The B-cell receptor enables individual B cells to identify diverse antigens, including bacterial and viral proteins. While advances in RNA-sequencing (RNA-seq) have enabled high throughput profiling of transcript expression in single cells, the unique task of assembling the full-length heavy and light chain sequences from single cell RNA-seq (scRNA-seq) in B cells has been largely unstudied.We developed a new software tool, BASIC, which allows investigators to use scRNA-seq for assembling BCR sequences at single-cell resolution. To demonstrate the utility of our software, we subjected nearly 200 single human B cells to scRNA-seq, assembled the full-length heavy and the light chains, and experimentally confirmed these results by using single-cell primer-based nested PCRs and Sanger sequencing.http://ttic.uchicago.edu/∼aakhan/BASICBioinformatics online. During de novo assembly method to determine the full-length sequence of the BCR in single B cells from scRNA-seq data, called BASIC (BCR assembly from single cells). To demonstrate the utility of our method, we subjected nearly 200 single human B cells to scRNA-seq and assembled full-length heavy and light chains. We then experimentally validated these results by using single-cell PCR and Sanger sequencing, and demonstrate overall high accuracy.Here, we developed a novel semi-de novo assembly in two stages  and constant  region sequences in human from IMGT (http://www.imgt.org). The database was indexed using Bowtie2 . Briefly, BASIC extends each anchor iteratively in the 3' direction (one read at a time) until there is either no overlapping read or a repeat is found. Then, each anchor is extended in the 5’ direction in the same way. For each chain, BASIC reports a single sequence if the extended sequence from the variable region anchor is equal to the extended sequence from the constant region anchor. However, if the two sequences did not match, BASIC reports both an extended variable region contig and an extended constant region contig, separately.t chains . We assuThe running time of BASIC mostly depends on the length of the sequencing reads and the number of reads. BASIC is implemented in Python and uses multi-core processing to assemble the heavy and light chains simultaneously.We obtained antibody producing B cells (plasmablasts) by fluorescence-activated cell sorting from the peripheral blood of seven human donors. These samples were subjected to scRNA-seq using an adapted version of the SmartSeq2 protocol , and theIn 37 situations, our initial nested PCR was unable to amplify the BCR using a cocktail of primers, potentially due to competition between primers preventing amplification or a mutation in the primer-binding site J gene usage as obtained by Sanger sequencing in both heavy and light chains in 370/382 (∼97%) of the sequences. Importantly, BASIC was able to correctly identify the V(D)J sequence across a range of somatic alterations and sequencing depths  of the immunoglobulin sequences. It stands to reason that sample quality and, in turn, sequencing coverage of the BCR is a major determinant for accurate assembly. While BASIC does not explicitly use pairing information, the additional sequences generated from paired-end sequencing likely provides for greater coverage of the BCR and implicitly facilitates the de novo approach. We assembled all 191 scRNA-seq samples using Trinity, a state-of-the-art, purely de novo approach J gene usage in the to BASIC . At the to BASIC . Taken tde novo-based approach. For the first time, BASIC can help couple gene expression information from scRNA-seq with immune repertoire, and facilitate studies between B-cell receptor features, clonality, differentiation and transcriptional programming at single-cell resolution.The BCR is generated through an immunological process known as affinity maturation and is ultimately secreted in soluble form as antibodies. During this antibody affinity maturation process, somatic rearrangements and mutations are introduced into the BCR to improve antigen recognition. We have introduced a novel algorithm, BASIC, which enables investigators to assemble BCR sequences from scRNA-seq data and study B-cell repertoire at single-cell resolution. We have experimentally validated sequences assembled by BASIC, and demonstrate overall high accuracy and in particular the superiority of an anchor-guided assembly strategy over a purely Supplementary DataClick here for additional data file.


KRAS is the most common and, simultaneously, the most ambiguous oncogene implicated in human cancer. Despite KRAS mutations were identified in Non Small Cell Lung Cancers (NSCLCs) more than 20 years ago, selective and specific inhibitors aimed at directly abrogating KRAS activity are not yet available. Nevertheless, many therapeutic approaches have been developed potentially useful to treat NSCLC patients mutated for KRAS and refractory to both standard chemotherapy and targeted therapies.The focus of this review will be to provide an overview of the network related to the intricate molecular KRAS pathways, stressing on preclinical and clinical studies that investigate the predictive value of KRAS mutations in NSCLC patients.A bibliographic search of the Medline database was conducted for articles published in English, with the keywords KRAS, KRAS mutations in non-small cell lung cancer, KRAS and tumorigenesis, KRAS and TKIs, KRAS and chemotherapy, KRAS and monoclonal antibody, KRAS and immunotherapy, KRAS and drugs, KRAS and drug resistance. Lung cancer is the leading cause of cancer-related death worldwide, despite a reduced incidence in western countries and a remarkable improvement in its therapeutic approach. Among lung tumors, Non Small Cell Lung Cancer (NSCLC) is the most common diagnosis and the adenocarcinoma is the predominant subtype . SeveralThe majority of these alterations are targetable by the EGFR tyrosine kinase inhibitors (TKIs)  –8.However, there are no specific approved drugs for patients with KRAS mutant tumors and all the anti-KRAS evaluated compounds have failed to demonstrate any clinical activity. Indeed, because of the high frequency of KRAS mutations in NSCLC, several preclinical and clinical investigations have been conducted including inhibition of KRAS protein expression via RNA interference (RNAi), blocking post-translational modification with farnesyl-transferase inhibitors (FTIs) or blocking KRAS localization at the cellular membrane –11. DiffThis review focuses on the molecular pathways of KRAS in order to point out possible targets for an anti-KRAS approach reporting success and failures of compounds developed to date.A bibliographic search of the NCBI PubMed database was conducted for articles published in English, using the following keywords: KRAS, KRAS mutations in non-small cell lung cancer, KRAS and tumorigenesis, KRAS and TKIs, KRAS and chemotherapy, KRAS and monoclonal antibody, KRAS and immunotherapy, KRAS and drugs, KRAS and drug resistance.KRAS belongs to a group of small GTP-binding proteins called the RAS superfamily or RAS-like GTP-ases. This group includes Harvey-Ras (H-RAS), neuroblastoma-Ras (N-RAS) and two splice variants of KRAS: KRAS4A and KRAS4B . FollowiKRAS is mutated in 15-25% of NSCLC, mostly adenocarcinoma and occasionally squamous cell carcinoma . There iKRAS and EGFR mutations are usually mutually exclusive and, therefore, KRAS mutations can be considered as innate resistance factor for anti-EGFR TKI. However, recent published data, obtained with high sensible technologies, suggest that some tumors can share EGFR and KRAS mutation in a heterogeneous tumor cell population, as well as the co-occurrence of genomic alteration in LKB1 and TP53 –39.One effect of KRAS activation is the induction of telomerase (TERT) transcription . RecentlZhang and colleagues evaluated the anti-tumor effect of an anti-KRAS ribozyme adenoviral vector (KRbz-ADV) in NSCLC cell lines with or without KRAS mutation, finding that KRbz-ADV inhibits significantly the growth of KRAS mutant than wild type cells .Using an RNA interference (RNAi), Sunaga and colleagues in 2011 investigated if the knock down mutant KRAS transcript may revert the malignant phenotype of NSCLC. KRAS expression was inhibited and cell proliferation was reduced alongside with a down regulation of MAPK pathway, however, tumorigenicity was not abolished. These findings remarked the complexity of mutant KRAS oncogenic signaling and cell capability to overcome the KRAS “targeted inhibition” . DespiteThe histone deacetylase inhibitors (HDACi) block gene transcription, inhibit proliferation and induce apoptosis in tumor cells with promising results for the treatment of some neoplastic proliferative diseases . Kurtze in vitro and in chemically-induced KRAS-mutant lung tumors in mice ..77].In preclinical models, docetaxel in combination with selumetinib showed an important inhibition of tumor growth and regression . A randoTrametinib, has been evaluated in a phase I trial in combination with docetaxel or pemetrexed in advanced NSCLC patients with or without KRAS mutations . Both coAs far as it is known, KRAS mutant NSCLCs do not respond to EGFR-TKIs treatment . The comCyclin-dependent kinases (CDKs) are critical proteins for cell cycle’s. Proliferation stimuli, including those through KRAS, converge on the complex CDK4/6 cyclin-D, a critical regulator of the transition between phase G1 and S .CDK4 has been shown necessary for tumor progression in a KRAS-induced lung adenocarcinoma model . AbemaciHeat Shock Proteins (HSPs) are adenosine triphosphate (ATP)–dependent chaperones with an important role for the cell response to stress and for maintaining cellular homeostasis. The ubiquitously expressed HSP90 has been studied intensively because of its involvement in the folding, stability and function of several oncogenic driver proteins. Interestingly, HSP90 chaperone is necessary for the maturation of proteins involved in KRAS downstream pathways, such as mTOR and MEK . Hence, Recently, the attention has turned into the discovery of drugs able to interfere with specific immune checkpoints, among which programmed death-1 receptor (PD-1) and its ligand (PD-L1) have been the most studied in NSCLC. PD-1 and PD-L1 are expressed by activated immune cell types, including T-cells, B-cells, dendritic cells, and their interaction negatively regulates immune activity in peripheral tissues in response to infection or tumor progression . SeveralFDA has recently approved nivolumab an anti-PD-1 antibody, for metastatic NSCLC progressed after prior platinum-based chemotherapy . SubsequHowever, PD-L1 is clearly not an easy-to-handle biomarker. In fact, different assays are used to determine its expression levels, with different cut-off of PD-L1 positivity making difficult the definition of a strong cut-off value for PD-L1 positivity in NSCLC.p = 0.043) and a higher mutation rate in patients with lower PD-1 expression (8 out of 10 KRAS mutant patients); whereas PD-L1 expression was higher in patients harboring EGFR mutations or with wild-type KRAS status [p = 0.018) [Interestingly, several data report that a high mutational burden is a positive predictive biomarker of response to immunotherapy . For thiS status . MoreoveS status . Scheel = 0.018) .Recently, according to findings from the phase III OAK trial, atezolizumab, an anti-PD-L1 antibody, improved survival compared with docetaxel in NSCLC patients following the failure of platinum-based chemotherapy, regardless of PD-L1 expression or histology. Even if the number of patients with KRAS mutations was small, the benefit was consistent also across this subgroup .Concerning the association between KRAS mutations and the response to anti-PD-1 antibodies, results of published studies are still limited and controversial.To conclude, the results for immune checkpoint inhibitor in NSCLC are encouraging, however, a multitude of questions related to predictive biomarkers to anti-PD-1/anti-PD-L1 therapies remains unanswered.A new hypothesis suggests that the extreme mutational heterogeneity of a tumor, such as in KRAS mutant NSCLC , may plaIn a recent study on cell-free circulating tumor DNA (cftDNA), Del Re and colleagues evaluated the appearance of KRAS mutations in EGFR positive NSCLC patients progressed after a TKI regimen. Patient that developed a KRAS mutation showed a worse survival compared to KRAS wild-type patients, suggesting a role of KRAS mutations also in acquired resistance to anti-EGFR TKI . GuibertSeveral preclinical and clinical investigations have been launched with the hope to better understand the biologic world that surround the KRAS gene, its potential prognostic and predictive role and, importantly, to look for effective treatments for NSCLC patients harboring KRAS mutations. However, KRAS targeting seems to be a real challenge to overcome, a direct KRAS-targeting is probably not efficacious because it is able to activate multiple mechanisms of escape under the selective pressure of treatments. One of the best pharmacological rational approach could be based on a combination of treatments, in order to silence more that one driver at the same time. However, the toxicity-side in this case plays an important role and needs to be strongly considered.Tumor heterogeneity increases the complexity of the system . AcquireTherefore, the landscape is becoming complex considering that KRAS mutations can concomitantly occur with two or more driver alterations in the same tumor.Although we are fully aware of the laborious path that leads the scientific community to face this challenge, we are confident that some of the attempts discussed in this contest could be an effective treatment for KRAS mutant NSCLC patients, and we strongly believe that in this landscape a multidisciplinary approach can help in the management of this complex disease .


