LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( Skin cancer is the most common form of cancer and can be divided into three histological subtypes: basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and cutaneous melanoma (CM) . AlthougWith the application of whole genome and transcriptome sequencing technologies, it has been shown that only < 2% of the human genome can encode protein-coding genes and at least 90% of the genome is actively transcribed and give rise to a range of the non-coding RNA transcripts (ncRNAs) . NcRNAs In this study, we analyzed the lncRNA expression profiles and clinical data in 225 patients with cutaneous melanoma from The Cancer Genome Atlas (TCGA) project. The aim of our study was to assess the prognostic value of lncRNAs in cutaneous melanoma and tried to identify a lncRNA signature that could be used as a molecular prognostic marker for patients with cutaneous melanoma.All patients from TCGA were first randomly divided into the training cohort n=113) and validation cohort (n=112) for the purpose of discovery and validation of prognostic RNAs. By subjecting lncRNA expression of patients in the training cohort to univariable Cox proportional hazards regression analysis, we identified 40 prognostic lncRNA candidates that were significantly correlated with survival time (p<0.005). Then we performed the multivariate analysis to evaluate the independent prognostic value of these 40 candidate prognostic lncRNAs and identified six lncRNAs as independent prognostic factors with the ability to predict the outcome. The overview of these six prognostic lncRNAs was listed in Table 13 and vaLINC01260)+(-0.1522*expression of HCP5)+ +(-0.4409*expression of CTA-292E10.6)+ +(-0.2056*expression of CTB-113P19.5). A patient with six-lncRNA signature risk score larger than the median risk score (0.562) was classified as high-risk, whereas patients with risk score six-lncRNA signature risk score smaller than the median risk score (0.562) was classified as low-risk. When the six-lncRNA signature was applied to the training cohort, all patients of the training cohort were divided into the high-risk group (n=57) and low-risk group (n=56) according to the threshold of the median risk score (0.562). Patients in the high-risk group had significantly shorter median survival time than those in the low-risk group   Figure . In detaDistribution of the six-lncRNA signature risk scores, the expression pattern of prognostic lncRNAs and the survival status was shown in Figure To confirm the survival prediction power of the six-lncRNA signature, we tested the six-lncRNA signature in the validation cohort. Each patient of validation cohort was assigned a risk score by the six-lncRNA signature, and was classified into the high-risk or low-risk patient according to the threshold of the median risk score 0.562) derived from the training cohort. The patients of the validation cohort were classified as high-risk (n=59) or low-risk (n=53) with significantly different survival time. Kaplan-Meier curves for the high-risk and low-risk groups within the validation cohort are shown in Figure  derived The six-lncRNA signature was then tested for its prognostic value in the 225 patients of entire TCGA cohort. The same six-lncRNA signature and threshold as those derived from the training cohort classified 116 and 109 patients of the entire TCGA cohort into the high-risk and low-risk groups, respectively. Consistent with the findings described above, patients in the high-risk group had significantly shorter overall survival than those in the low-risk group  Figure . In detaDistribution of the six-lncRNA signature risk scores, the expression pattern of prognostic lncRNAs and the survival status was shown in To test whether the prognostic power of the six-lncRNA signature for survival prediction is independent of other clinicopathological factors, we performed multivariate Cox regression to test the performance of the six-lncRNA signature in comparison with other clinical factors, including age, gender and stage. The results from the training cohort showed that the six-lncRNA signature , stage III  and stage IV  was significantly correlated with overall survival of the patients with cutaneous melanoma  Figure . Similaret al. revealed a 28-gene signature to predict the metastatic risk associated with cutaneous melanoma [Cutaneous melanoma is one of the most common malignancies and causes the greatest number of skin cancer-related deaths. Prediction of disease progression and prognosis is important for personalized risk assessment to improve treatment efficacy. With advances in the high-throughput omics study, large-scale genomic analyses of cutaneous melanoma have provided insights into the biological heterogeneity of cutaneous melanoma which has potentially important implications for improving prognosis . Althougmelanoma . Furthermelanoma . A subsemelanoma .BANCR, SLNCR1, CASC15, MALAT1 and so on [Despite great improvements in developing molecular biomarkers in cutaneous melanoma, these existing molecular signatures were mainly based on expression of mRNAs or miRNAs. Recently, a novel class of ncRNAs, termed lncRNAs, has been discovered and indicated as one of cancer hallmarks . Comparend so on , genome-nd so on , thus faLINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5) was constructed as an indicator for the clinical outcome of patients with cutaneous melanoma. By applying the six-lncRNA signature to the training cohort, a clear separation was observed in the survival curves between high-risk group and the low-risk group. Patients with high-risk lncRNA signature had poor survival outcome than those with low-risk lncRNA signature. Moreover, the six-lncRNA signature demonstrated robust and stable prognostic ability for survival prediction in both the validation cohort and entire TCGA cohort. Further analysis of univariable and multivariate Cox regression models showed that the six- lncRNA signature was an independent prognostic factor for patients with cutaneous melanoma. The six lncRNAs identified in this study provide novel insights into the molecular heterogeneity of cutaneous melanoma and also have potentially important implications for prognosis and therapy for cutaneous melanoma.In this study, we tried to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with the survival of patients with cutaneous melanoma. A linear combination of six lncRNAs  and their prognostic values should be tested in another independent patient cohort. Secondly, the biological function of these six lncRNAs has not been reported up until now and therefore needed to be studied using biological experiments in the future.https://cancergenome.nih.gov/). After removing patients without clinical information and lncRNA expression profiles, 225 patients with cutaneous melanoma were used in this study. Patients with cutaneous melanoma were randomly divided into a training cohort (n=113) and a validation cohort (n=112). The detailed clinical characteristics of patients in the training cohort and validation cohort were summarized in Table Clinical characteristics of patients with cutaneous melanoma were downloaded from The Cancer Genome Atlas (TCGA) data portal (hort n=11 and a vahttp://bioinformatics.mdanderson.org/) [Genome-wide lncRNA expression profiles of patients with cutaneous melanoma were obtained from the TANRIC database (on.org/) . Brieflyon.org/) . Then weUnivariable Cox regression analysis was used to identify candidate lncRNAs that are significantly associated with survival. Then these candidate lncRNAs were subjected to the multivariate Cox regression analysis to access their interactive effect and identify independent prognostic lncRNAs to predict survival of patients. To develop a lncRNA signature, these independent prognostic lncRNAs were fitted in a multivariate Cox regression model in the training cohort to obtain estimated regression coefficients as weights to represent their relative power in predicting survival. Then a prognostic lncRNA signature was constructed by including expression values of each prognostic lncRNAs, weighted by their estimated regression coefficients in the multivariate Cox regression analysis as follows:i is the expression value of lncRNAi and Coef is the estimated regression coefficients of lncRNAi in the multivariate Cox regression analysis. The median risk score in the training cohort was used to as risk cutoff value to classify patients into the high-risk group and low-risk group.Where n is the number of lncRNAs in this signature, expKaplan-Meier survival curves and log-rank tests were used to assess the differences in survival time between the high-risk and low-risk patients using the R package “survival”. Multivariate analyses were performed using Cox proportional hazards regression model to determine whether the lncRNA signature was independent of other clinical variables. Hazard ratios (HR) and 95% confidence intervals (CI) were calculated. The prognostic accuracy of lncRNA signature was also tested using time-dependent receiver operating characteristic (ROC) analysis using the R package“survival-ROC”. We used


The present study aimed to assess the changes in blood factors and ultrasound measures of atherosclerosis burden patient with mild cognitive impairment (MCI) and dementia. Peripheral blood samples and ultrasonography findings were obtained for 53 enrolled participants. Flow cytometry was used to evaluate levels of activated platelets and platelet-leukocyte aggregates (PLAs). The number of platelets expressing p-selectin was correlated with intima media thickness (IMT) and plaque number in both the MCI and dementia groups. The number of platelets expressing p-selectin glycoprotein ligand (PSGL) was strongly correlated with IMT in patients with MCI, whereas the number of platelets expressing PGSL was correlated with plaque number rather than IMT in patients with dementia. PLAs was associated with both IMT and plaque number in patients with MCI but not in those with dementia. Our findings demonstrate that alterations in IMT and plaque number are associated with an increased risk of cognitive decline as well as conversion from MCI to dementia and that blood factor analysis may aid to detect the severity of cognitive decline. Aging has been regarded as a major risk factor for neurodegenerative disease  were observed. Fasting levels of total and high-density lipoprotein (HDL) cholesterol, triglycerides and low-density lipoprotein (LDL) cholesterol were also measured in each participant. The characteristics of the participants are shown in Table Participants underwent measurement of carotid artery IMT, plaque morphology and thickness of carotid plaques via B-mode ultrasonography. Carotid artery plaques were examined using a high-resolution B-mode ultrasound system  