The platelet DGs and AGs are regarded as being budded from the endosomes and the trans-Golgi network (TGN), respectively, and then matured from multivesicular bodies (MVBs). However, the sorting machineries between DGs and AGs are different. Inherited platelet disorders are associated with deficiency of DGs and AGs, leading to bleeding diathesis in patients with Hermansky–Pudlak syndrome (HPS), gray platelet syndrome (GPS), and arthrogryposis, renal dysfunction, and cholestasis syndrome (ARC). Here, we reviewed the current understanding about how DGs differ from AGs in structure, biogenesis, and function. In particular, we focus on the sorting machineries that are involved in the formation of these two types of granules to provide insights into their diverse biological functions.Platelets respond to vascular injury via surface receptor stimulation and signaling events to trigger aggregation, procoagulant activation, and granule secretion during hemostasis, thrombosis, and vascular remodeling. Platelets contain three major types of secretory granules including dense granules , α-granules (AGs), and lysosomes. The contents of platelet granules are specific. Platelet DGs store polyphosphate and small molecules such as ADP, ATP, Ca The fundamental function of circulating platelets is to form aggregates that are adhered to the injured vessel wall to prevent bleeding . Platelehosphate . Platelehosphate .NBEAL2, while platelets from ARC patients have loss-of-function mutations in vacuolar protein sorting 33 homolog B (VPS33B) or VPS16B. These studies suggest that NBEAL2, VPS33B, and VPS16B are involved in AG biogenesis and function [HPS1–10 and CHS1, respectively, which encode proteins HPS1, adaptor protein (AP-3) β3A, HPS3, HPS4, HPS5, HPS6, Dysbindin, BLOS3, Pallidin, AP-3 δ, and LYST [Previous studies have shown that deficiency or absence of AGs is associated with two inherited platelet disorders: gray platelet syndrome (GPS) and arthrogryposis, renal dysfunction, and cholestasis syndrome (ARC). Further studies revealed that platelets from GPS patients have loss-of-function mutations in function . DG is afunction . The blefunction . HPS is function . HPS andand LYST ,15. Thesand LYST . The undand LYST . Severaland LYST . Based oThe initial findings about AG structure were based on thin section EM. In normal circulating platelets, AGs are the most abundant platelet granules, numbering approximately 50–80 per cell . AGs areIn comparison with the number of AGs in platelets, DGs are much less. Normally, each human platelet contains only three to eight DGs with 200–300 nm in diameter . DGs, wiPlatelets are derived from MKs through the extending cytoplasmic proplatelets via processes involving microtubules and dynein . During trans-Golgi network (TGN) or the plasma membrane and then are directed to multivesicular bodies (MVBs)/late endosomes (LEs) [AG development involves trafficking and sorting of proteins mediated by vesicles that bud from the membranes of one cellular compartment and fuse with another compartment . Using ues (LEs) . In MKs,VPS33B, a novel Sec1/Munc18 protein, lead to ARC syndrome [VPS33B mutations detected no VPS33B protein expression in their fibroblasts by immunoblotting. Consequently, platelet AGs were completely absent from ARC syndrome platelets. In addition, soluble AG cargos including platelet factor 4 (PF4), vWF, β-thromboglobulin, thrombospondin 1, endocytosed FGN, and membrane-bound P-selectin could not be detected in platelets [VPS16B mutation revealed a complete loss of AGs. Soluble and membrane-bound AG proteins were reduced or undetectable, suggesting that both releasable and membrane-bound AG constituents were absent. Stable expression of GFP-VPS16B in Dami cells showed that VPS16B colocalized with AGs, late endosomes, and TGN, indicating that VPS16B, together with its binding partner VPS33B, is essential for AG biogenesis in MKs and platelets [The study of molecular pathogenesis underlying GPS and ARC syndrome provides insights into AG biogenesis. Mutations in syndrome . In wildlatelets . These olatelets . ARC synlatelets .fl/fl-ERT2Vps33b, the authors found a marked reduction in AG counts and the presence of small granule-like structures in platelets by phenocopying the platelet phenotypes in ARC patients. Analysis of bone marrow-derived MKs from fl/fl-ERT2Vps33b mice revealed a reduction in mature MVB II and an accumulation of large vacuoles, which may result from mis-sorting of proteins during trafficking. Very less cargo protein such as vWF was transported from MVB I to MVB II [The function of VPS33B in AG trafficking has been confirmed in a mouse model . By geneo MVB II , suggestNBEAL2, which encodes neurobeachin-like 2 protein, lead to GPS [−/−Nbeal2 mice, vWF initially appeared within small vesicles near the Golgi that failed to mature into AGs and were released into the demarcation membrane system  instead process ,36. In NAlthough VPS33B, VPS16B, and NEBAL2 are implicated in AG biogenesis, the detail mechanisms of how they regulate AG biogenesis remain poorly understood. It has been suggested that both VPS33B and VPS16B are involved in