sorghum stem parts were evaluated using Box–Behnken design of Design Expert 11. The variables selected were NaOH loading , ethanol content , temperature (60–70 °C) and time (1–4 h). The analytical responses were pCA and ferulic acid) in the sorghum pith, rind and whole stem were analyzed according to the method described by Jiang et al. [2SO4 as the mobile phase with flow rate of 0.6 mL/min. All experiments were performed in triplicate and the average data were reported.The contents of esterified phenolic acid . The sample was scanned in the range from 4000 to 400/cm. SEM was used to observe the microstructure of the samples before and after pretreatment. Sample photographs were taken at a magnification of 1000 using FEI Quanta 200 (USA). The crystal structure of the lignocellulosic materials was analyzed using XRD. X-ray diffractometer  uses Cu-Kα (k = 1.54 Å) as a radiation source. The scan range was 5°–50° and the scan rate was 10°/min. The CrI of the crystalline sample was calculated from the XRD peak according to the following equation:pCA in the supernatant and desorbed with 70% (v/v) ethanol. PCA in the eluent was detected by HPLC.The overall mass balance of each process stage is described as Fig. Additional file 1. Additional figures and tables.


Traditional physiotherapy rehabilitation systems are evolving into more advanced systems based on exoskeleton systems and Virtual Reality (VR) environments that enhance and improve rehabilitation techniques and physical exercise. In addition, due to current connected systems and paradigms such as the Internet of Things (IoT) or Ambient Intelligent (AmI) systems, it is possible to design and develop advanced, effective, and low-cost medical tools that patients may have in their homes. This article presents a low-cost exoskeleton for the elbow that is connected to a Context-Aware architecture and thanks to a VR system the patient can perform rehabilitation exercises in an interactive way. The integration of virtual reality technology in rehabilitation exercises provides an intensive, repetitive and task-oriented capacity to improve patient motivation and reduce work on medical professionals. One of the system highlights is the intelligent ability to generate new exercises, monitor the exercises performed by users in search of progress or possible problems and the dynamic modification of the exercises characteristics. The platform also allows the incorporation of commercial medical sensors capable of collecting valuable information for greater accuracy in the diagnosis and evolution of patients. A case study with real patients with promising results has been carried out. Currently, there are more than 890 million people with chronic diseases worldwide . It is eOne of these cases is physiotherapeutic rehabilitation patients who, through current technological advances, could benefit from adapted, effective and easy-to-use rehabilitation systems from their own home. The exoskeleton-based rehabilitation systems available today for upper limbs are complex systems, difficult to install on the arm, and difficult to use. In addition, they have a heavy size that prevents the arm from moving naturally, making rehabilitation tasks difficult. Another added problem lies in the price of these devices, which causes that only the institutions and health centers can acquire them. The user does not have the possibility of carrying out rehabilitation exercises from the comfort of their home, they are also forced to go periodically to the physiotherapy center, which has the necessary equipment. Traditional rehabilitation systems also have a lack of motivation problem for patients, the vast majority of the exercises are based on repetition and this makes the sessions become monotonous and not very stimulating.The main objective of this work is to design a rehabilitation device based on an exoskeleton for the elbow of a degree of freedom (one DOF) connected to a virtual reality system called EXOMedical. This Virtual Reality (VR) system is specially designed for working immersively with the user, controlling the motor of the exoskeleton, and measuring the force exerted by the patient. In addition, a Context-Aware architecture  has beenCurrently, the rehabilitation process is carried out in a hospital or in specialized physiotherapy centers with the help and supervision of a professional in that area. The professional must perform the work of evaluation or triage as well as the monitoring and performance of the corresponding therapy. Due to the high number of patients, it may lead to the need for a large number of professionals to carry out all these activities and attend them correctly. In the same way, it is difficult to quantify the improvement or evolution of patients since there is currently no way to quantify them and the subjective assessment of an expert must be used. The developed system allows a quantitative measure of the evolution and capabilities of the patient over the Context-Aware architecture that has historical data on progress individually and in detail of the entire recovery. These data will serve the system to analytically measure the patient’s recovery, as well as the generation of new exercises adapted to that evolution. Although these processes are normally carried out in physiotherapy centers, the user can use it in a more comfortable place, such as in their own home, transmitting the data of their evolution to the platform, generating a more favorable and collaborative attitude on the patient part. As for chronic patients, this device allows an increasement in their quality of life by assisting in weightlifting. For example, a person who has suffered a car accident in which his arm has been damaged, or someone who has suffered a work accident or a stroke, can