equipped with a multi-frequency linear array transducer (5–10 MHz). All measurements were performed by a technician trained in ultrasound research in accordance with a standard scanning and reading protocol.Carotid artery IMT is defined as a distance from media-adventitia to lumen-intima interface. Carotid artery IMT  was measured offline in a plaque-free region at the far wall of the common carotid artery (CCA) using a computerized system. The upper limit of normal for IMT was defined as 1.0 mm. IMT measures were obtained from walls of three arterial segments of both carotid arteries; the near and far wall of the proximal 10 mm of the internal carotid artery, the near and far wall of the carotid bifurcation beginning at the tip of the flow divider and extending 10 mm proximally, and the near and far wall of the arterial segment extending 10–20 mm proximally to the tip the flow divider into the CCA -conjugated anti-CD41a for immunological identification of platelets. The samples were simultaneously incubated with fluorescein isothiocyanate (FITC)-conjugated anti-CD62p or FITC-conjugated anti-CD162 at saturating concentrations for 15 min at room temperature in the dark. Levels of platelet-bound anti-CD62p or -CD162 were determined by analyzing 50,000 platelets for FITC fluorescence. Results were expressed as a percentage of antibody-positive platelets.Blood samples were collected into Vacutainer tubes containing 0.5 mL of 3.2% buffered sodium citrate, immediately following which the citrated blood sample was added to a fixation solution to minimize Red blood cell-lysed blood samples were used to determine leukocyte levels, which were identified based on the forward and sideward scatter properties of PE-CD45-positive leukocytes. Monocytes and lymphocytes were identified based on strong expression of PE-CD14 and PE-CD154, respectively. The presence of platelet-leukocyte aggregates was assessed during the detection of CD42b-FITC-labeled platelets. FITC-conjugated immunoglobulin G (IgG) and PE-conjugated IgG antibody were used for isotype control experiments. A minimum of 50,000 cell events was analyzed in each assay. The percentages of platelet-monocyte and platelet-lymphocyte complexes were calculated. All antibodies used were purchased from BD Biosciences . Blood samples were analyzed using LSRII .p < 0.05 were considered statistically significant . Pearson correlation coefficients were used to assess the association between ultrasound findings (IMT and plaque number) and changes in blood factors associated with atherosclerotic vessel dysfunction. Values of the coefficient constant r and r2 are provided. A value of p ≤ 0.05 was regarded as significant .Participant characteristics and plaque thickness are presented as mean ± SD. Fluorescence-activated cell sorting (FACS) and ELISA values are presented as medians. The clinical characteristics of each group were compared using the Mann–Whitney nonparametric test. Statistical significance among groups was determined via one-way analysis of variance (ANOVA). Probability values were two-tailed, and values of p = 0.4), HDL (p = 0.7421) and LDL (p = 0.3439). Participant characteristics are detailed in Table p = 0.0061; control vs. dementia: 6.8 ± 4.2, p = 0.0012; Figure In the present study, there was no significant difference in vascular risk factors among the control, vessel damage, MCI and dementia groups. Moreover, there were no significant differences among the three groups with regard to total cholesterol  revealed that specific changes in PLA level in each MCI or dementia group Figure . The levThe number of platelets expressing p-selectin (CD62p) by FACS was increased in dementia group whereas the number of platelets expressing p-selectin glycoprotein ligand  was high both in MCI and dementia group Figures . The levThe correlation between cognitive function and circulating adhesion factors was analyzed as shown in Table In the present study, we demonstrated that alterations in IMT and plaque number are associated with an increased risk of cognitive decline as well as risk of dementia. Our results suggest that ultrasound findings may aid in identifying older individuals at increased risk for the progression of cognitive decline when morphological impairment of cerebrovascular structures has been identified. Moreover, our findings suggest that the presence of atherosclerotic changes and changes in blood factors such as PSGL, PLA and PMA can be used to predict MCI and dementia.In the present study, levels of p-selectin in circulating platelets, PSGL and circulating PMA were significantly increased in patients with MCI relative to controls Figures , 3. The Researchers have suggested a relationship between atherosclerotic severity and circulating adhesion blood factors; atherosclerotic severity and cognitive decline in the above mentioned reports. With one step further linking between them, our findings provide insight into the use of blood factor analysis (using FACS) as well as ultrasonographic evaluation of vessel status in both clinical and research settings. Changes in platelet activation and monocyte distribution are observed in the early stages of atherosclerosis. Such changes are strongly associated with stroke onset, as demonstrated by various studies (King et al., The present study shows that increased IMT was more frequently observed in patients with MCI, whereas increased numbers of carotid plaques were more frequently observed in patients with dementia. The patients with MCI in our study comprise 32% of all patients with atherosclerosis, and all patients of the MCI group in the present study had been diagnosed with carotid vascular stenosis or atherosclerosis Figure . These fOur results indicate that intima thickness and plaque number are associated with higher levels of p-selectin, as the evidence that platelets are engaged in the formation of PLAs (Steinhubl et al., The present study has some limitations that need consideration. First, longer follow-up is required to verify our findings. We are currently preparing a 3-year follow-up study including the participants of the present study and additional volunteers. Second, as the sample size was rather small, future studies should enroll a larger population. Future FACS studies should also aim to determine a cutoff value for each blood cell population for the prediction of progression from cognitive decline to dementia in older adults with cardio/cerebrovascular disease. Our simple assessment of vascular risk factors does not seem to be a fully satisfactory approach for adequately counteracting the risk of developing dementia, when compared to other large-scale studies (Coley et al., In conclusion, our findings demonstrate that circulating adhesion molecules level and interaction between factors present significant differences in patient with MCI or dementia. Alterations in IMT and plaque number are associated with an increased risk of cognitive decline as well as conversion from MCI to dementia. These results suggest that ultrasound findings may aid in identifying older individuals at increased risk for the progression of cognitive decline in when cerebrovascular damaged. Moreover, our findings suggest that the presence of atherosclerotic changes and changes in blood factors such as p-selectin, PSGL, PLA and PMA can be useful candidates to monitor the severity of cognitive decline.KC composed the manuscript and performed most of laboratory works and data. JK collected blood sample from outpatients and clinical records; and GWK supervised the whole study.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.


Leaky ribosome scanning produces a long Golgi-localized and a short plasma membrane-localized version of the JAS protein, with the short version required during meiosis to ensure products are reduced. The JASON (JAS) protein plays an important role in maintaining an organelle band across the equator of male meiotic cells during the second division, with its loss leading to unreduced pollen in Arabidopsis. In roots cells, JAS localizes to the Golgi, tonoplast and plasma membrane. Here we explore the mechanism underlying the localization of JAS. Overall, our data show that leaky ribosom scanning and alternative translation initiation sites (TISs) likely leads to the formation of two forms of JAS: a long version with an N-terminal Golgi localization signal and a short version with a different N-terminal signal targeting the protein to the plasma membrane. The ratio of the long and short forms of JAS is developmentally regulated, with both being produced in roots but the short form being predominant and functional during meiosis. This regulation of TISs in meiocytes ensures that the short version of JAS is formed during meiosis to ensure separation of chromosome groups and the production of reduced pollen. We hypothesize that increased occurrence of unreduced pollen under stress conditions may be a consequence of altered usage of JAS TISs during stress. The correct subcellular localization of a protein is an essential aspect of its function and is vital for cellular performance. Proteins are directed to different subcellular locations largely based on their primary amino acid (AA) sequence and secondary structure. Many proteins contain characterized targeting signals such as N-terminal transit peptides for mitochondrial and plastid import, N-terminal signal peptides for entry into the endoplasmic reticulum and the secretory pathway or internal nuclear localization signals  protein in Arabidopsis is located in multiple membranes within cells, namely the Golgi, membrane . Such unHere we explore the mechanism controlling the localization of JAS to multiple locations. We reveal that there are two versions of JAS that localize to different subcellular compartments: a longer Golgi-localized form with the N-terminal extension and a shorter plasma membrane-localized form. We show that the N-terminal region of the longer form is both necessary and sufficient for Golgi localization, and that basic residues play a role in this localization. By altering the nucleotides immediately upstream of the first ATG the production of the Golgi-localized protein was favored, strongly suggesting that leaky ribosome scanning leads to the use of alternative TISs producing the two forms of JAS. The ratio of the two forms of JAS is likely to be developmentally regulated with the short, plasma membrane-localized form being predominant and functional in male meiotic cells.Arabidiopsis thaliana plants in the Columbia background with mutant plants containing the jas-3 allele  from 943 bp upstream of the TIS (TAIR10) to immediately before the stop codon (+2685) was amplified from genomic DNA (primers in pENTR-D-TOPO (Thermo Fisher Scientific) and verified by sequencing. The subsequent pENTR-D-TOPO:JASg was