Aptamers are nucleic acids referred to as chemical antibodies as they bind to their specific targets with high affinity and selectivity. They are selected via an iterative process known as ‘selective evolution of ligands by exponential enrichment’ (SELEX). Aptamers have been developed against numerous cancer targets and among them, many tumor cell-membrane protein biomarkers. The identification of aptamers targeting cell-surface proteins has mainly been performed by two different strategies: protein- and cell-based SELEX, when the targets used for selection were proteins and cells, respectively. This review aims to update the literature on aptamers targeting tumor cell surface protein biomarkers, highlighting potentials, pitfalls of protein- and cell-based selection processes and applications of such selected molecules. Aptamers as promising agents for diagnosis and therapeutic approaches in oncology are documented, as well as aptamers in clinical development. During the partitioning step, nucleic acid molecules which bind to the target are selected while the vast majority of sequences which do not bind are washed away. Binding molecules are amplified thanks to the fixed primer-binding sequences flanking the variable region, by PCR or RT-PCR according to the nature of the oligonucleotide, ssDNA or RNA. Double-stranded DNA molecules are then separated from ssDNA in DNA-SELEX, or in vitro transcribed in RNA-SELEX by means of a T7-RNA polymerase binding site in the fixed region. The three steps  constitute a round of SELEX. Negative selection to environmental elements  and/or counter selection to target’s counterparts (like related proteins or cells) is usually performed, either before or after the positive selection, to eliminate non-specific binding nucleic acids. The rounds of selection are repeated several times, increasing stringency progressively, until molecules with the desired binding properties are cloned and sequenced. Those selected oligonucleotides are named aptamers, from the greek aptus (“to fit”) and the suffix “-mer”. Databases dedicated to aptamers provide information on targets of specific aptamers, length, molecular weight, extinction coefficient, GC (guanine-cytosine) content, chemistry, primary sequences, predictive secondary structures, as well as affinities, assay buffers…  or RNA molecules. They are selected through a fully in vitro well-established iterative process known as ‘selective evolution of ligands by exponential enrichment’ (SELEX) ,2,3. A lexample, ).More than 900 aptamers have been generated from SELEX  towards The success of a SELEX process relates to the identification of aptamers of high affinities and specificities for their targets. Identification of aptamers is more complex for cell-surface proteins which activities depend on their conformation and on their cellular environment than for non-amphipatic molecules. To target cell surface biomarkers, it can therefore be important when possible to choose selection conditions and processes mimicking as far as possible the targets natural environment. This review will thus focus on the main selection strategies which have been used to identify aptamers to tumor cell-surface proteins, highlighting differences, success, and limitations of the SELEX processes. Tumor cell-surface biomarkers used as targets for SELEX are listed in Owing to their three-dimensional conformation and the strong shape complementarity between aptamers and their targets, aptamers are known to recognize their specific target with high affinity and selectivity. Analogous to antibodies in their range of target recognition and variety of applications, they are referred as ‘chemical antibodies’ . Aptamer2OH) or 2′-methoxy (2′-O-Me) groups, LNA [TM assay, a highly sensitive proteomic tool for discovering and validation of biomarkers. Capping aptamers with inverted nucleotides is another alternative to reduce exonuclease degradation [RNA aptamers fold into more diverse three-dimensional structures than ssDNA aptamers, because of their 2′-hydroxyl (2′-OH) group on ribose and the non-Watson-Crick base pairing. The chemical production of ssDNA aptamers is easier and cheaper than RNA aptamers. But the preparation of ssDNA molecules during the SELEX process is more challenging than RNAs ,18. Nuclups, LNA . Synthetups, LNA ,28. Goldups, LNA  demonstrups, LNA . These mradation . The natradation ,33,34. Tradation ,35. Spieradation ,39,40,41Different SELEX processes have been developed for the selection of aptamers targeting tumor cell-surface protein biomarkers. Protein SELEX is the simplest form of SELEX process a. Table Cell surface proteins used as targets for protein-based SELEX are either full-length or truncated versions of full length proteins, generally recombinant ectodomains coupled to tags , facilitating purification and selection by affinity. Peptides can also be used as targets. In that case, the advantages linked to the exact knowledge of the aptatope, and to the facility of production of large amounts of targets can be offset by the limitations of these peptides as protein mimics. Cell-surface proteins are amphipatic membrane proteins, and therefore not easily extracted from the lipidic membrane, purified and solubilized. Even though membrane proteins can be purified and solubilized, large amount of proteins are needed for a whole protein-SELEX procedure. Further, full-length membrane proteins or ectodomains, expressed in prokaryotic or lower eukaryotic systems, may lack or have different post-translational modifications . For example, the 2′F-RNA aptamer E21, elicited against the EGFRvIII ectodomain produced in bacteria, did not bind to the native protein expressed from eucaryotic cells because glycosylation, a post-translational modification present only in eukaryotic systems, significantly alters the structure of the target protein .D (47–85 nM) than those obtained for aptamers to peptides, which might be due to an unstructured MUC-1 protein [Some of the biomarkers have been subjects to different SELEX, like MUC-1, that allowed comparison between aptamers targeting proteins and peptides mimics of proteins. For example, Ferreira et al.  selected protein .Overall, the main disadvantage of protein SELEX is that purified and solubilized membrane proteins, recombinant proteins and peptides may not adopt the same state , than the cell-surface biomarker in its endogenous environment. Thus, some aptamers selected against purified membrane proteins failed to recognize their targets in whole cells ,78, limiThe general process of cell-SELEX is shown in Depending on the objective, knowledge of the target identity prior to selection can be useful, or not. Therefore, different strategies can be distinguished:When the objective of a cell-based SELEX is the identification of aptamers to a clearly identified cell-surface biomarker b, the SEC634Y mutant receptor tyrosine kinase overexpressed in PC12 cells [Different procedures have been developed to direct the recognition of the target by the aptamer. For example, ligand-guided selection (LIGS) SELEX guides the selection to a specific epitope of a known cell-surface target. Zumrut et al. ,106 used12 cells , the HER12 cells , CD16α o12 cells , integri12 cells , the tra12 cells . In this12 cells  used anoCell-based SELEX involves positive selection to collect aptamers that interact specifically with the target cells and usually counter selection to eliminate nonspecific nucleic acid sequences binding to negative cells. Different human tumor cell lines have been used for positive selection: glioblastoma , breast carcinoma , ovarian cancer (SKOV3), gastric cancer (N87), lung carcinoma , lymphoma , liver cancer (HepG2), prostate adenocarcinoma (PC-3), cervical cancer (HeLa). The PC12 cell line derived from pheochromocytoma of the rat adrenal medulla has also been used, as well as other non-tumoral cells lines, like Chinese hamster ovary (CHO), Human embryonic kidney (HEK) cells. The choice of the couple of cells used for positive- and counter-selections is of great importance for cell-based SELEX on pre-identified cell-surface protein. The two cell type should display a high difference in target expression levels, so that aptamers interact specifically with the target on positive cells and does not interact with cells used for counter-selection which does not display or displays lower levels of the target protein. For positive selection, the pre-identified target can be naturally expressed or over-expressed at the surface of the cell line. Cells used for counter selection are chosen in light of positive cells. In the literature, cell lines used for counter selection were:(i) isogenic to cells used for positive selection. Most of the cell-based SELEX process used cells overexpressing the target of interest for the positive selection, and the parental cell line for counter selection . As an e(ii) unrelated to cells used for positive selection. Two studies ,114 rela18F and further screened in vivo by PET imaging in a SKOV3 tumor model. Two aptamers, Heraptamer-1 and-2 which had relatively high tumor uptake ratios, are promising ligands for HER-2 imaging in cancer. A similar approach was used by Wilner et al. [(iv) inexistent or not documented . ssDNA ar et al. . Four roAptamers are valuable tools to isolate tumor-specific biomarkers ,123,124,The ssDNA aptamer AS1411 in clinical trials as a novel treatment for cancer is original compared to all other aptamers cited in this review, as its discovery does not result from a SELEX approach. It is referred as an aptamer as its activity arises from binding to a specific target via shape-specific recognition. Briefly, Bates et al. , in the Berezovski et al.  describeD) in the low nanomolar range. These aptamers internalized into glioblastoma TICs that self-renew, proliferate, and initiate tumors.By cell-based SELEX process, aptamers have also been selected for tumor cell types d, withouAptamer binding is dependent on the target conformation which is conditioned by its environment. Full-length purified recombinant proteins, ectodomains or peptidic fragments of proteins used in protein-based SELEX may not be relevant targets if they have to be used in clinical developments. In cell-based SELEX, cell-surface targets post-translationally processed are in their endogenous environment, as close as possible to their natural distributions and conformations. Cell-based SELEX does not necessitate the production and purification steps usually required for protein-based SELEX and therefore the method may be useful to target proteins difficult to be produced and/or purified. Moreover, aptamers can be selected without prior knowledge of cell-surface targets. In that case, the aptamer acts as a bait to identify its target, which can be a new tumor protein biomarker.But cell-based SELEX is a complex process, much more difficult than protein-based SELEX . Cells lPost-SELEX characterization of the target is often required to check if the predetermined target is the ‘real’ target of selected aptamers, or to identify the target if it has not been identified prior selection. Selected aptamers are used as bait, a posteriori, to purify and then to identify their targets. Briefly, biotinylated-aptamers are used to retain whole live cells on streptavidin beads. The cell lysate is then loaded on a SDS-PAGE gel. After electrophoresis and silver staining, proteins that have a higher intensity than controls (extracted proteins with empty beads and extracted proteins with a scrambled nucleic acid sequence) are extracted from the gel and analyzed by nano-LC-MS/MS mass spectroscopy ,154. AptOther methods, indirect compared to the method described above, have been used to identify a protein target post-cell-based SELEX. For example, Esposito et al.  used difBR), using the isogenic CHO-K1 cell line for counter selection rounds. None of the selected aptamers could discriminate between both cell lines. Nevertheless, the authors decided to study the 2’-fluoro RNA aptamer ACE4. The band excised from the PAGE-gel revealed that ACE4 did not interact with ETBR, but with Annexin-2, a calcium dependent phospholipid-binding protein which is up-regulated in various tumor types and plays multiple roles in regulating cellular functions . The high affinity aptamer, although not initially planned to bind to the post-SELEX identified tumor biomarker Annexin A2, could however be a promising tool for biomedical applications. In another example [Cell-based SELEX might lead to the selection of aptamers against other proteins than the pre-identified target. A cell-based SELEX was performed by Cibiel et al.  to ident example , a panelBesides their role for biomarker discovery above mentioned, aptamers have many applications in oncology. Some relevant applications of aptamers in the cancer field will be briefly described.Current approaches of protein biomarker detection include gel electrophoresis and conventional immunoassays (for capture and/or detection) such as enzyme-linked immunosorbent assay (ELISA), surface plasmon resonance, mass-sensing BioCD protein array, surface enhanced Raman spectroscopy (SERS), microfluidics and colorimetric, electrochemical and fluorescence assays . Most of these approaches still lack accuracy, sensitivity and specificity required for diagnostic application. Advantages and limitations of these methods have been compared for the prostate specific antigen (PSA) biomarker detection . DiffereApplications of aptamers as targeted therapeutics have been reviewed recently ,175,176.O-methyl RNA [O-methyl 31 nucleotide long RNA aptamer, protected from exonuclease degradation by a 3′ inverted deoxythymidine cap. It is branched with a 40 kDa PEG carrier. PEGylation is generally used to increase aptamers molecular weight, prolong their circulating half-life by limiting renal clearance, enhance their stability and decrease their toxic accumulation in tissues and the volume of distribution of therapeutic molecules [Eleven aptamers have entered clinical stages ,195 for thyl RNA ,197. Pegolecules ,199,200.olecules . A phaseolecules ,203,204.olecules . In 1983olecules , but indolecules ,208,209.165. As an inhibitor of VEGF165-associated vessel formation, pegaptanib sodium is an anti-angiogenic medicine for the treatment of wet age-related macular degeneration. Pegaptanib sodium has also potential therapeutic effects as an agent for solid cancers characterized by extensive angiogenesis [Pegaptanib sodium or Macugen  was the ogenesis .In oncology, two aptamers have undergone clinical trials. The first one was AS1411 (AGRO100), a DNA quadruplex targeting nucleolin. This multifunctional protein, located in the nucleolus but overexpressed at the membrane of several cancer cells, is implicated in cancer development by interacting with key oncogenes  and by transferring specific extracellular ligands into the cells. The interaction of AS1411 and nucleolin induces internalization, inhibition of DNA synthesis and induction of apoptosis ,213,214.NOX-A12 (olaptesed pegol) is in clinical development for the treatment of chronic lymphatic leukemia and multiple myeloma ,220,221.Due to their pleiotropic characteristics and improvements in the SELEX technology, aptamers, which can be selected to virtually any type of targets, are thought to gain rapidly an important place in clinical applications and may replace in many cases animal-derived antibodies. Aptamers as synthetic molecules are believed to save cost and time in R&D and manufacture. The targets of aptamers actually in clinical trials  are extr


Previous research has suggested that immunoglobulin E (IgE)-mediated events lead to several chronic diseases. We investigated the association between allergic conditions and age-related cataracts in the South Korean adult population.A cross-sectional study was performed using data obtained from 1,170 participants aged 40 years or older who were enrolled in the Korean National Health and Nutrition Examination Survey 2010. Multivariable logistic regression was used to examine the relationship between age-related cataracts and allergic conditions, including total serum IgE and allergen-specific serum IgE levels, after adjustment for potential confounders .P = 0.044). In particular, increased IgE levels were significantly associated with nuclear cataract . However, allergen-specific serum IgE levels did not differ significantly between groups. In the trend analysis, no significant relationship was observed between serum IgE and any type of age-related cataract.After adjusting for potential confounders, the odds ratio (OR) for age-related cataract was greater in participants with higher total serum IgE levels (OR = 1.37; Increased total serum IgE level is independently associated with age-related cataracts after adjustment for confounding factors. Cataract, defined as opacity of the crystalline lens, is the most common cause of visual loss worldwide . MoreoveImmunoglobulin E (IgE) is an antibody that binds to Fc  receptors, which are mostly found on the surface of mast cells . It playIt is well-known that anterior and posterior subcapsular cataracts are a common ocular complication of atopic dermatitis . HoweverIn the present study, we investigated whether increased serum IgE is associated with the prevalence of age-related cataract after adjustment for well-known risk factors . The study protocol was approved by the institutional review board of the Korean Center for Disease Control and Prevention (IRB Number: 2010-02CON-21-C). All participants signed forms consenting to the use of their health information in the study. The KNHANES 2010 was a nationwide, population-based, cross-sectional survey conducted by the Division of Chronic Disease Surveillance of the Korea Centers for Disease Control and Prevention [All analyses were based on the Korean National Health and Nutrition Examination 2010  to evaluate the participants’ cataract status . The staDermatophagoides farinae, cockroach, and dog allergen were also examined using anImmunoCAP100 kit  and a 1470 WIZARD gamma-Counter analyzer  [Demographic information on traditional cataract-related risk factors was obtained during the health interview. Specifically, each participant completed a questionnaire in which they provided information on age, smoking status, alcohol use, sun exposure, and medical history. Blood pressure was also measured by the health professionals. Sunlight exposure time was evaluated by a multiple-choice question with the following answer options: <2 hours, 2–5 hours, and >5 hours per day. Fasting blood samples of individual participants were collected to measure serum biomarkers . The blood samples were immediately refrigerated and transported to the Central Testing Institute in Seoul, South Korea. Levels of total serum IgE and antigen-specific IgE against Finland) . The uppFinland) .2 test  or the Wilcoxon rank-sum test (for continuous data). To assess the association between cataract and increased IgE levels and sensitization to specific antigens, we used multivariable logistic regression to estimate the respective odds ratio (OR). The estimated ORs were calculated in the following ways: crude OR, in which no adjustment was made for potential confounders; Model 1, wherein the data were adjusted for age, sex, body mass index [The characteristics of the participants in terms of cataract status were compared using the χss index , smokingss index , alcoholss index , and sunss index  . We considered P-values < 0.05 as statistically significant. All statistical analyses were completed using the SPSS Statistics 21.0 software .To avoid collinearity between the confounders , we selected systolic blood pressure and total cholesterol level as covariates. When calculating the correlation matrix of all covariates, there was no multi-collinearity problem .Ultimately, a total of 1,170 participants were included in this study. In P = 0.048) and Model 2 . In contrast, sensitization to specific antigens, including Dermatophagoides farinae, cockroach, and dog, was not significantly associated with age-related cataract either before or after adjustment. The possible effects of socioeconomic status on the association between IgE and age-related cataract were also examined. Additional adjustments for household income and education had no effect on the associations reported above, which showed an age-related cataract OR of 1.41 in Model 1 (P = 0.028) and 1.42 in Model 2 (P = 0.028) in subjects with an increased IgE level. Therefore, the effect of socioeconomic status on the association between IgE and age-related cataract was minimal.P = 0.001). Increased IgE remained a significant risk factor for nuclear cataract after adjustment for confounding factors in Model 1  and Model 2 . Sensitization to specific antigens was not a significant risk factor for any type of cataract.Multivariable logistic regression was performed in each cataract subtype group to examine the association of cataracts with both total and allergen-specific serum IgE levels. The OR results are listed in P for linear trend = 0.080). Subgroup analyses were also performed in each age group. As shown in To explore the more specific association between IgE levels and age-related cataracts, we carried out additional analyses involving the quartiles of IgE level. The ORs for each quartile of serum IgE concentration, adjusted for the variables in the fully adjusted model (Model 2), are shown in To our knowledge, this study was the first to evaluate the association between serum IgE levels and age-related cataracts in the general population. Our results demonstrated that study participants with increased total serum IgE levels had a significantly higher OR for age-related cataract after adjustment for confounding factors. In particular, increased IgE was significantly associated with nuclear cataract—the most common form of age-related cataract. However, neither of these findings was true of IgE sensitization to allergens in our regression models. The trend analysis of the ORs did not show a significant linear trend between the risk for age-related cataract and the serum total IgE quartiles. Since the analysis used data from a nationally representative sample of the population and was adjusted for a wide range of confounders, our results support the hypothesis that increased serum IgE levels are associated with age-related cataract.Recently, age-related cataract has been seen as a multifactorial disease that may be related not only to age and exposure to ultraviolet, but also to systemic conditions . PreviouThe possible association between IgE and cataract formation maybe mediated by the mast cell in several ways: the mast cell may aggravate the oxidative status of the lens proteins directly (by activating inflammatory cascades) or indirectly (by increasing vascular permeability). Furthermore, mast cells release several inflammatory mediators, such as cytokines, chemokines, histamine, proteoglycan, and mast cell protease, following IgE stimulation . These mIn the present study, the adjusted multivariable regression models revealed an independent relationship between increased IgE and nuclear cataracts. In our analyses, we adjusted for potential risk factors of age-related cataract; nonetheless, our results may have been influenced by various chronic illnesses associated with both cataract formation and increased IgE level. Recent studies have revealed that IgE-mediated events can lead to several chronic diseases, including not only allergic conditions associated with hypersensitivity, but also metabolic syndrome. In fact, increased serum IgE has been associated with diabetes, hypertension, atherosclerosis, and ischemic heart disease; all these conditions are also related to cataract formation . FurtherDermatophagoides farinae, cockroach, and dog, showed no significant association. The reason for this finding is unknown. Because sensitization to most of these allergens occurs in childhood, the progression of age-related cataracts in old-aged persons may not be closely associated with the process [Considering that increased IgE levels were associated with age-related cataracts, it was surprising that IgE sensitization to specific allergens, including  process . Accordi process . For exa process . Additio process . Overall process . TherefoThis study had certain limitations. Firstly, our analyses did not establish a causal relationship because of their cross-sectional nature. Moreover, our health data was based on a health interview survey taken on one occasion. Fasting plasma glucose, body mass index, blood pressure, and serum IgE may all differ depending on the time of measurement. Secondly, this was a single, Asia-specific study. Generally, the incidence and type of cataract are influenced by genetic background . TherefoIn conclusion, our findings demonstrated that increased total IgE levels significantly associated with age-related cataracts. Specifically, increased IgE was significantly related to nuclear cataracts. Due to the aforementioned limitations, further studies involving a larger sample size and other ethnicities are still needed. In addition, future studies should clarify more specifically the role of IgE in the development of age-related cataracts.S1 Table(DOCX)Click here for additional data file.