perform daily tasks such as moving weights of up to 15 kg without letting the effort fall on your body.This article is structured as follows: In the current literature, it is possible to find articles that address the use of robotic exoskeleton systems for the recovery of patients with mobility problems. The vast majority of these works are focused on the recovery of injuries and problems of the upper limbs. There are other works that focus on the study of injuries from other areas such as the ankle ,8,9. OthIn the works that address the recovery of the joints in the upper extremities, there are different projects that seek to provide significant progress . These wThe article that addresses the integral physical rehabilitation of the arm, highlights numerous works that use virtual reality techniques as an additional recovery tool. The authors of the paper  propose Another researching lines in upper limb rehabilitation devices are stroke patients who require specific rehabilitation to recover effective arm movement. The authors of the work , in theiAs for the works that address the design of Context-Aware architectures and frameworks, it is possible to find a large number of works based on telemonitoring and diseasing monitoring systems ,29,30,31It is possible to summarize that there is no work in the current literature that comprehensively addresses the design of a Context-Aware system in combination with a low-cost exoskeleton integrated with a virtual reality environment for performing rehabilitation exercises. The current systems based on exoskeletons are supervised and unconnected systems, without the possibility of sharing the data obtained or generating new exercises dynamically as the device proposed in this work.This section presents the system proposed in this work. Firstly, it is described in a connected hardware device that will serve as a rehabilitation exoskeleton for system patients. Next, the architecture based on Context-Aware technology for monitoring and control of the rehabilitation system is described. Finally, the virtual reality system that will connect to the hardware device and Context-Aware architecture and whose purpose is to provide an immersive user interface to make physical exercises is analyzed.The set of elements that make up the EXOMedical device are described below. This exoskeleton for the elbow consists of two parts that are attached to the outside of the arm and forearm with a series of velcro straps, as shown in The structure of the prototype has been built using 3D printing technology since it allows the construction of low-cost prototypes in a short time. Before performing the printing process, the 3D modeling phase has been carried out. This phase has required a long period of time due to the measurement and adjustment of the design. So it is adjustable to a large number of users. Considering the parametric design, it has been possible to design the structural 3D pieces in different sizes to adapt to the measurements of the different patients. Once the structure has been designed, it has been 3D printed with resistant and low-cost material such as PLA (Polylactic Acid). In future versions of EXOMedical, for cases where greater resistance is required, it will be possible to print a new exoskeleton on more durable materials such as ABS, NYLON, or carbon fiber. The motor used in the exoskeleton is a servo motor with a force of 15 kg, which is responsible for assisting the user in the task of exercising the arm. This servo, at the same time, allows making known the position in which the arm is, that is, the opening angle that will be used as an input value in the VR environment. In the same way that happens with the types of plastic, this servo can be equally scalable to get a greater pushing force helping to lift a greater amount of weight. This will be interesting in cases in which the patient has a superior muscular capacity. As can be seen, the device is highly configurable based on the needs and characteristics of the patients.The load cell in the exoskeleton has the functionality of obtaining the force that the user is exerting at a given moment. In this way, it is possible to know if it is necessary to apply a greater or lesser amount of assistance force with the motor for the realization of the movement, or the lifting of loads, as well as to measure the performance and evolution throughout the realization of the exercises. Specifically, the load cell used is based on a Gauge type cell that measures the electrical resistance in response to a force that is applied to the device. Generally, the element that measures that resistance, also known as a deformation meter, is made up of a very fine wire usually made of copper or aluminum material. This measuring element is based on a grid design so that when pressure is applied to this element, a linear change in resistance occurs. The resistors used in strain gauges are typically 120, 350, and 1000 Ω. The resistances used in each of the load cells have a different sensitivity to the voltage, a variable called “gauge factor”, which is generally used in metal-type strain gauges that are commonly used in most devices, is close to 2.The load cell model used in this work is the TAL220, industrially used in different fields. This load cell is designed for operating ranges between 2 and 200 kg. Specifically, the one that has been used is the 30 kg load cell since it is the closest assistance value to the average weight that a person can lift in a rehabilitation process. The internal resistance of the TAL220 model is all 1000 Ω.However, experimentally the following is verified: The variations that occur in a deformation meter are relatively small, of about few millistrain R1/R2 = R3/R4 it follows that Vout is 0, however, if there is