protein sorting and trafficking, which is required for delivery of endocytosed cargos to lysosomes. The VPS33B–VPS16B complex is essential for late endosome-lysosome fusion and endosomal recycling . VPS33B–DGs, as a member of LRO ,17, sharThe AP-3 complex was originally identified by its homology with the clathrin-associated AP complexes AP-1 and AP-2, which are involved in vesicle trafficking ,43. AP-3Other machineries in regulating DG biogenesis by sorting cargos from endosomes are the BLOC complexes including BLOC-1, BLOC-2, and BLOC-3. BLOC-1 is a heteromeric complex composed of eight subunits: BLOS1 (BLOC1S1), BLOS2 (BLOC1S2), BLOS3 (BLOC1S3), Cappuccino (BLOS4 or BLOC1S4), Muted (BLOS5 or BLOC1S5), Pallidin (BLOS6 or BLOC1S6), Snapin (BLOS7 or BLOC1S7), and Dysbindin (BLOC1S8 or DTNBP1) ,52,53. BOther factor that may be involved in platelet dense granule biogenesis is VPS33A, a subunit of HOPS complex . HOPS co2+ [2+ by ‘kiss-and-run’ events during which two DGs make transient physical contacts and then move away from each other. During these events, DGs exchange contents and may play a role in DG maturation. TPC2 also regulates the formation of membrane tubules connected to DGs [DG contains serotonin, calcium, pyrophosphate, and a non-metabolic adenine nucleotide pool of ADP and ATP which play pivotal role in platelet activation. There is no evidence to show soluble protein cargos in DG lumen. It is suggested that the transporters are involved in their enrichment in DG lumen. Except for the constitutive membrane proteins of DGs, ions play important roles in DG biogenesis and function. Two-pore channel 2 (TPC2) is a component of the DG membrane that regulates the organelle luminal pH and the pool of releasable Ca2+ . TPC2 red to DGs . These f2+ release from DGs. Along with the increasing Ca2+ concentration, cAMP concentration decreases and a series of protein kinases such as Src kinase and protein kinase C (PKC) are activated, which in turn induces the release of DG contents, ADP and serotonin, to accelerate the activation and aggregation of platelets to form a hemostatic plug [Platelet AGs and DGs are both necessary and critical for hemostasis and thrombosis, but the functions of these two granules are different ,24. Oncetic plug .The deficiencies of AGs and DGs in human genetic disorders manifest with prolonged bleeding, but the phenotypes vary in AG and DG abnormalities. AGs play a pivotal role for normal platelet function as inferred from that ARC syndrome and GPS patients have bleeding diatheses with AG deficiency ,66. HoweHPS genes in humans, and mutations in at least 15 genes (including orthologs of those ten known HPS genes) cause a similar disorder in mice, especially the HPS phenotype in the buff mice with VPS33A mutation [CHS1 gene. Due to DG deficiency and multiple defects of other LRO, patients suffering from CHS have bleeding diathesis as well as decreased pigmentation and severe immune deficiency [The functions of DGs are independent of AGs as the number of DG is increased in VPS33B-ARC platelets and the absence of VPS16B does not diminish platelet DGs ,11. DG bmutation ,67,68. Imutation . CHS is ficiency . Mutatioficiency ,70. The We have learned a lot from platelet granule biogenesis by studying the inherited platelet granule deficiencies . From pa


Guidelines recommend integrating hypertension screening for HIV-infected adults, but blood pressure measurements may be dynamic around the time of HIV testing.We measured a seated resting blood pressure in adults (≥18 years) prior to HIV testing, and again after receiving HIV test results, in an ambulatory HIV clinic in KwaZulu-Natal, South Africa. We assessed sociodemographics, smoking, body mass index, diabetes, substance abuse, and anxiety/depression. We used blood pressure categories defined by the Seventh Joint National Committee (JNC 7) classifications, which includes normal, pre-hypertension, stage 1 hypertension, and stage 2 hypertension.3 had a 44% lower odds of hypertension , as compared to adults with CD4 >200 cells/mm3. The mean arterial blood pressure was 6.5 mmHg higher among HIV-infected adults after HIV testing (p <0.001).Among 5,428 adults, mean age was 31 years, 51% were male, and 35% tested HIV-positive. Before HIV testing, 47%  had a normal blood pressure, 40%  had prehypertension, and 10% (569) had stage 1 or 2 hypertension. HIV-infected adults had significantly lower blood pressure measurements and less hypertension, as compared to HIV-negative adults before HIV testing; while also having significantly elevated blood pressures after HIV testing. In a multivariable model, HIV-infected adults had a 30% lower odds of hypertension, compared to HIV-uninfected adults . In a separate multivariable model, HIV-infected adults with CD4 ≤200 cells/mmHIV-infected adults experienced a transient blood pressure increase after receiving HIV results. Blood pressure measurements may be more accurate before HIV testing and repeated blood pressure measurements are recommended after ART initiation before formally diagnosing hypertension in HIV-infected adults. Cardiovascular disease (CVD) is a leading