used as a template for site directed mutagenesis using the QuikChange II kit (Agilent Technologies) and primers in PMDC107 (mGFP6 via an LR reaction with LR Clonase II (Thermo Fisher Scientific).A genomic fragment of  PMDC107  in framepUBQ14:longJASc-GFP, pUBQ14:shortJASc-GFP, pUB Q14:JAS-LIKE-GFP, pUBQ14:NT-JAS-LIKE-GFP, pUBQ14:NT-GFP, pUBQ14:longMtrJR1c-GFP, and pUBQ14:shortMtrJR1c-GFP constructs were generated by Gateway multisite cloning. DNA was amplified from Arabidopsis genomic DNA (pUBQ14) or inflorescence cDNA from Arabidopsis  or Medicago (Medicago truncatula) R108 (longMtrJR1c and shortMtrJR1c) using Phusion high fidelity polyermase (Finnzymes) and primers with suitable attachment sites (pK7m34GW (The nt sites . To joinTOPO:JASg vector using Platinum Taq DNA polymerase (Thermo Scientific) and primers with appropriate restriction enzyme sites  to an OD600 of 0.5. After 2 h at room temperature, A. tumefaciens cells were infiltrated into N. benthamina leaves. Leaf disks of 7 mm were harvested 3–4 d after infiltration and homogenized in 50 μl 1× Cell Lysis Buffer (Targeting Systems). Renilla luciferase activity was measured sequentially using a CLARIOStar® microplate reader with injection of 50 μl Luciferase Assay Reagent (Promega) followed by 50 μl Renilla Luciferase Stop and Glo® reagent (Promega). Assays were conducted on three separate occasions to give three biological replicates with three leaves sampled on each occasion.Vectors were transformed by electroporation into Predictions of the subcellular localization of the JAS protein utilized TargetP , TMHMM , and SLPJR proteins were identified by TBLASTN searches of angiosperm genomes in Phytozome (www.ncbi.nlm.nih.gov/geo) under accession no. GSE50597. The raw reads were quality and adapter trimmed using cutadapt  sequence  in 5- to 6-day-old roots of transgenic Arabidopsis seedlings. For each fusion protein, GFP was detected in cells behind the root tip, although with varying fluorescence intensity in different cells and cell files in individual roots . This siTo determine the subcellular location of the different JAS–GFP proteins, transgenic plants were crossed with markers for the Golgi (SYP32–mCherry), tonoplast (VAMP711–mCherry) and plasma membrane  , and eacJAS cDNA with the N-terminal region  and a truncated version without the N-terminal sequence  under control of the UBQ14 promoter. When JAS contained the N-terminal sequence, a similar pattern to the longJASg–GFP was observed, with JAS being localized in organelles that overlap with the Golgi marker and also appearing to be in the tonoplast, but not in the plasma membrane  likely reflects that of the endogenous JAS protein, as it is encoded by a long genomic fragment of The colocalization experiments using longJASg–GFP and shortJASg–GFP revealed that the N-terminal 28 AA of the long version is necessary for Golgi localization. We therefore addressed whether the N-terminus is also sufficient for Golgi localization.UBQ14 promoter. A strong GFP signal largely colocalized with the plasma membrane marker and a much weaker signal colocalized with the tonoplast marker in Arabidopsis root cells   proteins. We focused on eudicots, as most eudicots undergo simultaneous cytokinesis during meiosis whereas monocots undergo successive cytokinesis and so do not require the organelle band in which JAS functions. We identified putative JAS homologs based on the C-terminal plant-conserved domain . The JR While each eudicot has at least one long JR protein, there is not a high degree of sequence identity in the N-terminal extension . HoweverMedicago truncatula). The N-terminal sequence of the Medicago JR1 (MtrJR1) protein differs from JAS but has the general characteristics described above (longMtrJR1c-GFP) or second ATG (shortMtrJR1c-GFP) driven by the UQB14 promoter were constructed. In Arabidopsis roots longMtrJR1c–GFP was partially localized to the Golgi  encodes the same protein as the unmodified genomic form (JASg-GFP) yet they display different localization patterns  or the later ATG (ATG+85), luciferase activity was again greater than the vector with luciferase lacking an ATG (t-test).In order for leaky scanning to arise, two AUGs in the mRNA must be able to act as TISs. To test if the AUGs at both +1 and +85 in G unmod, . Therefog an ATG , demonstJAS, consistent with both being translation initiation sites and the long and short forms of JAS being translated in seedlings  and the short cDNA (shortJASc-GFP) complemented in about 50% of independent T1 lines  expression of longJASg–GFP and longJASc–GFP with different promoters and 5′-UTRs resulting in similar localization patterns, making transcriptional control and alternative splicing unlikely, (iii) the suboptimal Kozak context of the first AUG in the JAS mRNA followed by a context closer to the optimal Kozak at the AUG at position +85, (iv) the ability of ATGs at both +1 and +85 to initiate translation in luciferase assays and in Arabidopsis seedlings as assessed by ribosome protection data (CTTCJASg-GFP) likely due to enhanced translation at the first AUG reducing initiation from the downstream site.In roots cells the two forms of JAS likely arise from a single genomic region, shown by proteins encoded by the  protein . One mec protein , 2002. WLeaky ribosome scanning and alternative TISs have been described for a range of proteins in animals, plants, and viruses. The alternative N-termini often impact upon the localization of the protein (jas mutant plants. It may be that the two forms have different molecular functions or that the same function is required in the Golgi and the plasma membrane. It does, however, appear that the choice of TISs in seedlings is regulated with translation from the AUG at position +85 producing the shortJAS favored under normal growth condition and the AUG at +1 giving longJAS favored under anoxic conditions. Regulated selection of AUGs during scanning and the discrimination between optimal and suboptimal Kozak contexts can be influenced by factors such as the abundance and activity of certain translation initiation factors (POLγ2 mRNA (As the JASg–GFP protein localizes to the Golgi and plasma membrane in Arabidopsis root cells, we conclude that the long and short forms of JAS are both present in these cells. Additionally, published ribosome protection data suggest both forms are translated in seedlings, although overall expression of JAS is low (Supplemental Fig. S6; Lγ2 mRNA .In male meiotic cells the JAS protein is required to maintain an organelle band across the equator of the cell during the second division to ensure correct spindle position and reduced meiotic products (The predominance and functional importance of the short JAS protein in meiocytes indicates that the choice of TIS is regulated in these cells to favor initiation from the ATG at +85. A role for translational regulation in animal  and yeasjas mutant, has long been observed (reviewed in JAS mRNA is preferentially selected and the long protein translated, as was observed in seedlings under hypoxic stress. This alteration in TIS would lead to a reduction in the amount of the short protein that is functional during meiosis, causing a disturbance in the organelle band and spindle misplacement, resulting in unreduced pollen.The observation that production of the short form of JAS during meiosis is regulated suggests a possible link between JAS regulation and the occurrence of unreduced pollen during stress conditions. A link between stress and the formation of unreduced male gametes through spindle misplacement, similar to the JXB online.Supplementary data are available at Fig. S1. Predicted secondary structure of the JAS protein.Fig. S2. Subcellular localization of stopJASg–GFP.Fig. S3. Subcellular localization of cDNA-encoded JAS–GFP.Fig. S4. Plasmolysed Arabidopsis root cell with JAS-LIKE–GFP.Fig. S5. Subcellular localization of GFP with the N-terminal 28 AA of longJAS.JAS.Fig. S6. Ribosome protection data for Table S1. Primers used in this study.Table S2. Gene identifiers for JR proteins shown in Supplementary TablesClick here for additional data file.


Sarcoidosis is a systemic granulomatous disease of unknown etiology, characterized by the formation of noncaseating granulomas. Gastrointestinal (GI) system involvement that is clinically recognizable occurs in less than 0.9% of patients with sarcoidosis, with data revealing small intestine involvement in 0.03% of the cases. A high index of suspension is required in patients presenting with small-bowel obstruction and previous history of sarcoidosis. Establishing a definitive diagnosis of GI sarcoidosis depends on biopsy evidence of noncaseating granulomas, exclusion of other causes of granulomatous disease, and evidence of sarcoidosis in at least one other organ system. Treatment of GI sarcoidosis depends on symptomatology and disease activity. Herein, we are presenting a case of 67-year-old female patient who had acute small-bowel obstruction at the level of jejunum with postoperative histopathologic evidence of noncaseating granulomatous inflammation with multinucleated giant cells, consistent with sarcoidosis.  Sarcoidosis is a systemic granulomatous disease of unknown etiology, characterized by the formation of noncaseating granulomas. Gastrointestinal (GI) involvement is very rare and can occur in a patient with known sarcoidosis or as the initial manifestation of the disease. Small-bowel obstruction secondary to sarcoidosis has been described in few case reports. Herein, we are reporting a case of 67-year-old female patient who had acute small-bowel obstruction at the level of jejunum with postoperative histopathologic evidence of noncaseating granulomatous inflammation consistent with sarcoidosis.2% of 98% on room air. Her abdomen was distended and mildly tender over the epigastric area, with no evidence of organomegaly. Her bowel sounds were hyperactive. Initial imagining studies with abdominal X-ray revealed dilated small-bowel loops with multiple scattered air fluid levels suggesting partial versus early complete small-bowel obstruction. A contrasted computed tomography (CT) scan of the abdomen and pelvis demonstrated multiple dilated loops of proximal small bowel with no definitive transition point and no intraperitoneal free air or fluid identified, a picture suggestive of a high-grade small-bowel obstruction  system involvement that is clinically recognizable occurs in 0.1–0.9% of patients with sarcoidosis, with one study revealing postmortem small intestine involvement on autopsy in 0.03% of the cases . It usuaGastrointestinal (GI) sarcoidosis is very rare and can occur in a patient with known diagnosis or as initial presentation. A high index of suspension is required in patients presenting with small-bowel obstruction and previous history of sarcoidosis.