a variation in one of the resistors, the Vout it will be affected, governed by the following Equation (Ohm’s law) (1):If Vin is a voltage that is constant and known and the resulting Vout is measured as follows If one of the resistors in the Wheatstone bridge is replaced, the resulting value in Vout can easily be measured and the force applied to the load cell can be obtained. On the other hand, the microcontroller used is an ESP8266. It is a microcontroller that contains 8 digital outputs and an analog input. It also has the ability to connect to the data network through WIFI technology and thus be able to send and receive data from the software architecture and VR environment without cables. It is also a low-cost device that allows its incorporation in a large number of Internet of Things (IoT) projects today ,36. So tThe important boom that has emerged in recent years in areas such as the Internet of Things and specifically in the so-called Wearable Internet of Things (WIoT) for the collection of physiological and medical data, has led to the application of new paradigms. New paradigms such as medical distributed computing that combine medical IoT devices and sensors to generate from the home environment, medical telemonitoring systems, and remote telecare. The existing WIoT architectures are highly centralized. During the last decades, cloud computing has been the technology base used to process and store data in the cloud instead of using the devices with limited resources that are composing the IoT environment. Cloud infrastructures facilitate the processing, storage, visualization, and real-time analysis of WIoT medical data. However, that cloud-based IoT health system is finding many barriers to handling the large health data that IoT currently generates. Edge computing (EoT) is a new technology that seeks to act as a service-oriented intermediate layer between the IoT health system and cloud computing. Edge computing is a solution that is in full expansion and offers efficient solutions to meet the important demands that telemedicine systems currently have. The objective is to increase the capacities available on the network, such as computing and storage capacity. These operations are performed on the edge of IoT-based systems, near data sources. Consequently, it moves calculations, storage and service provision from clouds to local peripheral devices, such as smartphones, gateways or smart routers, local wireless devices. These edge devices improve connectivity and allow to increase speed and data transfer for a faster and more efficient response.Context-Aware systems for current e-health environments are very focused on patient monitoring and follow-up. Specifically, these environments have been highly developed to perform a specific assistance task that helps the elderly patient. In addition, these are very centralized systems, especially focused on traditional Cloud environments. The disadvantages of these systems are the inability to handle large data due to their local structure, the lack of ability to generalize to other patients and other diseases, and lack of context-awareness. To all this, it is necessary to highlight the fact that there are hardly any works of Context-Aware systems focused on the aspect of rehabilitation of tasks and physical pathologies as the case of this work. Layer 1: Physical devices: This is the physical layer that binds both the exoskeleton sensors  and the possible medical sensors that can be added to the system and that can be used to monitor added medical parameters. As in the case of the pulse sensor or the ECG sensor that can emit valuable information about the patient’s physical condition while performing a rehabilitation exercise. All these devices, including the exoskeleton, have an 802.11 WiFi connection through which the data can reach the platform wirelessly.Layer 2: Local Context Monitoring: In this layer, which is deployed on the computer system at the local edge, there are the Context Provider and Context Aggregator modules that are responsible for managing the data generated by layer 1 (sensor system). There are also virtual reality blocks, the local database and the set of functionalities and remote services.Context Aggregator: This module is responsible for combining all simple contexts into a single Context State through the use of a context model [xt model . This elContext Provider: It is a service that is the main source for generating contexts. The Context Aggregator module transfers the low-level raw data generated by the different sensors to the Context Providers modules. These modules, in turn, are responsible for applying well-known techniques on this data to generate an elementary context from low-level data. For example, by applying pattern recognition techniques, it is possible to determine if a patient is correctly performing an exercise or is exhausted and therefore the exercise is being useless for rehabilitation.VR Environment: This module will be responsible for managing communication with the virtual reality simulation environment. It will act as coordination to send the exoskeleton data to the simulator and thus be able to make a real integration with the 3D environment. He will also be in charge of receiving back the values of the different tests that measure the performance and therefore the progress of the patient throughout the treatment. It will also be the key when generating the new scenarios and configure parameters generated by the system as the user advances or correct certain parameters that are determined to be unhelpful in case of detecting a lack of progress or regression.Local DataBase: It is a module responsible for managing the local database of the system that will store both the values of both the sensors deployed