cause of mortality worldwide, and a leading cause of HIV/AIDS-related mortality ,2. As moSimilar to the general population, HIV-infected adults should be routinely screened for hypertension, as treatment could be integrated within HIV care ,14. In aCurrently, there is limited information and guidance on how HIV-infection and associated immunosuppression influences hypertension screening result, and whether blood pressure measurements after receiving an HIV diagnosis causes transient blood pressure changes. Therefore, we sought to understand the association between HIV infection, hypertension, and blood pressure variability among South African adults accessing HIV testing services in a poor urban township. Since hypertension screening routinely occurs after HIV testing, the goal of this study was to determine the degree to which blood pressure measurements and hypertension screening are dynamic around the time of HIV testing in South Africa.We conducted a study among adults presenting for voluntary HIV counseling and testing in the outpatient department of the iThembalabantu People’s Hope Clinic (IPHC) in the Umlazi township of South Africa from September 2013 to April 2017. The IPHC tests adults for HIV and provides free clinic- and community-based HIV care and treatment for over 10,000 HIV-infected patients. We enrolled English or Zulu speaking adults ≥18 years of age, who presented to the clinic for HIV testing and were willing and able to provide written informed consent for study participation. We excluded patients known to be pregnant. All participants provided written, informed consent in either English or Zulu. The study was approved by the institutional review board of the University of Washington in Seattle (IRB #49563) and the Medical Research Ethics Committee of the University of KwaZulu-Natal in Durban (Protocol #BF052/13).The study team enrolled eligible participants prior to HIV testing and completed a questionnaire with demographic, socioeconomic, and mental health questions. All participants were asked about any recent (within 1 month) or prior (>1 month) use for smoking, alcohol use, intravenous drug use, and cannabis use. Within the baseline questionnaire, before HIV testing, we assessed general anxiety using the standardized generalized anxiety disorder 7-item (GAD-7) scale , and depAfter blood pressure measurement, all participants were tested for HIV infection using a rapid fingerprick test by an HIV counselor. All positive tests were confirmed with a second rapid test, and participants received pre- and post-test counseling. Only HIV-infected participants were subjected to additional clinical evaluations, including a repeat blood pressure measurement, and blood tests. Participants who tested HIV-negative were advised to return in several months for repeat HIV screening.Among HIV-infected participants, a research nurse administered a clinical questionnaire and obtained anthropometric measurements using standard procedures. Body weight was measured to the nearest 0.5 kg with the participant in light clothing and using a standardized scale . Height was measured to the nearest 0.5 cm using a standiometer with participants wearing no shoes. At the end of the clinical visit and after at least 10 minutes of rest, another seated blood pressure measurement was obtained. All HIV-infected participants had a CD4+ T-cell count, which was performed at the National Health Laboratory Service lab at Prince Myshenyi Hospital using FACS Calibur System . All HIV-infected participants received routine HIV medical care, including CD4 count testing and initiation of ART, according to current South African guidelines .The primary outcome in this analysis was blood pressure, and we used the hypertension categories from the Seventh Joint National Committee (JNC 7) , which w2), and we used the following standardized definitions: overweight was BMI 25.0–29.9 kg/m2 and obesity was BMI ≥30 kg/m2 [Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters  with 95% confidence intervals (CIs). Because receiving positive HIV status results might artificially elevate patient blood pressure readings, blood pressure measurements taken before HIV testing were used for all analyses. In the multivariable models, variables were selected using a backwards selection approach, and any primary exposure of interest was added after the model was completed. All multivariable analyses were adjusted by age and sex. We calculated 95% confidence intervals (CI), reported two-tailed p-values (α = 0.05), and used SAS 9.4 .The funder of the study  had no role in study design, data collection, data analysis, data interpretation, or writing of the report.3 (interquartile range: 162–481 cells/mm3).We enrolled 5,618 participants, and excluded 190 participants from the analysis who did not have complete blood pressure measurements . Among t3. However, 7.4% of HIV-infected adults with CD4 ≤200 cells/mm3 had stage 1 or 2 hypertension. Among HIV-infected adults with CD4 >200 cells/mm3, 10.7% had either stage 1 or 2 hypertension.The mean SBP was 118 ±15 mmHg, mean DBP was 72 ±16 mmHg, and mean MAP was 87 ±14 