Many patients with gynecological disorders seek traditional medicine consultations in Asian countries. This study intended to investigate the utilization of traditional Chinese medicine (TCM) in patients with dysfunctional uterine bleeding (DUB) in Taiwan.We analyzed a cohort of one million individuals randomly selected from the National Health Insurance Research Database in Taiwan. We included 46,337 subjects with newly diagnosed DUB (ICD-9-CM codes 626.8) from January 1, 1997 to December 31, 2010. The patients were categorized into TCM seekers and non-TCM seekers according to their use of TCM.Among the subjects, 41,558 (89.69%) were TCM seekers and 4,779 (10.31%) were non-TCM seekers. Patients who were younger tended to be TCM seekers. Most of the patients had also taken Western medicine, especially tranexamic acid and non-steroidal anti-inflammatory drugs (NSAIDs). More than half of TCM seekers (55.41%) received combined treatment with both Chinese herbal remedies and acupuncture. The most commonly used TCM formula and single herb were Jia-Wei-Xiao-Yao-San (Bupleurum and Peony Formula) and Yi-Mu-Cao (Herba Leonuri), respectively. The core pattern of Chinese herbal medicine for DUB patients consisted of Jia-Wei-Xiao-Yao-San, Xiang-Fu (Rhizoma Cyperi), and Yi-Mu-Cao (Herba Leonuri).TCM use is popular among patients with DUB in Taiwan. Further pharmacological investigations and clinical trials are required to validate the efficacy and safety of these items. Dysfunctional uterine bleeding (DUB) is defined as excessive, prolonged, frequent, and unpattern bleeding from the uterine in the absence of any structural etiology . In ordeDUB significantly and negatively impacts the patient’s physical and social quality of life. It may put patients at risk for developing anemia, fatigue, and depression. Patients with heavy menstrual bleeding had higher hospitalization rates, emergency room visits, and outpatient visits . OtherwiCurrent treatments for DUB include combined oral contraceptives, progestogens, non-steroidal anti-inflammatory drugs (NSAIDs), tranexamic acid, gonadotropin-releasing hormone analogues, danazol, and levonorgestrel-releasing intra-uterine system (LNG IUS) . EndometTherefore, this study intends to investigate TCM usage and prescription patterns for patients with DUB. We aimed to investigate the core prescription of TCM for patients with DUB and provide valuable information for TCM doctors and gynecologists. The results of this study will be useful for further research in clinical trials and pharmacological investigations in the future.The National Health Insurance (NHI) program was launched in Taiwan in 1995. It has covered more than 99% of Taiwanese residents in 2015 . TCM sern = 41,558) and non-TCM seekers (n = 4779). This study was approved by the Research Ethics Committee of China Medical University and Hospital (CMUH104-REC2–115).A randomly selected sample with one million individuals who were enrolled in the NHI program was analyzed. Patients with newly diagnosed DUB (ICD-9-CM codes 626.8) from January 1, 1997 to December 31, 2010 were identified from the database  and The Plant List (http://www.theplantlist.org/) [http://nodexl.codeplex.com/) to determine the core pattern of Chinese herbal medicine prescribed for DUB patients. As described in our previous reports [Chinese herbal formulas were listed in pin-yin name and English name. Single herbs were listed in pin-yin name, Chinese materia medica name and plant name. The TCM indications of the Chinese herbal formulas and single herbs were based on TCM theory , 12. Fulst.org/) . We used reports , the thiWe analyzed the acupuncture and Chinese traumatology that patients received by the treatment codes in the datasets. Acupuncture includes traditional Chinese manual acupuncture, electroacupuncture, and moxibustion. Chinese traumatology indicates traditional Chinese medicine traumatology and orthopedics, which is a combination of massage, acupressure, and body manipulation.P-value of <0.05 was considered statistically significant. The urbanized residence levels of all individuals were classified into four grades based on a previous study. Level 1 represents the highest urbanized level and 4 represents the lowest level [All statistical analyses were performed using SAS software, version 9.4 . A univariate analysis was conducted to compare the TCM seekers with the non-TCM seekers. The data analysis included descriptive statistics, including the frequency of TCM prescriptions, the patients’ demographic characteristics, indications for the prescription of TCM, and the most frequently prescribed herbal formulas and herbs for the treatment of DUB. We used t-test and chi-square test to examine the differences of numerical variables and categorical variables between two cohorts, respectively. The frequency of co-morbidities, which were the medical conditions as the reasons that DUB patients visited the clinics, between the two cohorts was compared using chi-square test. A st level .n = 41,558) visited TCM doctors for clinical consultation or treatment. Patients within the range of 18–29 years old were most likely to receive TCM treatment  and Yi-Mu-Cao (Herba Leonuri), respectively Table . The corIn this study, we found that more than 90% of patients with DUB received TCM treatment. Patients with young age (18–29 y/o) or patients lived in highly urbanized areas were more likely to receive TCM treatment. Of the TCM seekers in our study, more than half of them received both herbal medicine and acupuncture/traumatology. Jia-Wei-Xiao-Yao-San (Bupleurum and Peony Formula) and Yi-Mu-Cao (Herba Leonuri) were the most commonly used TCM formula and single herb, respectively. This was the first population-based cohort study to investigate the TCM utilization patterns among patients with DUB. The analysis of TCM formulas in DUB treatment could provide useful information for further clinical trials and pharmacological investigations.Our result revealed that patients with young age or lived in highly urbanized areas preferred to receive TCM treatment, which was consistent with the previous studies , 17. TCMOf the top ten commonly prescribed formulas identified in our study, Jia-Wei-Xiao-Yao-San and Dang-Gui-Shao-Yao-San share common features to nourish blood, regulate menstrual cycle, and relieve emotional and psychological symptoms clinically. Previous studies found that Jia-Wei-Xiao-Yao-San ameliorated depression in menopausal women through increasing serum TNF-α , 19 and Of the ten commonly used single herbs identified in this study, Yan-Hu-Suo  and Xiang-Fu (Rhizoma Cyperi) are traditionally used to treat qi stagnation to relieve pain. Moreover, Yan-Hu-Suo has been used to promote blood circulation, alleviate amenorrhea and dysmenorrhea, and treat puerperal blood stasis . TetrahyThe core pattern of Chinese herbal medicine for DUB patients was the combination of Jia-Wei-Xiao-Yao-San, Xiang-Fu, and Yi-Mu-Cao, which was also the most commonly used combination for premenstrual syndrome . There iThere are some limitations in our study. The laboratory data and the imaging findings were not available in this database. The differences in disease severity between the TCM seekers and the non-TCM seekers cannot be evaluated. We could only identify the patients who received the conventional drug treatment and surgery in TCM seekers and non-TCM seekers. It has to be noted that DUB requires exclusion diagnostic procedure after clinical and laboratory examination. In the NHIRD datasets, we could identify the specific codes for the laboratory examinations, sonography, and pelvic examination in the datasets. Although we only included those who had at least 2 claims as the DUB patients and further excluded those who were diagnosed as having cervical cancer, endometrial cancer, or ovary cancer within one year of the initial diagnosis of DUB to avoid the selection bias; however, the results of these examinations were not revealed in the datasets. It is also likely that without proper exclusion diagnostic procedures such as clinical and laboratory examination, the number of DUB patients may be exaggerated.Moreover, herbs purchased at patients’ own expanse beyond the NHI programs were not included in this study since the NHI program only reimburses Chinese herbal medicines manufactured by good manufacturing practice (GMP) -certified pharmaceutical companies in Taiwan. However, because the cost of Chinese herbal products reimbursed by the NHI program is much less than the herbs in the market, the likelihood of purchasing herbs outside of the NHI program is relatively low. In addition, progestin intrauterine device was not reimbursed by the National Health Insurance program until 2015, so we could not identify the patients who used progestin intrauterine device in our study. The other limitation of this study is that the direct efficacy of TCM treatment cannot be evaluated. The compliance to prescriptions was not revealed in the database. These factors should be evaluated in the high-quality, randomized, controlled clinical trials in the future.This is the first large-scale population-based study on complementary TCM utilization in patients with DUB. We found that the utilization rate of complementary TCM among patients with DUB is high. The prescription patterns identified in this study could be useful for future clinical studies or pharmacological investigations. Future high-quality, randomized, controlled clinical trials combined with laboratory data may help to determine the efficacy of TCM for DUB patients.