in layer 1 and the Context State generated by the Context Aggregator as well as all the results and evaluations produced during the VR exercises and simulations. This database has a double functionality. On the one hand, to perform a local persistence of the data to avoid loss or alteration of the data. On the other hand, a supporting function at the end of the computing tasks to identify patterns or anomalous situations in data.Remote Services: It is a module in charge of managing the remote services offered by Cloud architecture. Communications, data steps, and events are managed by this module, which will be in charge, for example, of managing and issuing the necessary alerts in the event that the system detects an abnormal situation in medical sensors. It will also be responsible for access services and medical records or request new exercises for a patient.Layer 3: Remote Context Monitoring: This last layer is located in an external and environmental Cloud to the other two layers. Its mission will be to manage and integrate the remote services for monitoring the context generated in the previous layers. This layer is managed by the central Personal Patient Monitoring Cloud module that is responsible for managing the rest of the modules and services of the system. It is a personal cloud that will be instantiated by each of the users so that all users have a private and secure cloud space. Among the modules deployed are Rehabilitation Exercises Cloud, e-Health Cloud Services, Medical Remote Monitoring, and Historical e-Health data:Medical Remote Monitoring: It is a module that will be responsible for providing the assigned medical professional with a set of functions for the proper management of the patient. Among these functions are online access to patient data, statistics, and advances. Reassignment or referral to other medical professionals to perform other treatments or alternative diagnoses. The assignment of new exercises for the patient or the modification of the configurations of certain exercises .Historical e-Health data: This module will manage all the data generated in the previous layers and that can be accessed by authorized medical professionals, as well as by the rest of the modules. This is a copy of the local database, which will also have the patient’s personal information and all his previous history.e-Health Cloud Services: This is the module in charge of the automatic management of the data generated and emitted by the system. This module will have the necessary internal tools and processes for the early detection of anomalies in medical data. As well as the constant monitoring of rehabilitation exercises performed by the user. It also has an automatic emergency called system if necessary.Rehabilitation Exercises Cloud: The system will have a large set of exercises and centralized configurations for performing rehabilitation exercises by patients. It will be possible to register new exercises, manage integration with the VR environment, and schedule exercise sessions that will be sent to the Local Context Monitoring environments of the different patients.The content of the exercises or games must be attractive and reasonably logical to capture the patient’s motivation.Positive feedback should be generated, encouraging rewards that help patients feel they are improving.Rehabilitation tasks and exercises should be integrated into exercises and games in an appropriate way and advised by an expert.Difficulty levels and settings must be designed to be applied to different patients and different stages of rehabilitation.Information on performance and evolution of patient training should be generated in real-time so that the system is able to assess its evolution and adapt to the context to generate new exercises or modify levels and settings.The virtual reality system that integrates the EXOMedical exoskeleton is based on the Unity 3D environment engine . IntegraThe EXOMedical device is integrated with the Oculus VR device  through The patient who is performing an exercise in the system, receives prior instructions on each of the exercises, visualizing through examples, the movements to be performed and the objective of the exercise or game. It also receives a set of visual and acoustic feedback that provides information about everything that happens in the VR environment. The user visualizes an avatar that represents their movements in the virtual environment and is able to recognize if they are performing the task correctly. In addition, visual or acoustic feedback can help patients understand the exact moments of the beginning and end of each exercise. This data is one of the most important because it provides the level of performance of a task, as well as the level of awareness of the patient about their evolution for the required exercise. The system can automatically modify some of the task parameters according to the real-time analysis provided by the Unity control unit. It will be possible to modulate each difficulty level of the exercise or the maximum time to complete the exercise. The environment will provide a reward in the form of scoring or unlocking new levels as the user’s skill progresses. All these data can also be modified by the medical expert in charge of the patient remotely, as well as visualize the results in real-time. The expert can monitor that the parameters generated automatically do not pose a danger to the patient. For example, to prevent the system from generating a very high simulated weight or a maximum unreachable time. With the aim of validating the system in a real environment, an experiment with 5 patients has been carried out over a period of one month. The study has been carried out due to the collaboration of a specialized physiotherapy rehabilitation