Associative learning is a common way for information acquisition, and the integrative storage of multiple associated signals is essential for associative thinking and logical reasoning. In terms of the cellular mechanism for associative memory, our studies by behavioral task and cellular imaging demonstrate that paired whisker and odor stimulations lead to odorant-induced whisker motion and associative memory cell recruitment in the barrel cortex (BC), which is driven presumably by synapse innervation from co-activated sensory cortices. To confirm these associative memory cells and synapse innervations essential for associative memory and to examine their potential mechanisms, we studied a causal relationship between epigenetic process and memory cell/synapse recruitment by manipulating miRNAs and observing the changes from the recruitments of associative memory cells and synapse innervations to associative memory. Anti-miRNA-324 and anti-miRNA-133a in the BC significantly downregulate new synapse innervation, associative memory cell recruitment and odorant-induced whisker motion, where Tau-tubulin kinase-1 expression is increased. Therefore, the upregulated miRNA-324 in associative learning knocks down Ttbk1-mediated Tau phosphorylation and microtubule depolymerization, which drives the balance between polymerization and depolymerization toward the axon prolongation and spine stabilization to initiate new synapse innervations and to recruit associative memory cells. Associative memory plays important roles in cognitive processes, such as logical reasoning and associative thinking . The molecular targets of miRNAs were studied by using dual luciferase report assay and western-blot. The detection of associative memory cells in the BC was done by using two-photon cell imaging All experiments were conducted based on the guideline by Administration Office of Laboratory Animals at Beijing China. Experiment protocols were approved by Institutional Animal Care Unit Committee in Administration Office of Laboratory Animals at Beijing China (B10831).n = 4 mice per cage) with a usual circadian cycle about 12 h under light condition and 12 h under dark condition.C57 Thy1-yellow fluorescent protein (YFP) mice  with odor stimulus  and were quantified in onset latency from odor test to whisker motion, whisking frequency and whisking duration . Whisking frequency and duration were converted into digital signals in 0.5 s as one unit, such that their dynamic values per second were presented before, during and after odor-test. The responses of mouse whiskers to the odor-test  were measured at the end of each training day to quantify the onset time and levels of the CR. CR-formation was defined to meet the following criteria. The patterns of odorant-induced whisker motion were similar to those of WS-induced whisker motion. Whisking frequency and whisker retraction time were significantly increased as well as the latency of whisker motion in response to odor-test was significantly reduced, compared with control and before the training. As this type of whisker motion induced by odorant was originally induced by WS, the odor signal evoked a recall of whisker signal and led to whisker motion  on the same side and rows were assigned for mechanical stimulations and for the observations during the odor-test. This selection was based on the studies of cross-modal plasticity , was used to measure neuronal activities. A craniotomy (2 mm) was made on the skull above barrel cortical areas . In surgical operations, the anesthetic depth was set at the levels where the mice demonstrated lack of reflexes in pinch withdrawal and eyelid blinking. The body temperature was maintained by a heating blanket whose temperature was electronically controlled at 37°C. Cain vivo two-photon cell imaging in the mice was set at the moderate reflexes in pinch withdrawal and eyelid blinking, as well as the responses of their whiskers to the test stimuli , which was equipped by the two-photon laser-beam generator  and mounted to an upright microscope (Olympus BX61WI) with the water immersion objectives . A wave of two-photon laser beam at 810 nm was given to excite OGB and examine neuronal responses to WS and OS. The emission wavelength was 525 nm for Ca2+-binding OGB. Average power delivered to the barrel cortices was less than 75 mW to minimize photo bleach. Whole field images were acquired at 10 Hz of frame rate (256 × 256 pixels). The parameters for photomultiplier tube (PMT) and laser beam were locked in the measurements throughout all experiments to have consistency in data comparison.The anesthetic depth for doing Similar to the stimuli in behavioral task, an odor-test pulse toward the noses or mechanical pulses to the whiskers on the contralateral side of two-photon imaged cortices were used to induce cell responses. Stimulus patterns were pair-pulses (OS vs. WS or WS vs. OS) and pulse intervals were 60 s  and analyzed in cell bodies by NIH ImageJ and MATLAB (MathWorks). To reduce photon and PMT noise, a median filter  was used to all images. Ca2+ signals were normalized and presented as relative fluorescence changes (ΔF/F). Basal fluorescence (F) was an averaged value before stimuli. Values about ΔF were the differences of Ca2+ signal fluorescent strengths between evoked response and basal condition  into the piriform cortex (PC) and by detecting its presence in the BC from C57 Thy1-YFP mice  into left ventricle until their bodies were rigid. The brains were quickly isolated and fixed in 4% paraformaldehyde PBS for additional 24 h. The cerebral brains were sliced in a series of coronal sections at 100 μm. These slices were rinsed by PBS for three times, air-dried and cover-slipped. In order to clearly show three-dimension images for new synapses in the BC, we placed the brain slices into a solution (Sca/eA2) for a few hours to make them transparent . The excite wavelength was 488 nm for GFP and YFP. Although the peaks of the GFP and YFP emission wavelengths are closely at 510 nm and 525 nm, respectively, we scanned the images of these neurons by setting up the optical grating in 505–515 nm for GFP and the optical grating in 545–555 nm for YFP to separate their fluorescent images. These images were merged to construct the newly formed synapses. Although we have reported the functional connection from the PC to the BC in CR-formation mice . The site-mutation of the detected miRNA targeting site of 3′-UTR fragment was constructed based on a guideline of QuikChange Lighting Site-Directed Mutagenesis Kit . miRNA mimics and their negative control (NC) were synthesized by Guangzhou Rui Bo Biological Technology Co. Ltd., China. Primer sequences are listed in Supplemenatry Table S1. For the luciferase reporter detection, HEK293T cells were planted in RPMI media containing 10% fetal bovine serum at 5 × 104 cells per well in 24-well plates. After 24 h, these cells were co-transfected with 20 ng psiCHECK2-3’UTR wild-type or mutant reporter plasmids. In the meantime, these wells of cell culture were added by 50 nM of miRNA mimic or miRNA-NC by using Lipofectamine 2000 transfection reagent . The activities of firefly and Renilla luciferases were assessed after 48 h by using Dual-Glo® Luciferase Assay System , based on the manufacturer’s protocols. A ratio of Renilla luciferase activity to firefly luciferase activity was used to analyze the level of mRNA expressions regulated by miRNAs, such as mRNA downregulation or upregulation . After SDS-PAGE, proteins were electrically transferred onto nitrocellulose membrane. The membrane was incubated by blocking solution  at room temperature (25°C) for 2 h, and then incubated overnight by a primary antibody (1:2000 in dilution) of Ttbk1  or by primary antibody (1:1000 in dilution) of β-actin  in 5% milk in TBST. After incubations with their corresponding secondary antibodies conjugated with peroxidase , the bands of these proteins were visualized by using the enhanced chemiluminescence ECL Plus immunoblotting detection system . The protein bands corresponding to the expected size were selected and read by using this computerized scanner. The pixel density in each of these bands was determined by this computer after the background was corrected, which were used to quantify for the relative level of these proteins. The optical densities of each band relative to measured values of β-actin bands were determined using ImageJ software  for their homogenizations. The homogenized tissues were removed into a new EP tube (1.5 ml), kept at 4°C in a refrigerator for 30 min, and centrifuged at 12,000 t-test was used in the comparisons of the experimental data before and after associative learning as well as the neuronal responses to WS and odorant stimulus in each of the mice. One-way ANOVA was used for the statistical comparisons in the changes of neuronal activity and morphology between the miRNA antagomir and antagomir control groups. It is noteworthy that the behavioral studies and the data analyses are conducted by different individuals.The paired In the present study, we aim to study the causal relationship from new synapse innervations and associative memory cell recruitment to associative memory as well as to examine their molecular mechanisms by manipulating epigenetic process. To investigate the roles of epigenetics-mediated events, such as miRNAs, in associative memory cell recruitment, synapse innervation and associative memory, we have injected the antagomirs of miRNA-324-5p and miRNA-133a-3p or antagomir NC into mouse barrel cortices Figures . The selAfter the training in the mice, the OS-test was given to their noses. The mice that have received antagomir control express whisker motion in response to the OS Figure . This od2+ imaging, which had been injected with the antagomirs of miRNA-324 and miRNA 133a (Figure 2+ signals in response to the WS vs. the OS from a mouse in antagomir group and from a mouse in antagomir control group. The proportions of the neurons in response to the OS are significantly lower in antagomir group than antagomir control (Figure 2+ signal strengths (Figure 2+ signals in response to the WS are not statistically different between antagomir group and antagomir control group (Figures The influence of anti-miRNAs on the recruitment and activities of associative memory cells was examined in the barrel cortices of WS/OS-trained mice by using two-photon cell Caa Figure  or antaga Figure . Figuresl Figure , implyins Figure  and duras Figure  are sign Figures . Our res2+ signal strength and duration in response to the OS are significantly lower in antagomir-transfected cells than non-transfected cells (Figure This indication should be further tested in barrel cortical neurons that are transfected vs. non-transfected by miRNA antagomirs in mice whose barrel cortices receive the injection of miRNA antagomirs. In barrel cortices, red fluorescent-labeled neurons were thought to be antagomir-transfected neurons, or vice versa, since miRNA antagomirs had been conjugated with Cy3. The proportions of miRNA antagomir-transfected neurons are 48.2 ± 5.2% in response to the WS and 6.9 ± 1.0% in response to the OS Figure , indicats Figure . These pThe recruitment of associative memory cells in the BC may be driven by the synapse innervations from the PC (Wang et al., Taken these results together, we suggest that there are the causal relationships among synapse formation, associative memory cell recruitment and associative memory, in which the epigenetic molecular events triggered by miRNA-324 and miRNA-133a play critical roles in these processes.Ttbk1 that translates Tau-tubulin kinase-1 is a predicted target of these miRNAs. This brain-specific kinase phosphorylates microtubule-associated protein Tau, leading to its aggregation (Sato et al., Ttbk1 by dual luciferase report assay. Luciferase reporter plasmids including the wild-type or mutant 3′-UTRs of predicted miRNA-324-5p binding site in Ttbk1 (top panel in Figure Ttbk1 3′-UTR is significantly inhibited by miRNA-324 and this inhibition is reversed by mutating miRNA-324-5p binding site (Figure Ttbk1 is a target of miRNA-324-5p.mRNA e Figure . That isThe influence of anti-miRNAs on the expression of Ttbk1 protein was examined by western-blot. The proteins were harvested from the barrel cortices that had received the injection of miRNA antagomirs or their controls. The levels of Ttbk1 appear higher in antagomir group than in antagomir control, which is statistically different Figure . Memory Pairing whisker and odor signals in the mice leads to odorant-induced whisker motion alongside natural whisker-induced whisker motion, i.e., cross-modal associative memory. After receiving new synapse innervations from the axons of co-activated piriform cortical neurons, the barrel cortical neurons are recruited to be associative memory cells that encode the newly learnt odor signal alongside the innate whisker signal. These processes are attenuated by anti-miRNA-324 and anti-miRNA-133a (Figures Ttbk1 that guides the expression of Tau-tubulin kinase-1, which is supported by the data of dual luciferase report assay and western-blot in Figure Ttbk1 by the upregulated miRNA-324 may shift the balance between axon prolongation and retardation toward axon growth from the PC to the BC, and trigger axon terminals to make new synapses onto barrel cortical neurons. These new synapses may drive these barrel cortical neurons to be recruited as associative memory cells (Figure In our study, miRNA-324 acts and downregulates mRNA s Figure .in vivo about axon prolongation and synapse formation are consistent with molecular profiles.The cellular targets of miRNA-mediated epigenetic process for associative memory include the following. Both presynaptic axon boutons Figure  and postThere are two forms of neural plasticity that are associated with memory formation and cognition, i.e., the recruitments of new synapse innervations and associative memory cells as well as the functional change of synapses and neurons. Plasticity in our study falls into new synapse formation and associative memory cell recruitment that are driven by the association of new and innate signals via miRNA-mediated processes. These associative memory cells are specific for the integration and storage of the newly acquired signal and innate signal. On the other hand, plasticity at those existing synapses in a specific pathway, such as LTP (Bliss and Lomo, Based on our studies, the characteristics of associative memory cell are proposed below. They are recruited to encode multiple associated signals. They receive multiple synapse innervations from the sensory cortices that are co-activated and encode different signals. Their axons project toward the brain areas related to cognitions, emotions and behaviors for memory retrieval. The recruitment of associative memory cells is initiated by epigenetic-mediated process. The number of recruited associative memory cells is proportional to memory strength and maintenance. The downregulations of the associative memory cells and their new synapse innervations reduce memory capacity (Wang et al., ZL, DW, NC, KM, WL and ZS contributed to experiments and data analyses. SC contributed to draw diagram. J-HW worked for the concept, project design and article writing.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.