The recurrence risk stratification and the cost effectiveness of oncological surveillance after radical cystectomy are not clear. We aimed to develop a risk stratification and a surveillance protocol with improved cost effectiveness after radical cystectomy.Of 581 enrolled patients, 175 experienced disease recurrences. The pathology-based protocol presented significant differences in recurrence-free survival between normal- and high-risk patients, but the medical expense was high, especially in normal-risk (≤pT2pN0) patients. Cox regression analysis identified six factors associated with recurrence-free survival. Risk score-based 5-year follow-up was significantly more cost effective than the pathology-based protocol.We retrospectively evaluated 581 patients with radical cystectomy for muscle-invasive bladder cancer at 4 hospitals. Patients with routine oncological follow-up were stratified into normal- and high-risk groups by a pathology-based protocol utilizing pT, pN, lymphovascular invasion, and histology. Cost effectiveness of the pathology-based protocol was evaluated and a risk-score-based protocol was developed to optimize cost effectiveness. Risk-scores were calculated by summing risk factors independently associated with recurrence-free survival. Patients were stratified by low-, intermediate-, and high-risk score. Estimated cost per one recurrence detection by the pathology and by risk-scores were compared.Risk-score-stratified surveillance protocol has potential to reduce over-evaluation after radical cystectomy without adverse effects on medical cost. Radical cystectomy (RC) with extended pelvic lymph node dissection is the standard treatment for non-metastatic muscle-invasive bladder cancer (MIBC) , 2. LongP = 0.291). The number of patients with tumor recurrence within 24 months in the high-risk group  and the normal-risk group  were not significantly different   were included in the pathology-based normal-risk group and 282 (48%) were included in the high-risk group. The clinicopathological characteristics are shown in Table ) Figure P < 0.001) or intermediate-risk (P < 0.001) scores  or intermediate-risk score  groups , the low-risk and high-risk  groups (P = 0.0011), and the intermediate-risk and high-risk, groups (P = 0.0256) , preoperative chronic kidney disease (CKD), and cardiovascular disease (CVD) Table . The riss Figure . The nums Figure . The nums Figure . The med) Figure . The ris) Figure . The num) Figure .P < 0.001)    Figure , left. S) Figure , right. ) Figure . In addi) Figure . TherefoP = 0.056)  and older (> 70). Our results suggested that there was no significant difference in the recurrence pattern between the younger (≤ 70) and older (> 70) patients. However, late recurrence (> 24 months) showed marginal difference between ≤ 70 years  and > 70 years   Figure .P = 0.867)  Figure . These rIn the present study, type of urinary diversion was selected one of independent predictors for disease recurrence. This result suggested possibilities that the strong selection bias for urinary diversion and/or opportunity difference for surveillance after surgery. There is a strong selection bias for orthotopic bladder substitution including younger age, good performance status, and lower-risk for local recurrence. Due to the retrospective analysis, we could not assess the influence of frequent care in patients with stoma might have impact of follow-up surveillance. Further prospective studies are necessary to address these important clinical questions.The use of neoadjuvant chemotherapy (NAC) for patients with renal impairment remains unclear –33. BaseAlthough use of this risk score-based protocol may reduce over evaluation, the cost was still substantial because of the low relapse rate in the low-risk group. This result highlights the limitation of predicting relapse risk exclusively on clinical information. For a better understanding of tumor biology, biomarkers that predict malignant potential are necessary. Genome-based molecular classification is a potential biomarker , 40. A bThis study was limited by its retrospective design. First, as we could not control all variables, it was subject to selection bias and the influence of confounding factors including all medical costs for oncological surveillance, CT cost for with or without a contrast medium, numbers of dissected and positive lymph nodes, smoking status, regimen of NAC and the influence of adjuvant/salvage therapy. In addition, we could not address the optimal timing and utility of urine cytology for routine screening in the present study because only five patients (2.9%) were detected by urine cytology. Furthermore, we could not control the influence of frequent care in patients with stoma that might have impact of follow-up surveillance. Second, we focused two points; risk stratification and cost effectiveness of postoperative follow-up. In this point of view, it might be hard to discuss these two issues at the same time. However, when we simply evaluated the medical cost based on guideline recommended pathological risk factors, we found that pathology-based protocol did not improve the cost-effectiveness. In addition, it is not optimal for a clinical practice to use all previously reported risk factors. Therefore, we selected risk factors that significantly associated with tumor progression in our patients, and then developed the optimal risk stratification and surveillance protocol. Third, we could not clearly explain why CVD and CKD were selected as significant factors for recurrence in MIBC patients who underwent RC. Because there are not enough evidences to support the clinical implication of CVD and CKD for tumor progression, further basic and clinical research are necessary. Forth, the risk score-based surveillance model might increase the number of patients not detected by screening. Finally, the implication of this study may not suitable for other population such as non-Asian people because the entire Japanese population is covered by universal health insurance (maximum copayment of 10% to 30%). However, it is not easy to make the one-fit-all surveillance protocol due to medical system differences among the nations. Therefore, our study provides the idea that risk stratification in each nation is necessary to improve the cost-effectiveness in each medical system.Despite these limitations, this study adds to our knowledge of the cost effectiveness of oncological surveillance after RC. Although the importance of risk-stratified surveillance protocol has been reported, no study previously reported cost-effectiveness calculation using risk-score based protocol. We believe our study provides the idea for risk stratification to improve the cost-effectiveness. A prospective study on the cost effectiveness of follow-up using a universal, standard, and easily applicable surveillance model is required to validate these results.In conclusion, a risk-score-stratified surveillance protocol has the potential to reduce over investigation during follow-up making surveillance more cost effective. Further study is needed to determine the impact of risk-stratification on the cost effectiveness of oncological follow-up after RC.This retrospective study was performed following the ethical standards of the Declaration of Helsinki, and was approved by the Ethics Committee of the Hirosaki University School of Medicine (authorization numbers 2015–258 and 2016–225).Between May 1996 and December 2016, a consecutive series of 581 adults underwent RC and urinary diversion at Hirosaki university hospital, Aomori Rosai Hospital, Mutsu General Hospital, and Aomori Prefectural Central Hospital.2. Tumor stage and grade were defined by the 2009 TNM classification of the Union of International Cancer Control  / [number of patients with recurrence]) using an exchange rate of 100 yen to the U.S. dollar. Estimated medical costs were $350 for a CT, $70 for blood testing, $53 for ultrasonography, and $25 for urine cytology. The cost of prescriptions, medications, and doctor fees were not included in the analysis. To compare cost effectiveness, we developed a novel risk score-based protocol using a multivariate Cox proportional hazard regression model. Patient risk-scores were calculated by summing the number of independent risks suggested in the multivariate analysis, and the patients were stratified into low (0-1), intermediate (2–3), and high 4–6)  with 95% confidence intervals (CIs) were calculated after controlling simultaneously for potential confounders, including patient demographic and clinicopathological variables. Model variables included age, sex, ECOG PS, history of HTN, DM, CVD, preoperative CKD, NAC, urinary diversion, ≥ pT3 or SM+, pN+, LVI+, and nonurothelial carcinoma components.Statistical analysis was performed using SPSS version. 24.0  and GraphPad Prism 5.03 . Categorical variables were compared using Fisher’s exact test or the chi-square test. Differences between groups were compared using This study was performed in accordance with the ethical standards of the Declaration of Helsinki and approved by an ethics review board of Hirosaki University School of Medicine .