clinic. All patients have voluntarily agreed to perform this experiment and have been duly informed. All procedures performed in studies involving human participants were in accordance with the ethical standards of the 1964 Helsinki declaration. The work has been approved by the ethical committee of the Expert Systems and Applications Laboratory Research Group . Four of the volunteers (three men between the ages of 23 and 47 and two women between 29 and 37) had previously been diagnosed with lateral epicondylitis of the elbow (or tennis elbow), while one of them was healthy (control patient). The study has been carried out over a month, where volunteers have held four sessions, the first session on day 1 of the study, the second at 7 days, the third at 14 days and the fourth at 30 days.The activities carried out in each session were simple exercises in the Virtual Reality environment, with different configuration parameters. Specifically, the patients carried out a Virtual Reality version of the classic Buzz Wire Game as shown in During each of the case study sessions, participants performed 20 activities of this game, progressively increasing the difficulty. Specifically, with each new exercise, the number of cable curves is increased, the internal diameter of the ring decreases and the estimated time to complete the exercise is reduced. As control variables, the positions, angle and time to perform each of the exercises have been analyzed. Of the 20 activities, 10 have been designed to be performed with simulated weight and the other 10 exercises with real weight. The results achieved by the patients involved in the case study can be observed in By individually analyzing one of the patients during the four sessions, it is possible to observe the evolution in their performance with the passing of the sessions. As can be seen in If patient 3 is analyzed for the same activities but performed with the real weight, it is possible to observe how the average performance was worse than in the case with simulated weight (as shown in This article presents the design of a training system for the rehabilitation of the elbow through a low-cost exoskeleton that is integrated with a virtual reality system. On this system, an architecture based on Context-Aware has been designed for intelligent management, the detection, and monitoring of the advances made by a patient in the system. The system has the functions of evaluating the rehabilitation, the advances, and all the data generated, with the aim of inferring knowledge that allows helping in its rehabilitation. Virtual reality technology is integrated into patient rehabilitation training in the form of interactive activities and games that generate a positive and motivating effect. These games and exercises are designed in such a way that the patient knows the state in which the exercise is, as well as its evolution and performance. Joint rehabilitation is achieved through fun repetitive training tasks where levels of difficulty are gradually increasing. In addition, through the Context-Aware architecture designed, a layer of intelligence is added to the system that allows, among other things, to track the automatic patient that, depending on the context data, allows new levels to be generated for their exercises or to detect possible anomalies or health problems.Compared to other rehabilitation systems based on exoskeletons and similar VR environments, this system has differential advantages. For example, in data acquisition, compared to other existing systems, the designed exoskeleton allows it to be installed in a simple way. It has a low cost and without cables that prevent a natural movement of the arm. In the aspect of the design of the exercises, the mechanisms and activities of this system are patterned according to the training specifications that are most suitable for proper rehabilitation. In addition, the exercises and games are extensible and easily expandable, due to the powerful engine designed by Unity3D and Oculus. It is also important to highlight how the rehabilitation plan will be generated automatically for the Context-Aware system and the observations of the medical expert in charge of the rehabilitation. This represents an important advance with respect to the systems in which only the expert could modify the parameters of the exercises. Considering the important database generated, and the different cases treated by the system, as new workouts are generated, the system will further refine its diagnoses and configurations. It should also be noted that the contents of the exercises and rehabilitation games can be loaded remotely by the system, being possible to add more elements to daily activities and generating a new sense of motivation about the patient. This allows the system to enrich the content of the activities and adapt them to the advances and performances of the patients. It is also possible to include more rehabilitation techniques in the future since the architecture is designed to open enough to do so. It is a connected device, aligned with the new technologies and paradigms based on IoT that allow managing data remotely, being accessible from anywhere in the world. In addition, the platform will allow not only the rehabilitation of patients but constant monitoring and follow-up of their medical parameters, being a very useful tool to be deployed in domestic environments.As a line of future work, we will study how to expand the exoskeleton to allow the rehabilitation of more arm joints and even the leg or neck. It will also be interesting to study exoskeletons for the rehabilitation of hands and phalanges of the fingers. In a future version of the system, a more friendly backend interface will be included so that any medical expert can configure the system parameters in a simpler way. Another line of future research will be to conduct a case study with a higher number of patients and with different medical problems to compare the evolution according to the pathology.