In contrast to mammals, plants carry DNA methylation at all cytosine contexts  with various degrees and effectiveness of N∗ module in genome editing in plants has not been explored. In this study, we designed sets of TALENs with or without N∗ modules and examined their efficiency in genome editing of methylated regions in rice. Although improvement in genome editing efficiency was observed with N∗-TALENs designed to a stably methylated target, another target carrying cytosines with various levels of methylation showed resistance to both normal and N∗-TALENs. The results suggest that variability of cytosine methylation in target regions is an additional factor affecting the genome editing efficiency of TALENs.Genome editing in plants becomes popular since the advent of sequence-specific nucleases (SSNs) that are simple to set up and efficient in various plant species. Although transcription activator-like effector nucleases (TALENs) are one of the most prevalent SSNs and have a potential to provide higher target specificity by their dimeric property, TALENs are sensitive to methylated cytosines that are present not only in transposons but also in active genes in plants. In mammalian cells, the methylation sensitivity of TALENs could be overcome by using a base-recognition module (N Agrobacterium-mediated systems. Rice and other crops are transformed via callus—a mass of dedifferentiated cells from which a whole plant body can be regenerated. Recently, methylation profiles in the genome of rice callus have been reported, showing that methylation state in a fraction of the genome is unstable whereas methylation in the other majority of the genome is highly reproducible in independent calli (Genome editing in crops requires the introduction of sequence-specific nucleases (SSNs) into plants via transformation, commonly involving nt calli . This prFokI nuclease portion of TALENs further suppresses off-target digestion of monomer binding sites /CRISPR-associated protein (Cas) and transcription activator-like effector nucleases TALENs; . TALENs ng sites . Howeverng sites , which ing sites . Bindingng sites , suggestACS1, Os02g0525900/LOC_Os02g32490), which is highly methylated at CG sites within its gene body, a character typical of active genes . Examination of two target sites located at close proximity within a gene is expected to minimize differences due to factors other than cytosine methylation, such as higher order chromatin structure and transcription state, and to provide an accurate estimation of the effect of cytosine methylation on the efficiency of genome editing by TALENs. Plasmids carrying N∗ modules of TALENs were created by deleting a codon corresponding to glycine at the 13th position in NG modules . In addition, the target 31 region contains an additional CHG site that is methylated at 10% in callus. No other cytosines in the target regions are methylated. Stability of the methylation states of these target regions were confirmed by another two independent BS-seq data of wild-type callus samples; methylation in target 274 is relatively stable whereas that of target 31 is variable  contains two CG sites. BS-seq data of two independent wild-type callus samples showed that both cytosines are highly methylated in callus  but not HD module-containing TALENs (274C-TALENs)  yielded detectable genome editing , we analyzed a combination of unmethylated and methylated cytosines in each single DNA molecule by aligning reads of BS-seq that cover the 5′-TALE binding region of target 31. As expected, the three cytosines in CG context are differentially methylated in various combinations in each read . The number of reads carrying methylated cytosines at all three CG sites was less than half of the total reads covering the 5′-TALE binding region. The second most abundant read contained two methylated cytosines and one unmethylated cytosine at CG sites, indicating that the corresponding DNA molecule in the genome carries mixtures of methylated and unmethylated cytosines in the TALE-binding region and so would not be an optimal target for either 31C- or 31mC-TALENs. The 3′-TALE binding region of target 31 contains two cytosines methylated at 90 and 10%, respectively , and this would add further variations to combinatorial binding sites for 31C- and 31mC-TALENs. Together, these data indicate that the presence of methylated cytosines at various levels affects the efficiency of genome editing with TALENs.For target 274, efficient genome editing was observed with N∗ module were examined in rice  showed that methylation rate of cytosine in the 5′ binding site of target 274 (position -12) is high but slightly variable since even control calli showed reduced levels of methylation  that is consistent with data obtained in four independent BS-seq data . Among these calli, a callus sample carrying an active 274mC-TALENs  showed statistically significant differences in methylation at position +11 relative to those of controls and callus without detectable mutation (Supplementary Tables Double-stranded breaks (DSBs) introduced by SSNs are repaired by homologous recombination (HR) or non-homologous end joining (NHEJ); HR restores original sequences, whereas NHEJ often results in various lengths of deletions/insertions. Introduction of mutations by TALENs implies that NHEJ is, at least partly, involved in repair of DSBs by TALENs. Resection of DSB occurs in both repair pathways and is followed by synthesis of new DNA strands in HR; a process that would erase epigenetic information around DSB sites. In addition, DSB formation recruits a set of chromatin proteins that transiently modifies the surrounding chromatin state in eukaryotic cells . Therefoin vivo. Our data provide a precedent for plant genome editing by TALENs in which the methylation state is a critical determinant in selecting target regions and choice of cytosine- or methylcytosine-binding modules in TALENs. A combination of TALENs and information on methylation state in callus will lead to improved efficiencies for genome editing in crops.Plants have methylated cytosines at all sequence contexts  and gene body CG methylation is frequently observed in active genes . AlthougYH designed the work; HK, AN-Y, and YH conducted the experiments; HN analyzed the data; HK, HN, AN-Y, ST, and YH drafted, reviewed, and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


To assess the feasibility of dual-contrast spectral photon-counting computed tomography (SPCCT) for liver imaging.We present an SPCCT in-silico study for simultaneous mapping of the complementary distribution in the liver of two contrast agents (CAs) subsequently intravenously injected: a gadolinium-based contrast agent and an iodine-based contrast agent. Four types of simulated liver lesions with a characteristic arterial and portal venous pattern  are presented. A material decomposition was performed to reconstruct quantitative iodine and gadolinium maps. Finally, a multi-dimensional classification algorithm for automatic lesion detection is presented.Our simulations showed that with a single-scan SPCCT and an adapted contrast injection protocol, it was possible to reconstruct contrast-enhanced images of the liver with arterial distribution of the iodine-based CA and portal venous phase of the gadolinium-based CA. The characteristic patterns of contrast enhancement were visible in all liver lesions. The approach allowed for an automatic detection and classification of liver lesions using a multi-dimensional analysis.Dual-contrast SPCCT should be able to visualise the characteristic arterial and portal venous enhancement with a single scan, allowing for an automatic lesion detection and characterisation, with a reduced radiation exposure. Based on our simulations, dual-contrast liver imaging with spectral photon counting computed tomography is feasible.A dual-contrast injection protocol  enables simultaneous multiphase scanning.The arterial contrast enhancement is visible thanks to the gadolinium-based contrast agent while the portal venous enhancement is visible thanks to the iodine-based contrast agent.Dual-contrast liver SPCCT imaging could help reducing radiation exposure.Computed tomography (CT) is a standard imaging technique for detection and characterisation of focal liver lesions, the majority of them being benign (cysts and haemangiomas). In clinical routine it is important to differentiate benign lesions from malignant lesions, as the liver is a preferential organ for metastases of many primary tumours and benign and malignant lesions may coexist. Accurate diagnosis of hepatocellular carcinoma (HCC) is also important as it is the most common primary malignancy in the liver and the second leading cause of cancer-related mortality in the world –3.With respect to oncological liver diagnostics, conventional contrast-enhanced CT is the workhorse in the clinical day-to-day routine. A controversial discussion concerns dynamic phases  in the setting of different liver pathologies –6. Todaymaterial decomposition, i.e. the analysis of different material components within the examined object.Detection and characterisation of liver lesions on conventional CT is based on differences in the attenuation values between lesions and the normal liver parenchyma. This difference occurs due to a tissue-dependent uptake of contrast agent (CA). In contrast to standard energy-integrating detectors, spectral photon-counting computed tomography (SPCCT) provides additional information on the energy spectrum of x-ray photons after passing through the patient and can thus detect spectral differences in the attenuation. This technology enables The aim of our study was to explore the feasibility of a new approach for liver imaging using two CAs with different x-ray attenuation properties for an improved visualisation and automated detection and characterisation of lesions: a dual-contrast single-scan SPCCT protocol. More specifically, our aim was to investigate if this can be achieved by a specifically adjusted injection protocol, with arterial contrast distribution of one CA and portal venous enhancement of another CA. To achieve this goal, we present the potential of a sequential injection procedure, including a first intravenous injection of a gadolinium-based CA (CA1) and a second injection of an iodine-based CA (CA2), with a specific time gap depending on the individual circulation time. The scan acquisition is simulated at the time point of portal venous distribution for CA1 and at the time of arterial phase for CA2.This retrospective in-silico study was conducted in accordance to the guidelines of the local institutional review board. Anonymised CT datasets of one participant with a healthy liver (n = 1) and four patients, each of them with characteristic liver lesions  were used as a template for the numerical experiment. The diagnosis of liver lesions was confirmed by biopsy for HCC and metastasis while follow-up studies including magnetic resonance imaging confirmed the diagnosis of haemangioma and cyst.For dual-contrast liver imaging, we defined a dedicated injection protocol Fig.  with a s0, CA1  is injected generating a maximal