We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea). As autonomous driving technology becomes important for upcoming car industries, fundamental driving assistant skills are being included in commercial cars and the size of the market is increasing. To create true self-driving technology and evolve from Advanced Driving Assistant System (ADAS) to Auto traveling, understanding the environment is important.Currently alongside ADAS technology, another core technology for autonomous driving is Traffic Sign Recognition (TSR), a system which detects and recognizes traffic signs captured by a front mounted camera. With TSR, self-driving cars can thoroughly understand road regulations for safety. The European New Car Assessment Programme (EURO NCAP) regard TSR as top issue in safety skills for car safety . In GermWhile ADAS requires an extra sensor such as radar or ultra-sonic equipment, TSR only requires a camera and machine learning technology. In order to execute TSR in real-time and with high performance, cutting edge hardware mounted in the car system is usually required. However, the recent announcement of NVIDIA’s General Purpose Graphics Processing Unit (GPGPU), DRIVE PX , a GPU fObject detection in driving scenes faces unique technical challenges. One major problem is wide variation in illumination due to weather and time of day. Another problem is low image quality at high speeds. To reduce the impact of these problems, various image pre-processing methods have been introduced; however, they come up short as they are not real-time procedures.TSR technologies also use various methods to process the image. TSR is commonly a two step process: it first extracts the candidate region of the traffic sign and then classifies the detected region. For traffic sign detection, most methods are based either on the sign’s color or shape information –11 or onColor-based traffic sign detection uses the characteristics of traffic signs, which have limited and solid colors. These methods first segment specific colors to create a color map , 6, 7, 8Major learning-based traffic sign detection methods use Haar-like features and AdaBoost-based detection , 14 and D. Ciresan et al. presented a traffic sign recognition method using a Convolutional Neural Network (CNN) . BecauseIn this paper, we present the Byte-MCT and a landmark-based AdaBoost classifier for traffic sign detection. The presented method takes a driving scene as its input image and detects a candidate region using one classifier. After verifying the candidate region using a Support Vector Machine (SVM), the method recognizes the traffic sign using a CNN. This method uses Byte-MCT, a modified version of Modified Census Transform (MCT), which is robust against illumination variation. This method also utilizes a landmark feature, which allows the characteristics of the traffic sign to overcome partial occlusion of the input image. Additionally, during traffic sign detection, the method uses parallel processing (which can be implemented on a GPGPU) and reduces the detection time as compared to the sliding-window searching method. During the recognition stage, we use a cascade classifier that assembles the SVM to verify the candidate region and a CNN for diverse traffic sign recognition.In the following section, we provide an overview of the presented method. Section 3 describes traffic sign detection that is robust to illumination. Section 4 describes the verification stage using SVM and recognition of traffic signs using CNN. Section 5 presents our experiment results for the testing set. Conclusions are given in section 6.Recently in the field of traffic sign detection and recognition, diverse methods have been introduced. However, several problems still remain to be solved.The models still lack invariance to illumination; conventional models are optimized primarily for daylight scenesTechnical difficulties remain in real-time processingDetection of diverse traffic sign requires multiple detectorsIn this paper, we propose a GPGPU-based real-time traffic sign detection and recognition method to address each of these issues. The overall flow of the method is presented in circle, triangle, and other. In the final recognition stage, we use CNN to classify the diverse traffic signs to further improve the result.After the candidate region is extracted from the input image, we split each candidate window into four partial window regions and generate feature vectors which are concatenation of Byte-MCT histograms. Consequently, the feature vectors are fed into SVM verification procedure. Therefore, feature vectors can distinguish traffic signs in similar shapes. The SVM classifies the detected windows into three classes, i.e., In this chapter, we introduce a method for detecting traffic signs with illumination-invariant Byte-MCT feature in real-time. Illumination-invariance is an important element for traffic sign detection due to two senses: 1) detecting objects in images captured in a moving vehicle involve change of illumination which makes detection even more challenging, 2) weather and timeline shifts causes change of illumination.x is a pixel in the image and I(x) represents pixel x intensity, L(x) and R(x) represent the luminance of a light source and surface reflectance, respectively, g and b are camera parameters. The intensity of pixels are decided by combination of luminance and reflectance. If luminance becomes constant or limited in certain circumstances, then Eq . The CT uses either 3-by-3 or 5-by-5 fixed-size windows to construct index of edge structure based on relative intensity comparison between middle index pixels and neighbor pixels. The most conventional CT methods are Modified Census Transform (MCT) and Local Binary Pattern (LBP).In a digital image, each pixel can be described using Eq :I(x)=gLx)R(x)+b,where x  then Eq , indicatx,N(x) is the eight neighboring pixels of x, Iavg(x) is average intensity of N(x), and y∈N is a concatenation of neighboring pixels’ transformation result. As a result, MCT can describe up to 511 (= 29−1) local edge structures in a 3-by-3 window. Since MCT compares each pixel to the average intensity of local region, global illumination has no impact and only reflectance is considered thus it becomes robust against luminance change.B. Froba and A. Ernst  presenteIn this paper, we further modify MCT method to present Byte-MCT (8-bit MCT). Byte-MCT excludes the central pixel from concatenation, resulting in only eight neighbor pixels. In this section, we describe a method of identifying traffic sign landmark points using Byte-MCT. Y. Freund and R. Schapire  introducD1(i) is the initial weight of the first pixel classifier; i indicates the sign or non-sign and D is the boosting weight. After assigning the initial boost weight to construct the strong classifier, we train the assigned number of pixel classifiers. During pixel classifier training, each trained class generates a Byte-MCT-based look-up table and calculates the pixel classifier weight α based on error ε. In each learning iteration, the weak (pixel) classifiers are trained and assembled into a strong classifier. The learning iteration ends when the overall sum of weak classifier error is less than θt and θα is bigger than α, because α represents the importance of the weak classifier.T landmark pixel classifiers are weak classifiers which considers the most distinguishable pixel and are combined into the strong classifier. Unlike conventional ensemble classifiers, which use multiple stages (for time efficiency) instead of full training, the proposed method has only one strong classifier with a small number of landmark points. Because of the algorithm’s structure, the proposed method calculates far fewer operations than the original AdaBoost. Another benefit of the landmark-based architecture is that it can run on a GPU with parallel-window searching. The GPU’s parallel system divides one task into multiple small independent tasks that can be processed by thousands of GPU core blocks. Therefore, for non-sequential tasks such as sliding-window, this method can take advantage of the parallel system. Details will be presented in next section.B. Froba et al.’s method trains the pixel classifiers in four stages. At each stage, the classifier is trained until the error is less than the threshold value. The drawback of this method is that it trains all of the pixel classifiers until it reaches the end condition, meaning that the learning time sharply increases as the input resolution increases. To overcome this disadvantage, the modified AdaBoost method trains weak classifiers only on the landmark pixels. The values of landmarks are decided by α-score from The two major approaches for object detection are sliding-window and object-proposal. Object-proposal is based on edge shapes. Usually, object proposals extract up to 1,000 candidate regions per image, regardless of the shape of the object. Because traffic signs have distinct shapes, object-proposal is not a suitable method. For this reason, TSR methods commonly use holistic searching in sliding-window fashion.Traditional sliding-window searching scans the entire image from a fixed window using raster scanning; thus, running time increases as the input resolution increases. To handle this challenge, the conventional methods construct a cascaded ensemble classifier using AdaBoost. The cascade method increases the running time efficiency by skipping non-object areas. However, this method requires sequential processing and cannot be run on a GPU. Therefore, object detection on a Full-HD image in real time is difficult.Advances in modern hardware has transformed CPUs from a single-core sequential processors into multi-core multi-thread parallel processors. This parallel processing paradigm can also be applied to GPGPUs, which have more than thousands of cores in a single unit. In this paper, we propose a Byte-MCT and landmark-based AdaBoost classifier using a parallel window-searching method on a GPGPU as shown in Unlike the sliding-window method, which scans an image in a sequential manner, parallel window-searching divides the input image into several blocks and simultaneously performs classification on one block using each GPU core. Although the GPU parallel system shares the concept of the CPU parallel system, GPU-based parallel window-searching has challenges with arbitrary positions in memory. We use a kernel function to address this challenge.In the previous section, the method for extracting the candidate region of the sign was described. In this section, we discuss SVM-based verification and CNN-based recognition. The recent emerging of deep learning network become one of main backbone of self-driving industries , 22. Howr is the number of candidate regions and max(Hr) is the maximum histogram value from the divided region. This equation normalizes each divided region using its own maximum value to generate the 256-dimensional histogram. By concatenating the 256-dimensional histograms, the method generates a 1024-dimensional feature vector. Because this feature extraction process uses Byte-MCT input, the extracted feature is also robust against illumination. Finally, the SVM calculates the extracted feature vector using the Radial Basis Function (RBF) kernel to classify the input classes: circle, triangle, and other.To verify candidate regions extracted by AdaBoost, we adapt the Byte-MCT as feature vectors for SVM. The SVM determines the decision boundary that has a maximum margin from the support vector, which is an outlier of the feature vector. It verifies the candidate regions with better generalization ability than CNN. The circle class indicates a prohibition sign, which has a red rim. The triangle class is a warning sign. The negative class is any place in which images from the input are not traffic signs. This class also includes background images that have similar shapes as traffic signs. In the real world, same traffic sign shapes have different meanings based on information inside the signs such as 40 mile speed limit and 60 mile speed limit have same shape but different restriction. Additionally, the background image can also contain shapes similar to traffic signs yet have no meaning in terms of traffic rules. This situation requires additional recognition steps for fine grained recognition to reduce the false positive inputs.other.From an SVM-verified image, such as a circle or a triangle, we use CNN to recognize signs. In the German Traffic Sign Recognition Benchmark (GTSRB) , the CNNThe presented CNN model takes a 40-by-40 input image and generates 250-dimensional feature vectors from two pairs of convolution and pooling layer. This feature vector passes the fully connected neural network with the final softmax layer that classifies the 24 traffic sign types. Unlike D. Ciresan’s model , the proTo evaluate our proposed method, we use two different datasets: the LISA US traffic sign dataset  and a reTo evaluate the presented model, we compare