MNAT1 , a cyclin-dependent kinase-activating kinase (CAK) complex, highly expressed in diverse cancers and was involved in cancer molecular pathogenesis. However, its deliverance profile and biological function in osteosarcoma (OS) remain unclear.The expression of MNAT1 in OS was detected by western blot (WB) and immunohistochemistry (IHC). The potential relationship between MNAT1 molecular level expression and OS clinical expectations were analyzed according to tissues microarray (TMA). Proliferation potential of OS cells was evaluated in vitro based on CCK8 and OS cells colony formation assays, while OS cells transwell and in situ tissue source wound healing assays were employed to analyze the OS cells invasion and migration ability in vitro. A nude mouse xenograft model was used to detect tumor growth in vivo. In addition, ordinary bioinformatics analysis and experimental correlation verification were performed to investigate the underlying regulation mechanism of OS by MNAT1.In this research, we found and confirmed that MNAT1 was markedly over-expressed in OS tissue derived in situ, also, highly MNAT1 expression was closely associated with bad clinical expectations. Functional studies had shown that MNAT1 silencing could weaken the invasion, migration and proliferation of OS cells in vitro, and inhibit OS tumor growth in vivo. Mechanism study indicated that MNAT1 contributed to the progression of OS via the PI3K/Akt/mTOR pathway. We further verified that the MNAT1 was required in the regulation of OS chemo-sensitivity to cisplatin (DDP).Taken together, the data of the present study demonstrate a novel molecular mechanism of MNAT1 involved in the formation of DDP resistance of OS cells.The online version contains supplementary material available at 10.1186/s12885-020-07687-3. Osteosarcoma (OS) is the more usual devastating bone cancer in the young people with a frequency increasing by 0.3% per year . The morThe third subunit besides CDK7 and Cyclin H in cyclin-dependent kinase-activating kinase (CAK) complex was originally determined to be MNAT1 . MountinIn this research, we found MNAT1 expression was increased in OS cells and tissues. Upregulation of MNAT1 expression was associated with bad clinical expectations of OS patients. In addition, downregulation of MNAT1 inhibited OS cell proliferation and invasion ability in vitro, suppressed and slowed down tumor growth in vivo. Moreover, we showed that MNAT1 overexpression enhanced cisplatin resistance, and that MNAT1 silencing restored the sensitivity and effective of OS cells to cisplatin, a chemotherapy drug, through regulation of the PI3K/Akt/mTOR pathway. Our study provided a novel insight for the function of MNAT1 in the sensitivity of OS to chemotherapy and the mechanism involved.A total of 78 human OS samples and the corresponding non-tumor tissue samples were obtained from Affiliated Hospital of Qingdao University  between May 2009 and November 2018 (DQU cohort), after we obtained written informed consent according to an established protocol approved by the Ethics Committee of the Affiliated Hospital of Qingdao University. The diagnoses were confirmed by histological examination.OS cell lines MG63, U2OS, Well5 and 143B were purchased from the American Type Culture Collection , and Normal osteoblast cells HOBC and HFOB was acquired from the Cell Bank of the Chinese Academy of Sciences . The cell lines were cultured in Dulbecco’s modified Eagle’s medium  supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin.http://gdc-portal.nci.nih.gov/). DESeq package in R language was used to compare the MNAT1 expression between OS and non-tumor samples in TCGA dataset. Functional and pathway enrichment analysis was performed based on TCGA OS database via Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA).The independent OS microarray was extracted from The Cancer Genome Atlas (TCGA) database , 5′-GGTTGCCCTCGGTGTAAGAC-3′ (forward) and 5′-AGTTGCTCTTTCTGAGTGGAGT-3′ (reverse); GAPDH , 5′- GAGAAGGCTGGGGCTCATTT − 3′ (forward) and 5′- AGTGATGGCATGGACTGTGG − 3′ (reverse);TRIzol was used to obtain the total RNA, which was refrigerated at − 80 °C. The biological spectrometer was then used to assess the RNA concentration. For another, the PrimerScript RT Master kit  was used to do cDNA synthesis. The mRNA level of MNAT1 was detected by qRT-PCR with SYBRGreen PCR Master mix  on an ABI 7900 Real-Time PCR System . The relative fold-change in expression compared with control sample GAPDH was calculated using 2-The TMA were made from 78 OS tissues and matched nonneoplastic counterparts. A core (1.0-mm diameter) was punched from each OS tissue and arranged into the TMA blocks. For MNAT1 IHC analysis in TMA, MNAT1 staining was graded as negative (score 1+), weak (score 2+), moderate (score 3+) or strong (score 4+) for further nonparametric testing according to the percentage of cells staining positive and the staining intensity.Protein exacts were collected and lysed with RIPA lysis buffer. Equal amount of protein was loaded to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and wet transferred to PVDF membranes. Membranes were incubated sequentially with specific primary antibodies and secondary antibodies. Primary antibodies against MNAT1 , β-tubulin , PI3K , Akt  and mTOR .6 cells (per well) were plated into a 6-well plate, and plasmids, siRNA targeting MNAT1 or negative control were transfected into the cells using Lipofectamine 2000  following the manufacturer’s instruction. The transfected cells were harvested after 48–72 h. The