arterial enhancement of the liver at time point T1, followed by injection of CA2 at T2 . The time difference ΔT = T1 – T0 represents the period from CA injection to maximum of arterial enhancement. Sequential injection of CA1 and CA2 leads to a dual-phase dual-contrast distribution at the time point T3 = T2 + ΔT, with CA1 in the portal venous and CA2 in the arterial phase  by a 3D joint real normal distribution, as follows:The outcome of the material decomposition are three material projection datasets . The anti-correlated noise in the material images is suppressed by an iterative image based statistical de-noising algorithm . Pixel-bxi with i = {water, CA1, CA2} are the entries of i = {water, CA1, CA2} are the coordinates of the centre of the cluster for tissue type t; and i = {water, CA1, CA2} are the standard deviations of the cluster along the material axes.where: t. Thus, displaying t. The scatter plot and the likelihood representation of the decomposed material data were used to proof the lesion detection capability.Correlated noise between the material images was suppressed to a level allowing to neglect it in The material decomposition was allowed to differentiate between liver enhancement of CA1 and CA2, as shown in Figs. Cysts and haemangiomas, two typical benign liver lesions, usually present with a characteristic behaviour in arterial and portal venous phases. Fig. SPCCT images of haemangiomas reveal the typical peripheral nodal enhancement in the arterial phase, followed by a centripetal contrast filling of the lesion in portal venous phase Fig. . All thrFigure The simulated metastases with a ring-like enhancement in the arterial phase, and particularly in the portal venous phase, were clearly visible in all images, including the likelihood map, for all sizes of lesions. In addition, the corresponding scatter plots illustrate an excellent delineation of metastases and healthy liver parenchyma, without relevant overlap between the imaging features in both tissues.In this study we present our first results of an in-silico simulation of simultaneous dual-contrast multi-phase SPCCT liver imaging. A dedicated perfusion protocol was defined to simultaneously assess the arterial and portal venous distribution of two CAs. We evaluated the typical presentation of the arterial and portal venous contrast enhancement for four characteristic types of liver lesions. Further, the likelihood maps, based on the information of both CAs in different dynamic phases, illustrated areas with high probability for the respective lesion within normal liver tissue. This new dual-contrast SPCCT protocol therefore shows a potential for a clinically relevant simultaneous assessment of the arterial and portal venous contrast enhancement of liver lesions at one time point using a single SPCCT scan acquisition, together with a virtually unenhanced image. This approach goes beyond the currently possible ability of dual-energy systems, which can be used to acquire simultaneous iodine and gadolinium images , but notIn SPCCT, the x-ray photon is directly converted into an electrical pulse signal, whose amplitude is indicative for the energy of the initial x-ray photon –17. WithIn SPCCT, material decomposition delivers a set of basis images, which typically features higher noise than an integrated image. But the noise in the decomposed images is anti-correlated so that, using recent reconstruction methods, this noise can efficiently be reduced . Such deNotably, liver parenchyma receives a dual blood supply from the portal vein and hepatic artery. Normal liver parenchyma is mainly perfused via the portal vein, whereas HCCs are mostly supplied with blood from the hepatic artery. Therefore, information of perfusion patterns has an important impact on diagnostic decision-making . Thus, aWith standard single-energy CT, a differentiation between normal liver parenchyma and focal liver lesions is achieved by comparing the changes in contrast enhancement between arterial and portal venous phase. In the past, poorly aligned multi-phase CT examination protocols made it difficult to assess these changes in contrast enhancement of the same anatomic areas and post-processing techniques (including motion-correction of repetitive CT scans) were essential for reliable results of extracted perfusion parameters , 24. UsiOf note, we have used a gadolinium-based agent as first CA and an iodine-based agent as second CA. In future studies it will be necessary to address the question if this order is the preferred one or if iodine-based agent as first CA and gadolinium-based agent as second CA might be advantageous.One future perspective of our approach could be adding a delayed dynamic phase, a clinically relevant issue particularly for characterising haemangioma and HCC . While tThere are limitations of our study. First, we used numerical experiments to evaluate the imaging features in dual-contrast liver SPCCT. Although the simulations were performed using sophisticated tools and incorporated most physical effects in the SPCCT system, the findings have to be proved in an in-vivo study with a real SPCCT system in future. Second, there is currently very little clinical experience with the subsequent injection of iodine-based CA and gadolinium-based CA in humans. Therefore, pharmacological testing of potential adverse side effects will be necessary before an application of our presented contrast injection protocol can be used in patients.Third, there is a general limitation with respect to the minimum lesion size assessable with this approach, as the contrast uptake and characteristic patterns cannot be studied when the lesion becomes too small. Finally, we should consider pharmacodynamic considerations about the long-term deposition of gadolinium in patients, which presently is a subject to intense discussions in the community.In conclusion, we proved the concept of single-scan dual-CA CT as a new approach for K-edge SPCCT imaging, which exploits the spectral information for simultaneously assessing the gadolinium-based and iodine-based liver enhancement in different dynamic phases. Our simulation results have shown that we can successfully detect and visually discriminate the clinical presentation of four typical liver lesions by simultaneously evaluating unenhanced, arterial, and portal venous phases at one time point by a single scan, with a potential for dose reduction in clinical practice.


MicroRNAs (miRNA) are short nucleotides that interact with their target genes through 3′ untranslated regions (UTRs). The Cancer Genome Atlas (TCGA) harbors an increasing amount of cancer genome data for both tumor and normal samples. However, there are few visualization tools focusing on concurrently displaying important relationships and attributes between miRNAs and mRNAs of both cancer tumor and normal samples. Moreover, a deep investigation of miRNA-mRNA target and biological relationships across multiple cancer types by integrating web-based analysis has not been thoroughly conducted.MMiRNA-Viewer that can concurrently present the co-relationships of expression between miRNA-mRNA pairs of both tumor and normal samples into a single graph. The input file of MMiRNA-Viewer contains the expression information including fold changes between normal and tumor samples for mRNAs and miRNAs, the correlation between mRNA and miRNA, and the predicted target relationship by a number of databases. Users can also load their own input data into MMiRNA-Viewer and visualize and compare detailed information about cancer-related gene expression changes, and also changes in the expression of transcription-regulating miRNAs.We developed an interactive visualization tool called MMiRNA-Viewer, eight types of TCGA cancer datasets with both normal and control samples were selected in this study and three filter steps were applied subsequently. We performed Gene Ontology (GO) analysis for genes available in final selected 238 pairs and also for genes in the top 5 % (95 percentile) for each of eight cancer types to report a significant number of genes involved in various biological functions and pathways. We also calculated various centrality measurement matrices for the largest connected component(s) in each of eight cancers and reported top genes and miRNAs with high centrality measurements.To validate the MMiRNA-Viewer offers an intuitive approach for visualizing and elucidating co-relationships between miRNAs and mRNAs of both tumor and normal samples. We suggest that miRNA and mRNA pairs with opposite fold changes of their expression and with inverted correlation values between tumor and normal samples might be most relevant for explaining the decoupling of mRNAs and their targeting miRNAs in tumor samples for certain cancer types.With its user-friendly interface, dynamic visualization and advanced queries, we also believe The online version of this article (doi:10.1186/s12859-016-1219-y) contains supplementary material, which is available to authorized users. Cancer is affecting millions of lives across the world. According to the World Cancer Report, cancer rates could further increase by 50 % to 15 million new cases in the year 2020 (http://www.who.int/mediacentre/news/releases/2003/pr27/en/). The leading causes of cancer death among men are different from the leading causes of cancer death among women. Cancer occurrence also has racial/ethnic and geographic variations (http://www.cdc.gov/cancer/dcpc/data/).Cancer is a disease caused by an uncontrolled division of abnormal cells, and it can start from anywhere in the human body and spread into surrounding tissues/organs. There are more than 100 types of cancer reported (The advent of next-generation sequencing (NGS) has opened a new avenue by which, in theory, all of the limitations of traditional technology can be overcome at a reasonable cost and the underlying chromosomal structure of an individual’s DNA can be fully characterized down to the nucleotide level. Next-generation sequencing technology in cancer studies has become an effective way to provide high sensitivity and resolution in the post-genomic era.http://cancergenome.nih.gov). The Cancer Genome Atlas project provides various types of NGS sequencing data including Exome, SNP, Methylation, mRNA, miRNA, and Clinical. Moreover, sequencing data for multiple individuals of both tumor and normal samples are available for each of these cancer types [In 2006, the Cancer Genome Atlas (TCGA), a project initiated by the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI), aimed to catalogue mutations responsible for cancer. So far, more than 30 cancer types and 10 cancer tissues  have been presented for potential characterization and their DNA and RNA sequencing data are publicly accessible to the community and researchers (MicroRNAs (miRNA) are short nucleotides that interact with their target genes through 3′ untranslated regions (UTRs). MicroRNAs can at the same time target many mRNAs and fine-tune gene expression by means of cooperative or combinatorial targeting. In other words, one miRNA can at the same time target many RNAs, and many miRNAs can cooperatively target a single