its performance to that of the Aggregated Channel Feature (ACF) method , which iTo evaluate the effectiveness of proposed detection method, we conduct the experiments with two factors: MCT features, and AdaBoost. Since the focus of these experiments is comparing detection performance between features, cascade of architectures is excluded so that maximum performance is bounded by non-cascaded models. From 9-bit MCT and full-pixel AdaBoost, shows superior precision compared to Byte-MCT with full pixel based AdaBoost regardless of datasets. However, the performance of features are decided by recall, since detection performance is thoroughly influenced by choosing true positive. Unlike precision, recalls are always higher in 8-bit MCT features regardless of datasets. DE-D contains partial occlusion of traffic signs in datasets, and results show that the Byte-MCT are more robust against the noise and partial occlusion. The landmark-based AdaBoost performance for 9-bit MCT and Byte MCT result shows a different trend: both precision and recall are higher in Byte MCT feature. The margin between 9-bit MCT and Byte-MCT are even larger for noisy input especially under the low illumination inputs, i.e., KR-N.The classifier performance between full-pixel AdaBoost and landmark-based AdaBoost, landmark-based AdaBoost always produces better performance with shorter training time. Although full-pixel based AdaBoost shows stable performance in KR-D datasets, it was largely affected by lower illumination, KR-N. Applying the landmark feature significantly enhanced performance for the partially occluded dataset, DE-D. This data depicts the situation of possible over-fitting of pixel classifiers for full-pixel AdaBoost.The proposed traffic sign detection and recognition method is specifically designed for parallel-window searching on a GPGPU, unlike traditional sliding-window searching. Normally, most computational processing units are CPUs, but the GPGPU allows a parallel system that is optimized for graphics and display processing, which uses thousands of processing units and pipelines. To evaluate the running time of the proposed method, we compare CPU-based operations and GPU-based operations. The input image resolution is Full-HD (1920 × 1080), which is resized to generate image pyramid of six-step down-sizing for CPU/GPGPU processing. The hardware specifications are an Intel i7-6700 3.2-GHZ CPU and an NVIDIA GeForce TITAN X GPU.For detection stage, we use detection windows of four different sizes and experiment with both single and multiple windows on each image pyramid. In recognition stage, the running time is proportional to the number of verified regions from SVM, which varies across different input images. Due to this limitation, we can only compare the results based on average time consumption. The SVM and CNN run on the CPU and GPU respectively. The overall recognition takes 5ms on average, while SVM verification takes 2ms, and CNN classification takes 3ms.In this paper, we presented a GPGPU-based real-time traffic sign detection and recognition method for high resolution image inputs. This method introduces the Byte-MCT for stable candidate region detection regardless of illumination changes. For real-time high-resolution image processing, we used the target object’s landmark-point-based AdaBoost for traffic sign detection, and applied a parallel-window searching algorithm for the GPGPU. For high-performance recognition, we used a hierarchical classifier structure that combines SVM for verification and CNN for final recognition. Our proposed method makes the following three primary contributions:Illumination-robust Byte-MCT and landmark-based traffic sign region detectionParallel-window searching for traffic sign detection based on GPGPUHierarchical classifier structure using SVM and CNNThe presented method proposes possible solutions to two traditional challenges in traffic sign recognition.Using its robustness against illumination features, the proposed method significantly improved the performance of detection and recognition under low illumination environments, i.e., nighttime.The method was able to perform real-time processing using a GPGPU on full-HD resolution input.The accuracy of proposed method is 89.5%, which is higher than the ACF result , 84.3%,


Background: Non-alcoholic fatty liver disease (NAFLD) is a common metabolic disorder all over the world, mainly being associated with a sedentary lifestyle, adiposity, and nutrient imbalance. The increasing prevalence of NAFLD accommodates similar developments for type 2 diabetes and diabetes-related comorbidities and complications. Therefore, early detection of NAFLD is an utmost necessity. Potentially helpful tools for the prediction of NAFLD are liver fat indices. The fatty liver index (FLI) and the NAFLD-liver fat score (NAFLD-LFS) have been recently introduced for this aim. However, both indices have been shown to correlate with liver fat status, but there is neither sufficient data on the longitudinal representation of liver fat change, nor proof of a diet-independent correlation between actual liver fat change and change of index values. While few data sets on low-fat diets have been published recently, low-carb diets have not been yet assessed in this context. Aim: We aim to provide such data from a highly effective short-term intervention to reduce liver fat, comparing a low-fat and a low-carb diet in subjects with prediabetes. Methods: Anthropometric measurements, magnetic resonance (MR)-based intrahepatic lipid (IHL) content, and several serum markers for liver damage have been collected in 140 subjects, completing the diet phase in this trial. Area-under-the-responder-operator-curves (AUROC) calculations as well as cross-sectional and longitudinal Spearman correlations were used. Results: Both FLI and NAFLD-LFS predict liver fat with moderate accuracy at baseline (AUROC 0.775–0.786). These results are supported by correlation analyses. Changes in liver fat, achieved by the dietary intervention, correlate moderately with changes in FLI and NAFLD-LFS in the low-fat diet, but not in the low-carb diet. A correlation analysis between change of actual IHL content and change of single elements of the liver fat indices revealed diet-specific moderate to strong correlations between ΔIHL and changes of measures of obesity, ΔTG, and ΔALT  and between ΔIHL and ΔGGT . With exception for a stronger decrease of triglycerides (TG) levels in the low-carb diet, there is no statistically significant difference in the effect of the diets on anthropometric or serum-based score parameters. Conclusion: While liver fat indices have proved useful in the early detection of NAFLD and may serve as a cost-saving substitute for expensive MR measurements in the cross-sectional evaluation of liver status, their capability to represent interventional changes of liver fat content appears to be diet-specific and lacks accuracy. Liver fat reduction by low-fat diets can be monitored with moderate precision, while low-carb diets require different measuring techniques to demonstrate the same dietary effect. Non-alcoholic fatty liver disease (NAFLD) is a common metabolic disorder all over the world, mainly being associated with a sedentary lifestyle, adiposity, and nutrient imbalance. The increasing prevalence of NAFLD accommodates similar developments for type 2 diabetes and diabetes-related comorbidities and complications.Uncomplicated NAFLD, i.e., hepatosteatosis, itself may progress to the inflammatory state of non-alcoholic steatohepatitis (NASH). Another complication, irreversible hepatic fibrosis, can lead to functional impairments of liver functions, representing hepatic cirrhosis, and finally culminate in primary malignoma of liver tissue.Therefore, early detection of NAFLD is an utmost necessity. Most imaging techniques provide only fair information on steatosis status and degree. Ultrasound sonography requires experienced examining personnel and sufficient imaging quality to provide qualitative, non-quantitative estimates. Sonoelastography and similar techniques assess liver tissue density, but not necessarily liver fat content. Computed tomography is inferior to magnetic resonance (MR)-based techniques in the assessment of soft tissues and exposes the patient to a huge amount of ionizing radiation. MR tomography also does not provide sufficient sensitivity and specificity for NAFLD detection and graduation.As one gold standard, MR spectroscopy has been established, but due to high costs and several medical contraindications its use for NAFLD assessment is limited to clinical studies. Liver biopsies, on the other hand, provide a highly specific measurement of intrahepatic lipid (IHL) amount, but heterogeneously distributed liver fat can easily be misinterpreted. In addition to that, tissue samples can only be taken with a significant risk of liver injury, bleeding, bile leakage, and subsequent complications.Thus, there is need for screening tools to assess and monitor NAFLD with minimal effort, low costs, and no restrictions with relation to cohort structure or individual medical history. Several NAFLD scores have been developed in order to fill this diagnostic gap. The fatty liver index (FLI) comprises markers of obesity (body mass index (BMI) and waist circumference), dyslipidemia (triglycerides (TG)), and liver injury alanine-aminotransferase (GGT). It highly correlates with objective measures of fatty liver disease and predicts most cases of NAFLD . SurprisMoreover, data on longitudinal NAFLD monitoring is sparse, as only a few studies have investigated whether changes in NAFLD scores mirror changes in actual liver fat content. Investigations on lipid fractions as correlates of therapeutic liver fat reduction were severely underpowered . One pubWe therefore investigate the statistical relation between changes in two liver fat scores in a human lifestyle intervention trial that features different dietary approaches for metabolic improvement. The ongoing study compares low-fat and low-carb diets in subjects with prediabetes and assesses, amongst other parameters, liver fat content by MR spectroscopy and liver fat scores on the basis of anthropometric measurements and fasted blood samples.Data for this publication are extracted from the ongoing lifestyle intervention trial “Diabetes Nutrition Algorithms in Prediabetes (DiNA-P)” registered at clinicaltrials.gov: NCT 02609243. DiNA-P compares a one-year low-carb or low-fat dietary intervention in subjects with impaired fasting glucose and/or impaired glucose tolerance. The study was conducted in accordance with the Declaration of Helsinki. The ethics committee of the University of Potsdam approved the study protocol in June 2013 . All subjects provided written informed consent for their participation in the study. Recruitment for this study started in June 2013 and aims for completion in summer 2018. For this present publication, subjects with randomization until November 2015 were selected to ensure completion of the first diet phase and analysis of all required serum parameters.At baseline, the participants of the DiNA-P study undergo fasting blood sampling, an oral glucose tolerance test, full anthropometry  and a medical examination. Study volunteers, if suitable and consenting for MR imaging, are subjected to liver MR spectroscopy and abdominal MR imaging according to pre-published specifications . Data frAfter screening, inclusion, and baseline assessment with MR, dietary protocols, and pedometry, subjects are 1:1-randomised to two dietary regimes: low-carb or low-fat. Dietary intervention is conducted for 12 months, split up into a first intensive initiation phase of 3 weeks and a 49-week maintenance phase. All assessments from the screening visit are repeated after the first phase and 6 and 12 months after screening.This publication only reports data from the first diet phase. In this diet phase, both groups are requested to limit their daily energy intake to 1200–1500 kcal. The low-carb diet aims not to exceed a daily intake of 40 g of carbohydrates. The low-fat requires restriction of fat intake below 30% of total energy intake. Despite the long-term goal of increased physical activity, subjects were instructed not to change physical activity before the second diet phase.FLI and NAFLD-LFS were calculated according to their first publication ,4.Statistical analysis entails calculation of area-under-the-responder-operator-curves (AUROC) for the prediction of NAFLD by FLI and NAFLD-LFS at baseline, split for both diet groups. Also, Spearman correlations were used to evaluate the cross-sectional prediction of NAFLD at baseline and the longitudinal monitoring of NAFLD during the first diet phase. Additional correlation analyses were performed to elucidate potential reasons or mechanisms for diet-dependent results.One hundred and forty (140) subjects of the ongoing study were selected for the presented data set. Baseline characteristics for both diet groups are