transfection efficiency was determined by qRT-PCR. The sequence of the siRNA and shRNA were listed as following: MNAT1-siRNA sequence: 5′-AAGACCACCAAATATCGGAAC-3′; MNAT1-shRNA sequence: 5′-CCGGCCTAGTCTAAGAGAATACAATCTCGAGATTGTATTCTCTTAGACTAGGTTTTT-3′.The MNAT1 siRNA and MNAT1 plasmid  were purchased from Ribobio , a scramble oligonucleotide was referred to as negative control (si-NC). For transfections, 1 × 10For the stable knockdown of MNAT1, the annealed siRNA sequences were cloned into the LV-12 (pGLVH6-CMV-LUC-2A-Puro-U6-shRNA) vector to generate a MNAT1-shRNA lentivirus (shMNAT1) . U2OS cells were transduced with the concentrated shMNAT1 or control virus.3 cells per well were seeded into 96-well plates, with three wells used for each assayed group. Briefly, Cell numbers were evaluated over 5 days by CCK-8 Kit  method. The DNA synthesis rate was evaluated through Edu staining assay , EdU positive cells were observed by using an Apollo and DAPI staining. For the colony formation assay, 1000 cells/well were plated into 6-well plates and routinely cultured for 14 days. The cells were subsequently fixed with 30% formaldehyde for 15 min and stained with 0.1% crystal violet. The number of colonies (containing more than 50 cells) was determined under an optical microscope. These experiments were in triplicate.When MNAT1 siRNA or MNAT1 plasmid was transfected into U2OS and 143B cells. 5 × 10Wound-healing assays were carried out to determine the migration ability. U2OS and 143B cells expressing MNAT1 were seeded 24 h before the experiment. When the convergence degree of the cell reaches 90–100%, linear scratches are produced at the tip of the 200 μL pipette tip. Cells were observed using a light microscope (40× magnification) every 24 h. These experiments were in triplicate.4/ml, and then plated into the upper chamber in 200 μl completed medium. Six hundred microliter of completed medium containing 10% FBS was added into the lower chamber. After 24 h incubation, Transwell chamber with remaining cells was removed, and then the invaded cells were washed, fixed with 4% paraformaldehyde, and stained with crystal violet for 20 min. The number of invaded cells was counted in random non-overlapping field under a light microscope. The average number of cells in each field was counted.In vitro cell invasion was tested by Transwell assays. The logarithmic U2OS and 143B were collected and the number of cells was adjusted to 5 × 106 U2OS cells stably transduced with a lentivirus expressing either sh-MNAT1 or sh-NC was subcutaneously injected into nude mice. The tumor volume was calculated by the formula: Tumor volume = (width)2 × length / 2. The study protocol was also approved by the Committee on the Use of Live Animals in Teaching and Research.Six to eight-weeks-old male mice were used to construct xenograft tumor model. A total of 100 μl of a cell suspension containing 3 × 10p < 0.05 is considered to be statistically significant.All analyses were performed with GraphPad Prism V6 . All experiments were repeated at least three times to calculate the mean and standard deviation (SD). The survival curves were calculated by Kaplan-Meier method. A * With the purpose of determining the expression of MNAT1 in the OS, we evaluated the expression of MNAT1 in tissues from patients diagnosed with OS and several cell lines as representative of OS. Firstly, we found that the expression of MNAT1 was enhanced in MG63, U2OS, Well5 and 143B cells than that in control cell lines, the difference is significant  by immunohistochemistry (IHC) Fig. a. ConsisTo detect biological functions of the MNAT1 in OS cells, we performed functional experiments. We found that specific siRNAs targeting MNAT1 decreased the expression of MNAT1 after transfection of U2OS and 143B cells  OS database to analyze the mechanism of MNAT1 in OS. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) enrichment analysis suggested that PI3K/Akt/mTOR signaling pathway closely correlated with high MNAT1 expression Fig. . We repeTo investigate whether MNAT1 was involved in the chemosensitivity of OS to DDP, we used a gain or loss-of-function approach in U2OS and 143B cells. As shown in Fig. Although in-depth knowledge has been made in the diagnosis and treatment strategies of OS, due to its delayed diagnosis and lack of effective treatment strategies, its mortality rate remains high , 11. TheTumor is caused by the accumulation of multiple oncogenes and the inactivation of tumor suppressor genes. This research confirm that MNAT1 is a neoteric oncogene in OS clinical expectations. In this research, we revealed that MNAT1 was upregulated in OS cancer tissues and cell lines Fig. . More imTo further investigate mechanism of MNAT1 on progression of OS, previously described bioinformatics and mechanism studies indicated that PI3K/Akt/mTOR pathway was extremely relevant to expression of MNAT1 Fig. a and b. Previous studies reported that OS is prone to multidrug resistance –21. Howe. Moreover, MNAT1 overexpression contributed to the enhanced malignancy in OS cells including high proliferation, high invasion, and enhanced DDP chemoresistance. Our results suggest a profound insight into the development of OS, and provide a potential therapeutic target for the treatment of OS.MNAT1 was upregulated and functioned as an oncogene through activating PI3K/Akt/mTOR pathway in OS. Knockdown of MNAT1 inhibited OS proliferation and invasion both in vitro and in vivoAdditional file 1:Figure S1. MNAT1 regulated the activity of CAK. U2OS and 143B cells treated with si-MNAT1 or MNAT1 plasmid. Western blot analysis of CDK7 and Cyclin H proteins in U2OS and 143B cells.Additional file 2:Figure S2 Mechanism study of OS by MNAT1.  GSEA analysis the enrichment of pathways between MNAT1 high group and low group.