mRNA . In mammhsa-miR-183 was found to be expressed higher in most of the breast cancers, but lower expressed in estrogen receptor-positive breast tumors, which suggests the hsa-miR-183 plays different roles in different cancer cells [hsa-miR-183 acts as both a tumor promoter (onco-miRNA) and tumor suppressor miRNA, which depends on the type and/or subtype of cancer [It is common to attempt to describe and/or visualize miRNA-mRNA interaction networks in order to better understand their contributions to various diseases states, including cancer. Generic studies that involve normal negative correlation have been noticed. In fact, there exist more complex issues ““decoupling” like genes being either tumor promoters or suppressors depending on the tumor-type. The miRNA and mRNA pairs can fail to show negative correlation when expected, and conversion from negative to positive correlation. Specifically, a study on miRNA-mRNA network in brain regions of human alcoholics suggested that miRNAs would finally overcome the adaptive upregulation of the targeted genes and resultantly turn those initially upregulated alcohol-responsive genes to be downregulated . The hsaer cells . In a stf cancer .Furthermore, some pairs of predicted/verified miRNA and their target mRNA were found to fail to show the anti-correlation in vivo . The potMMiRNA-Tar [http://bioinf1.indstate.edu/MMiRNA-Tar) that can calculate and plot the correlation of expression for mRNA-miRNA pairs across samples or over a time course using a pre-defined correlation cutoff and prediction confidence. MMiRNA-Tar provides researchers a convenient tool to calculate the co-relationship between mRNAs and miRNAs to predict their targeting relationship. In order to facilitate effective interpretation of the important attributes and values identified for each miRNA and mRNA pair, in this study we developed a prototype of the web interface tool MMiRNA-Viewer that can concurrently render the co-relationships of mRNA − miRNA pairs in both tumor and normal samples. We also investigated the target relationship between mRNA and miRNA pairs for TCGA cancer datasets and studied their biological functions in a systematic way.We have previously developed a web interface tool iRNA-Tar  , and RNA-Seq data were generated by University of North Carolina at Chapel Hill (UNC). To make measurement units between two sequencing data sets consistent, we adopted transcripts per million (TPM) expression values for both miRNA and mRNA analyses.Every sample downloaded from TCGA contains mRNA and miRNA expression values for individual samples. We used in-house developed C programs to match patients’ tumor and normal samples in the same sample order to generate four tabular data files  for each cancer type.A customized C program was written to calculate Pearson correlation coefficient (PCC) and check three target prediction databases  values, including multiple testing for miRNA and mRNA expression files in both tumor and norm samples. The TPM was calculated for normalized expression. The average expression was used for calculating the Fold Change (FC) between tumor and normal samples. The calculated P-values and FDR values were used to select statistically significant pairs.A customized R script was written to perform normalization and calculate Transcript Per Million (TPM), Average, Median, Among 34 cancer types, 11 cancer types do not have their normal samples; One cancer type (GBM) has no tumor sample available; The mRNA and miRNA files in tumor samples for 7 cancer types do not match their counts. Two cancer types (STAD and COAD) do not match their mRNA and miRNA counts in both tumor and normal samples. There are two cancer types (PAAD and CHOL) having no common target pairs while selecting opposite expression pairs. Two cancer types (PCPG and CESC) were excluded due to the FDR cutoff values (<0.1) that we employed. The cancer type (THYM) having only two matched tumor or normal samples was also excluded from the subsequent analysis. Therefore, we obtained eight total cancer types  with complete transcriptome data available for both tumor and normal samples. 29 ambiguous (“?”) genes were excluded because of a similar reason mentioned in the study [We combined both tumor and normal results by selecting miRNA and mRNA pairs with opposite correlation values and FDR < 0.1 and predicted by at least one of three prediction algorithms. The FC in terms of expression ratio of tumor over normal was calculated for miRNAs and mRNAs.vs in normal and of the mRNAs in tumor vs in normal for eight cancer types were plotted using a customized R script.In order to compare the regulation directional change for miRNA and mRNA between tumor and normal samples within and between cancers, The fraction of upregulated, downregulated, and unchanged for miRNAs and mRNAs were calculated. The scatter plots of the miRNAs in tumor http://toreopsahl.com/tnet). The calculation of spanning tree was done using a modified method described in the paper [https://www.gnu.org/software/octave/).We used various centrality measures  to identify important mRNAs and miRNAs in tumor and normal samples for each of the eight cancers. For degree, closeness, and betweenness calculation, we used methods described in the paper  and implhe paper  and the We first processed all pairs selected for each cancer type. The connected components (groups) were created according to the available connection after removing duplicated nodes (mRNAs/miRNAs). We only studied the largest connected component in the analysis. Specifically, for each studied large connected component, edge lists were generated and tnet package were executed to calculate degree, closeness, and betweenness centrality. A customized script was designed to generate adjacency matrices and calculate Laplacian matrices and determinant of reduced Laplacian matrices. The centrality of spanning tree was calculated using the overall determinant and the values from Laplacian matrices. The implementations for the measurement of all centralities were done using R and customized C programs. All measurement results were normalized using the max values in its group. “Nodes” with positive values for most of centrality measurement metrics for each of eight cancers were selected for cancer annotation.We annotated cancer association for gene and miRNA pairs via querying different databases. Specifically, all the genes in the table were queried to get annotations of pathways using KEGG Mapper – Search Pathway , of geneSpecifically, in the KEGG Mapper – Search Pathway , the genThe annotations of genes and experimentally validated miRNAs from the above-mentioned databases were manually scrutinized, categorized, and tagged to tell whether they were related to the eight cancer types in this study. The annotations that were not related to the eight cancer types were not included. After the annotation filtering step, each cancer type that the gene and miRNA pair belongs to were classified into three categories: the cancer type was found in neither gene nor miRNA annotations(neither_exist), in either gene or miRNA annotations (either_exist), and in both gene and miRNA annotations (both_exist).We searched the Database for Annotation, Visualization and Integrated Discovery (DAVID)  for funcWe also ran ClueGo for a bigger size of gene list. This set of genes was selected according to the criteria that pairs’ correlation values to the top 5 % (95 percentile) in either tumor or normal samples in each cancer type due to the fact that the range of correlation values varies substantially among different cancer datasets.MMiRNA-Viewer for visualization. The visualization graph presented by MMiRNA-Viewer is supported by the Node JS Application (D3.js and JQuery: https//d3js.org) with browser side application prototype. The algorithm for drawing out the graph starts with the links between mRNA and miRNA pairs. Links indicate the databases that validated the connection and normal/tumor correlation. We use link color intensity to represent the number of predictions by different databases. Then nodes are drawn based on its type. Basically we use squares to represent mRNA while circles represent miRNA. Motion actions like click, drag, and double click are also attached to the nodes.Only pairs with high confidence  were uploaded into MMiRNA-Viewer can be played using the following steps:Upload input miRNA and mRNA pair data. The file uploaded to the this tool is a text file and should contain expression correlations between mRNA and microRNA, mRNA and microRNA normal/tumor P and FDR values, Number of Databases that validated the connection and Normal/Tumor correlation, and Fold Changes values for miRNA and mRNA pairs.Search and filter miRNA and mRNA pairs. Users can search for a specific node in the graph by inserting the gene name in the search box. After inputting an mRNA or microRNA name, the user can click the search button to center its position in the graph. The ID search is case-sensitive. Additionally, there are various filters that can be applied to filter data at will. For example, when users select Node Filter as “mRNA” and Connections Filter as “>10”, then only the nodes representing mRNA with connected nodes greater than 10 will be highlighted in the graph.Show miRNA and mRNA pair data. Users can click on two nodes that are connected with each other to get the annotation values in normal and tumor samples, which are directly displayed in the table right below the “Filters”. Users can collapse and expand the legend on the top right corner in the graph by clicking the legend icon.The MMiRNA-Viewer, we compared our MMiRNA-Viewer with CrossHub [To demonstrate merits of the co-relationship for mRNA-miRNA calculated by CrossHub , a tool The number of cancer and normal samples downloaded from TCGA for each cancer type are listed in Table Upon excluding cancer types that do not have matched miRNA and mRNA samples and running customized expression calculation and database prediction scripts, the filtered expression data for the eight selected cancer types are generated. We obtained 14,505 total miRNA and mRNA pairs  which met the statistical cutoff criteria  for eight cancer types . The nodes are selected genes and miRNAs in the largest group for each cancer. In LUSC’s case, there are three groups with node size greater than 20. A connection topology for one of the top clusters with 42 “nodes” in LUSC is shown in Fig. The centrality scores of genes and miRNAs based on various matrix measurement for the largest connected component of eight cancer types were calculated and shown in Additional file FGFR3) and hsa-miR-100 in the BLCA. FGFR3 and hsa-miR-100 pair in BLCA have been identified by this approach and both of them were reported as the bladder cancer gene and miRNA. In other words, in the BLCA cancer dataset, the top negatively correlated gene and miRNA in expression values were both annotated to be related to the cancer BLCA in the above-mentioned databases. Specifically, FGFR3 gene is reported to be involved in Bladder cancer based on the result (hsa05219) from the KEGG pathway mapping database [hsa-miR-100 leads to