presented in NAFLD prediction by FLI and NAFLD-LFS is comparable to their first publication ,4, resulAccordingly, correlation between liver fat scores and IHL content was strong and highly significant within both diet groups at baseline .r = 0.499, p < 0.001) in the low-fat group. Similarly, a moderate, significantly positive correlation was present between change of NAFLD-LFS and change of IHL  in the low-fat group. In the low-carb group, no such significant correlations could be found  and IHL did not correlate significantly .In both diets, actual IHL and almost all of the parameters which were used to calculate FLI and NAFLD-LFS decreased during the diet with statistical significance, but without statistically significant difference between the diets. TG, as the only exception, significantly decreased in both diets, but was significantly stronger in the low-carb diet (data not shown).Liver fat scores are widely used in metabolic research and clinical practice. Due to low costs, they allow an easy, quick, and relatively accurate prediction of fatty liver disease in patients with a significant risk profile. They do not require imaging procedures and are therefore suitable for patients with claustrophoby, metal implants, or severe obesity. Nevertheless, their measures of sensitivity and specificity leave about 15–20% of all tested subjects with a falsely predicted or falsely excluded diagnosis. Our publication supports the use of these indices for cross-sectional NAFLD prediction before treatment with similar measures of precision.On the other hand, those indices are also often used to monitor patients during interventions aiming at liver fat reduction despite missing data on the validity of this approach. Our data set implies that liver fat reduction by a low-fat diet is reflected with moderate precision by both scores, while the same metabolic effect on IHL, induced by a low-carb diet, cannot be extrapolated by either FLI or NAFLD-LFS. Similar findings for low-fat diets have been published recently in smaller studies ,17.A supplementary correlation analysis indicates that both diets differentially affect single elements of the liver fat scores. A low-fat diet decreases IHL, but also highly correlates to body weight, waist circumference, fasting insulin, triglycerides, and GGT. A low-carb diet leads to IHL reduction, which only correlates with dropping fasting insulin and alanine aminotransferase (ALT) levels.Several conclusions and hypotheses can be drawn from these findings.First, under low-carb conditions, IHL reduction appears to be independent from weight loss, rendering BMI or change of BMI a useless parameter for the monitoring of NAFLD and also within certain prediction scores. On the other hand, a strong correlation between weight loss and decreasing liver fat deposits was found for the low-fat group, supporting anthropometric measures as easy surrogate parameters for NAFLD improvement in this particular diet regime.Second, metabolic improvements of a low-fat diet, particularly a decreasing fasting insulin, seem to be more tightly linked to change in liver fat compared to the amelioration in the low-carb group. Both diets appear to affect liver metabolism and insulin sensitivity via different mechanisms inside and outside of the liver.Third, reduction of serum TG levels is pronounced in the low-carb group, but does not correlate with IHL improvement. Once again, dietary mechanisms seem to differ between the two regimes, thus modulating the hepatometabolic pattern.Fourth, change of ALT and IHL reduction correlate under low-carb, but not low-fat conditions. On the other hand, IHL and GGT are linked during a low-fat diet, but not during a low-carb diet. Despite similar baseline values and a similar decrease of both enzyme activities within both diets, the differential correlation with IHL might reflect different subtypes of liver injury that are specifically affected by a certain type of diet.Some limitations have to be addressed for our analysis. The current data set does not cover all patients from the DiNA-P study, as this trial is still ongoing. Nevertheless, with this paper we provide an analysis that provides a similar statistical power to other papers on this issue.Also, we are unable to fully clarify the reasons for missing comparability of longitudinal correlations between liver fat scores and MR-based liver fat values between different diets. As a first hint, we demonstrate that both diets differentially affect all components being used to calculate these indices. This highlights that liver fat reduction can be achieved in accompaniment with highly variable metabolic improvements depending on the type of diet. This diet-specific interaction also entails linkage of IHL reduction and total weight loss in low-fat diets, but not low-carb diets.Conclusively, with this paper, we replicate the good predictive properties of both FLI and NAFLD-LFS before a dietary intervention in subjects with prediabetes by both AUROC analysis and Spearman correlation. We also demonstrate that actual liver fat reduction is accompanied by moderately correlating liver fat scores in a low-fat, but not a low-carb, diet. This diet-specific finding on correlation magnitude can also be seen for each single component of those liver fat scores.Liver fat indices need to be used with caution, especially when assessing changes in different interventional settings. Furthermore, more research is needed to elucidate the diet-specific effects of low-carb and low-fat diets on a variety of hepatometabolic disturbances.


Spinal cord stimulation (SCS) has become a valuable brain-intervention technique used to rehabilitate patients with disorders of consciousness (DOC). To explore how the SCS affects the cerebral cortex and what possible electrophysiological mechanism of SCS effects on the cortex, the present study investigated the functional connectivity and network properties during SCS in minimally conscious state (MCS) patients. MCS patients received both SCS and sham sessions. Functional connectivity of the phase lock value (PLV) in the gamma band (30–45 Hz) was investigated at the pre-, on- and post-SCS stages. In addition, to evaluate global network properties, complex network parameters, including average path length, cluster coefficient and small-world, were measured. When SCS was turned on, significantly decreased connectivity was noted in the local scale of the frontal-frontal region and in the large scales of the frontal-parietal and frontal-occipital regions. The global network showed fewer small-world properties, average path lengths increased and cluster coefficients decreased. When SCS was turned off, the large-scale connectivity and global network returned to its pre-SCS level, but the local scale of frontal-frontal connectivity remained significantly lower than its pre-SCS level. Sham sessions produced no significant changes in either functional connectivity or network. The findings directly showed that SCS could effectively intervene cortical gamma activity, and the intervention included immediate global effects  and long-lasting local effects . Moreover, considering the mechanism and propagation of gamma activity, it indicates that the frontal cortex plays a crucial role in the SCS effects on the cerebral cortex. Despite considerable research, there is currently no effective standardized treatment for patients with disorders of consciousness (DOC). However, in recent years, spinal cord stimulation (SCS) has become a valuable brain-intervention technique for rehabilitating DOC patients because it is a less-invasive, simpler surgical procedure than deep-brain stimulation  that delivered electric pulses with a 3-V amplitude and a 210-μs pulse width. The pulse generator was implanted under the anterior chest wall. And the pulse generator was connected to stimulation electrodes through Touhy needle. The needle was implanted into the midline epidural space at the cervical-thoracic junction. And the stimulation electrodes were inserted into the epidural space of the cervical vertebrae, and placed at the C2–C4 levels. The stimulation was caused by periodic occurrence of voltage difference between two electrodes. The stimulation parameters could be setup by a wireless controller Resting state EEG was recorded for 10 min before stimulation, for 20 min during the real or sham stimulation and for 10 min immediately after the stimulation. EEGs were recorded using 32 channels  and Ag/AgCl pin electrodes having a sampling rate of 1 kHz. The skin/electrode impedance was maintained below 5 kΩ. During the experiments, participants were behaviorally awake , and if they showed signs of sleepiness , either the JFK CRS-R arousal-facilitation protocol was applied or the experiment was suspended.EEG pre-processing was conducted using EEGLAB software version 12.0.2.5b, running on a MATLAB environment . The 50-Hz power signal was removed by a notch filter. The EEG signal was band filtered between 1 and 45 Hz. The Independent Component Analysis (ICA) was used to identify and remove artifact-relevant components, including eye movements and muscle activation. The EEG data were divided into epochs of 10 s with overlaps of 50%. The selected artifact-free epochs were average referenced.x(t) and φy(t) of the pairwise channel were evaluated based on the Hilbert transform. Then, the phase difference was defined byC with each element of PLVxy.Connectivity between pairwise channels in the gamma band (30–45 Hz) was computed using phase synchronization, which is briefly described as follows. For each epoch EEG signal, the instantaneous phases φC with each element of PLVxy.Graph theoretical analysis was performed on the phase synchronization matrices. The nodes in the graph were defined as the electrodes and the links as the measure of the phase synchronization between the nodes. Weighted graphs were created using synchronization matrix Cw) and the path length (Lw) to analyse weighted networks. To calculate the clustering index from weighted networks, the weights between the node i and the other nodes j should be symmetrical (ωij = ωji), and 0 ≤ ωij ≤ 1, as proposed by Onnela et al. , central , parietal  and occipital . Figure t-tests: On-SCS vs. Pre-SCS, Post-SCS vs. On-SCS and Post-SCS vs. Pre-SCS , frontal-parietal (p < 0.001) and frontal-occipital (p = 0.011). When SCS was turned off, all the connectivity rebounded but only with significance in the frontal-parietal (p < 0.001). But when post-SCS compared with pre-SCS, significance was only found within frontal-frontal connectivity (p < 0.001). As Table SCS induced connectivity changes were found in frontal-frontal, frontal-parietal, and frontal-occipital Figure . To inveS Figure . Bonferrt-tests, and correction of the false discovery rate was performed after multiple comparisons . Top panel of Figure Then, pairwise comparisons of each connectivity were performed using paired t-tests with Bonferroni corrections. Figure p = 0.004) and decreases of cluster coefficient (p = 0.040) were found during SCS stimulation period. The global network showed less small-world property. And the network perturbation company with the stimulation. When SCS was turned off, the network parameters rebound to the baseline level. In sham sessions, the various stages produced no significant alterations of the network parameters.In order to explore the effects of SCS on the global cerebral cortex, graph theoretical based network parameters were calculated using the connectivity matrix in the gamma band at three stages: path length, cluster coefficient and small-world. Comparisons between pairwise stages were performed using paired SCS has been demonstrated as a valuable brain-intervention technique for rehabilitating DOC patients  and long-lasting local effects . Considering the mechanism of gamma generation and propagation, we suggest that the frontal cortex plays the crucial role in pathway of the stimulation: the SCS alters the frontal cortex by using the thalamus-cortex connection, and then the global brain are modulated via connectivity with the frontal cortex. In addition, the pathway may be the anatomical basis by which the SCS modulates the brain. Since the thalamus, frontal cortex and parietal/occipital cortex play crucial roles in the consciousness-related network, the effects of SCS on consciousness may benefit from interfering with the circuit-level network.This study was carried out in accordance with the recommendations of the ethics committee of PLA Army General Hospital with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the ethics committee of PLA Army General Hospital.YB had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: YB and XX. Acquisition, analysis, or interpretation of data: YB and XX. Drafting of the manuscript: YB. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: YB. Obtained funding: JH and XL. Administrative, technical, or material support: YW. Study supervision: JH and XL.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.