Around 80–90% of prostate cancer (PCa) cases are dependent on androgens at initial diagnosis; hence, androgen ablation therapy directed toward a reduction in serum androgens and the inhibition of androgen receptor (AR) is generally the first therapy adopted. However, the patient’s response to androgen ablation therapy is variable, and 20–30% of PCa cases become castration resistant (CRPCa). Several mechanisms can guide treatment resistance to anti-AR molecules. In this regard, AR-dependent and -independent resistance mechanisms can be distinguished within the AR pathway. In this article, we investigate the multitude of AR signaling aspects, encompassing the biological structure of AR, current AR-targeted therapies, mechanisms driving resistance to AR, and AR crosstalk with other pathways, in an attempt to provide a comprehensive review for the PCa research community. We also summarize the new anti-AR drugs approved in non-metastatic castration-resistant PCa, in the castration-sensitive setting, and combination therapies with other drugs. Prostate cancer (PCa) is the fifth leading cause of cancer death worldwide, and its incidence has been increasing in the U.S. since 1950, apparently related to an overall increase in life expectancy -ribose) polymerase inhibitors (PARPi), nanoparticle-based drugs, immunotherapeutics, and radioactive iodine, respectively. A phase 1 study of PARPi niraparib with ARSi apalutamide or abiraterone acetate plus prednisone in people with mCRPCa with or without DNA damage repair (DDR) defects has recently been completed [NCT02924766]. Another phase 1 study of the combination of niraparib and enzalutamide in men with mCRPCa has been terminated [NCT02500901]. A phase 2 study currently recruiting patients is testing CRLX101—a nanoparticle drug conjugate with camptothecin—plus enzalutamide in mCRPCa patients progressing under enzalutamide [NCT03531827]. In a phase 1b/2 study, enzalutamide is being included in a treatment arm (arm C) with anti-PD-L1 avelumab and bempegaldesleukin  for mCRPCa patients [NCT04052204]. In addition, a randomized phase 2 study is evaluating I-131-1095 radiotherapy in combination with enzalutamide compared with enzalutamide alone in chemotherapy-naïve prostate-specific membrane antigen (PSMA)-avid mCRPCa patients progressing under abiraterone [NCT03939689] .PTEN (Phosphatase And Tensin Homolog) mutations occur in 8% of all PCa patients and correlate with worse outcomes, along with reduced benefit from ARSi molecules. The initial results of the phase 3, double-blind, placebo-controlled, randomized IPATential150 trial) i.e., Ipatasertib plus Abiraterone vs. Placebo plus Abiraterone in Metastatic Castration-Resistant Prostate Cancer) were presented at the most recent ESMO Meeting. A total of 1101 asymptomatic or mildly symptomatic untreated mCRPCa patients were randomized (1:1) to receive ipatasertib plus abiraterone acetate versus abiraterone acetate alone. Patients with PTEN-loss and those who were treated with the combination arm showed a significant improvement in median radiographic PFS, with a risk reduction of 23%.Investigating AR-targeted therapies continues to be a cornerstone in PCa research, throughout all stages of disease. In very high risk clinically localized PCa patients, the phase 3, double-blind, randomized ANZUP1801 trial  has been planned to investigate the addition of the ARSi darolutamide or placebo to ADT and definitive/salvage radiotherapy; survival data are awaited. At the American Society of Clinical Oncology (ASCO) Virtual Annual Meeting 2020, updated results of the PROSPER, SPARTAN, and ARAMIS trials demonstrated improvements in OS for patients with non-metastatic CRPCa randomized to enzalutamide, apalutamide, and darolutamide, respectively, as compared to ADT alone. A post hoc analysis of the ARCHES trial with stratification by baseline PSA levels was presented at the ESMO  Virtual Annual Meeting 2020. The authors found that the benefit of enzalutamide over placebo in terms of Radiographic progression-free survival (rPFS) was consistent across three strata of baseline PSA values, ≤0.2, 0.2–4, and >4 ng/mL. Preliminary data of the phase 3 IMbassador250 trial presented at the AACR (American Association for Cancer Research) 2020 Virtual Meeting show no survival benefit with the checkpoint inhibitor atezolizumab combined with enzalutamide in mCRPCa patients after disease progression to abiraterone acetate. Of interest, a very recent phase 1 trial of the c-MET  inhibitor crizotinib plus enzalutamide in men with mCRPCa showed a marked reduction in systemic exposure of crizotinib, likely caused by enzalutamide induction of Cytochrome P450 3A4 (CYP3A4) . This evDuring recent decades, several therapies have been developed for PCa treatment, and the therapeutic armamentarium is continuing to increase. AR signaling is the main pathway involved in PCa growth, and accordingly, anti-AR molecules are in development at all stages of PCa, from high-risk localized tumors to mCRPCa stages. Despite the wide use of AR-targeted therapies, biomarker-driven tools capable of orienting therapeutic choices are so far lacking in these patients when considering the drug therapies reported here. This could become a serious embarrassment for clinicians when all the anti-AR therapies become available and are introduced into daily clinical practice. Conversely, according to the last National Comprehensive Cancer Network (NCCN) PCa guidelines, molecular-driven therapy is currently a well-defined approach in mCRPCa patients, both for the PARPi olaparib with homologous repair gene mutated tumors and for the immune checkpoint blocker pembrolizumab when MicroSatellite Instability High (MSI-H) or MisMatch Repair deficiency (dMMR) does occur.In the near future, one dangerous risk from the extensive use of therapies targeting the AR axis could be the increase in AR-independent tumors, notoriously associated with worse prognosis. In the era of precision medicine, the main question for the clinician is “what is the best treatment option for my patient?” The continuously improving diagnostic techniques, along with the increasing amount of data emerging from clinical trials, will allow a better understanding of the molecular characteristics of the tumor and their predictive significance for treatment resistance or sensitivity.