upregulation of FGFR3 before its mutation. Therefore, literature provide the support that our bioinformatics pipeline can detect such pairs with the opposite regulation between mRNAs and miRNAs. Literature search results associated with cancers for other pairs which are reported here to have opposite FC values between mRNAs and miRNAs and inverse correlations between tumor and normal samples are shown in Additional file When looking at the gene and miRNA cancer association, the results revealed one hit of “both_exist”, 135 hits of “either_exist”, and 102 hits of “neither_exist”. The both_exist gene and miRNA pair is fibroblast growth factor receptor 3  across cancer types, namely appearing in more than two different cancer types. There is one gene node across four cancer types.hsa-miR-203 was decreased in esophageal adenocarcinoma compared to paired adjacent mucosa [hsa-miR-221 was downregulated in prostate cancer [hsa-miR-222 was upregulated in anaplastic thyroid carcinoma [hsa-miR-182 was upregulated in the esophageal cancer [hsa-miR-183 was upregulated in the metastatic breast cancer [hsa-miR-21 was upregulated in the gastric cancer [hsa-miR-629 that was functionally inhibited could suppress motility and invasion of the clear cell renal cell carcinoma [hsa-miR-106b was downregulated in the metastatic pancreatic cancer [hsa-miR-1266 was significantly decreased in expression in gastric cancer tissues [hsa-miR-145 was downregulated in laryngeal squamous cell carcinoma [hsa-miR-378 was downregulated in cutaneous squamous cell carcinoma [hsa-miR-454 was downregulated in osteosarcoma [hsa-miR-484 was upregulated in expression in the serum samples of early breast cancer patients [hsa-miR-625 was upregulated in bile duct cancer [hsa-miR-940 was downregulated in hepatocellular carcinoma tissues and cell lines [There are 3 miRNA nodes across 7 cancer types. The t mucosa ; the hsae cancer ; hsa-miRarcinoma . There al cancer . The hsat cancer . The hsac cancer . The hsaarcinoma . There ac cancer . The hsa tissues . The has tissues . The hsaarcinoma . The hsaarcinoma . The hsapatients . The hsat cancer . The hsaWe searched the Database for Annotation, Visualization, and Integrated Discovery (DAVID)  for funcWe used Cytoscape ClueGO plugin to do the GO enrichment of the 32 files of the top 5 % expression correlation coefficient of different levels at Normal High (NH), Normal Low (NL), Tumor High (TH), Tumor Low (TL) genes of eight cancers. Only BLCA, HNSC, KICH, KIRP, LIHC, and THCA have GO enrichment results. BLCA GO terms were only found in TL dataset, so we only used HNSC, KICH, KIRP, LIHC, and THCA to discover GO terms that would be shared by NH and TL or by NL and TH in each of the five cancers.The GO terms shared by NH and TL or by NL and TH in HNSC, KICH, KIRP, LIHC, and THCA were denoted by Venn diagrams . An interface screenshot of MMiRNA-Viewer is shown in Fig. We have developed a prototype visualization tool -MMiRNA-Viewer is available at http://bioinf1.indstate.edu/MMiRNA-Viewer.MMiRNA-Viewer, it took CrossHub 9 min to calculate correlation coefficient values for 1836 pairs. The average value of absolute difference between two methods is ~0.07. The calculated correlation values by two methods are shown in Additional file When compared to a short running time (less than one minute) using MMiRNA-Viewer to upload input data files and visualize the results in an intuitive way that user can quickly locate their interested pairs for further functional study. The current version has many interesting features, but its functionalities can be further expanded. For instance, we would like to incorporate other functionalities with publicly available literature search and pathways mapping study.In this study, we developed a web-based tool Our study assumed that the tumor is activated via mRNAs mutation directly targeted by miRNAs. Results that miRNAs and mRNAs are inversely correlated exist in 238 selected pairs for eight studied cancers. Our protocol that inversely correlated miRNA and mRNA pairs should be oppositely regulated in tumor samples could be useful for prioritizing cancer associated pairs.MMiRNA-Viewer were generated using TCGA cancer sequencing data (Level 3) to compute the correlation coefficients and target relationships for miRNA and mRNA pairs between tumor and normal samples using three state-of-art database prediction algorithms. We took FDR cutoff (<0.1) to select significantly correlated miRNA and mRNA pairs in the initial step so that more pairs potentially associated with cancers through inverse correlation could be included. Under the assumption that miRNA and mRNA pairs are often inversely correlated and their FC values should be opposite between tumor and normal samples, we obtained 238 pairs for GO biological function and pathway studies.Current example input files for We employed a modified spanning tree centrality method for calculation. We have found that due to the definition of spanning tree, some nodes have pre-determined values of simply 1 and 0 and thus are not very interesting and can be predicted. This does help to calculate the result easier as we can remove some nodes and still generate the exact results for all nodes that cannot be predicted, thus increasing speed and precision of the calculation. We can then go back and fill in or modify the predictable values. Further, we have introduced a method to modify the value of the 1 s to better reflect their actual centrality while still using the spanning tree method as a back bone. For KIRP cluster, we used an altered approach for the calculation of spanning tree due to the large number of connections in the cluster. Specifically, the algorithm first found the most distant point from each “node” (gene or miRNA), then broke the nodes into two groups and removed branches from each two halves to calculate adjusted spanning tree values. Finally, two sets of results were merged according to original connections to report final spanning tree values.P-values and FDR of the calculated correlation coefficients and using the above-mentioned 3-database matching, CrossHub, doesn’t filter out the calculated correlation coefficients of miRNAs and mRNAs via their reported P-values, via unreported FDR of their correlation coefficients, and via their reported miRNA-mRNA targeting databases. The two programs are basically consistent with respect to the calculation of the expression correlation coefficients of the miRNA-mRNA in the same dataset (HNSC) in TCGA. The slight difference of calculated correlation coefficient values might be due to the fact that CrossHub adopted read number mapped to each genes, whereas MMiRNA-Viewer uses TPM, so the mapping process might cause differences. In CrossHub pipeline, “By default, CrossHub performs the analysis for top 30 overexpressed microRNA with read counts  from 20,000 to 4,000,000. These miRNA represent the most important fraction in the context of biological regulation”. In addition, the memory usage of CrossHub is huge and running time is quite long.Unlike our algorithm that filters out the pairs using MMiRNA-Viewer that provides a user interface for various cancer types of miRNA-mRNA expression data with significant interaction pairs. Our MMiRNA-Viewer supports dynamic queries through intuitive user interactions to help users search meaningful cancer biological findings. We also suggested that miRNA and mRNA pairs with opposite FC values of their expression and with inverted correlation values between tumor and normal samples might be potential pairs to be responsible for transcription decoupling for certain cancer types.We developed an intuitive graph visualization tool


It serves to mitigate cellular stress and to provide metabolic precursors especially upon starvation. Thereby, autophagy can support the survival of cancer cells. In addition, there is now convincing evidence showing that under certain conditions autophagy can also foster cell death. This dual function of autophagy is also relevant upon anticancer treatment, as many chemotherapeutic agents engage autophagy. A better understanding of the molecular mechanisms that are critical for mediating autophagic cell death in cancer cells will be instrumental to selectively interfere with this cellular program in order to increase the cancer cell’s response to cytotoxic drugs. This review illustrates how anticancer drug-induced autophagy is involved in mediating cell death.Autophagy represents a catabolic program involved in the degradation of cellular components  In apoptosis-deficient cancer cells, gossypol has been reported to induce ACD , which is considered as the main active component of cannabinoids, has been shown to act as a stimulus for ACD, for example, in hepatocellular carcinoma (HCC) and glioblastoma , 29. Knoin vivo . These svia accumulation of ceramide and phosphorylation of eukaryotic translation initiation factor 2 alpha, resulting in upregulation of CHOP and tribbles homolog 3 (TRB3), two ER stress-related proteins  has been shown to stimulate autophagy-associated cell death accompanied by ultrastructural changes in autophagosome formation and increased lipidation of LC3 . PharmacIn HeLa cervical carcinoma cells, SAHA has been reported to induce characteristic autophagic features including morphological changes and LC3-II conversion . GeneticIn HCC, HDACIs including SAHA and OSU-HDAC-42 have been described to trigger ACD based on both genetic- and pharmacological blocking experiments underscoring that SAHA- or OSU-HDAC-42-stimulated autophagy is required for the induction of cell death, as either silencing of ATG5 or 3-MA protected cells from the cytotoxicity of SAHA . Also, ain vivo model. ACD was emphasized by genetic knockdown of ATG7 that significantly rescued combination treatment-induced cell death. The authors went on to show that IM and TIC increase the autophagic flux by upregulating 3′-5′-cyclic adenosine monophosphate (cAMP) levels via distinct mechanisms. While IM treatment activates adenylate cyclase and induces cAMP-mediated autophagy, the addition of the P2Y12 inhibitor TIC short circuits the ADP/ATP-induced feedback inhibition of adenylate cyclase (The tricyclic antidepressant (TCA) imipramine (IM) and the anticoagulant ticlopidine (TIC), two drugs approved by the US Food and Drug Administration, have been shown to synergistically trigger autophagy and cell death in glioblastoma cells . In addi cyclase . TogetheThere is ample evidence showing that some cytotoxic drugs used for the treatment of cancer can engage ACD. Since this property can in principle be exploited for cancer therapy, it is critical to understand the pathways regulating these events. However, as autophagy can control both cell death and survival programs, induction of autophagy in cancer cells represents a double-edged sword. It will therefore be critical to develop novel approaches that will allow selective engagement of the pro-death branch of autophagy.SF has solely contributed to the conception and design of the work, has drafted and revised the work, and has given final approval of the version to be published.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.