mmHg . The meaAmong HIV infected participants, blood pressure measurements were significantly higher after participants received their positive HIV test results . On aver3.We compared baseline characteristics between normotensive and hypertensive participants among the entire cohort and separately for HIV-infected adults. Among the entire cohort, several characteristics, including older age, male sex, being married, and having more children, were all significantly associated with hypertension. In addition, having anxiety, more alcohol use, and more cannabis use were also associated with more hypertension. Among HIV-infected adults, older age, being married, and having more children were similarly associated with hypertension. In addition, we observed a higher prevalence of hypertension among obese participants and adults with CD4 above 200 cells/mmIn univariate analyses among the entire cohort, the risk factors for hypertension were older age, male sex, being married, having >1 child, having current employment, having a higher income, having more anxiety, more alcohol use, and more cannabis use . In a mu3 was associated with significantly lower rates of hypertension, as compared to participants with a CD4 >200 cells/mm3. Multivariable analyses among HIV-positive adults suggest that age, anxiety, and CD4 count are independently associated with hypertension. After adjusting for age and anxiety, CD4 count ≤200 cells/mm3 was found to be associated with 44% lower odds of hypertension compared to CD4 >200 cells/mm3 . In sub-analyses, participants who had no prior HIV testing did not have a higher prevalence of hypertension, as compared to participants who previously tested HIV-positive.Among HIV-infected adult, risk factors for hypertension in univariate analyses included older age, being married, having >1 child, having current employment, having anxiety, more cigarette smoking, more cannabis use, a high BMI, and higher CD4 count . A CD4 c3) were associated with significantly lower baseline rates of hypertension, when adjusted for other contributing factors. Importantly, HIV-positive adults experienced a significant transient increase in blood pressure after receiving an HIV+ test result. Our results demonstrate that blood pressure measurements are dynamic after HIV testing, suggesting that hypertension screening should ideally occur before HIV testing and repeated measures are necessary after ART initiation before formally diagnosing hypertension in HIV-infected adults. These findings should help inform ongoing efforts to integrate non-communicable disease screening with HIV care and treatment in resource-limited settings.In this cross-sectional study of ART-naïve South African adults, 10.2% had either stage 1 or 2 hypertension. HIV infection and immunosuppression Click here for additional data file.


Burkholderia pseudomallei HNBP001, an epidemic strain isolated from a melioidosis patient with pneumonia in Hainan, China.Here, we report the complete genome sequence of  Burkholderia pseudomallei HNBP001, an epidemic strain isolated from a melioidosis patient with pneumonia in Hainan, China.Here, we report the complete genome sequence of  Burkholderia pseudomallei is a Gram-negative bacterium that causes melioidosis, a serious human and animal infection commonly reported in parts of Africa, South America, and Asia  agar plate with gentamicin for 24 h at 37°C (https://www.broadinstitute.org/gatk/), SOAPsnp  with 3,807 protein-coding sequences, 6 rRNA genes, and 45 tRNA genes. Chromosome 2 is 3,363,129 bp in size  with 3,342 protein-coding sequences, 6 rRNA genes, and 14 tRNA genes. These numbers are similar to those of previously published genome annotations of B. pseudomallei  and CP038806 (chromosome 2). The raw data were deposited in the Sequence Read Archive (SRA) for the PacBio RS II (SRA number SRR9027110) and Illumina (SRA number SRR9691870) read data.The finished annotated sequences of the two chromosomes of


TET mRNA expression in a well-characterized dataset of 117 matched pairs of HNSCC tissues and normal tissues. 5-hmC levels and TET mRNA expression were examined via enzyme-linked immunosorbent assay and quantitative real-time PCR, respectively. 5-hmC levels were evaluated according to various clinical characteristics and prognostic implications. Notably, we found that 5-hmC levels were significantly correlated with tumor stage (P = 0.032) and recurrence (P = 0.018). Univariate analysis revealed that low levels of 5-hmC were correlated with poor disease-free survival . The expression of TET family genes was not associated with outcomes. In multivariate analysis, low levels of 5-hmC were evaluated as a significant independent prognostic factor of DFS . Taken together, our findings showed that reduction of TET family gene expression and subsequent low levels of 5-hmC may affect the development of HNSCC.Ten-eleven translocation (TET) enzymes are implicated in DNA demethylation through dioxygenase activity, which converts 5-methylcytosine to 5-hydroxymethylcytosine (5-hmC). However, the specific roles of TET enzymes and 5-hmC levels in head and neck squamous cell carcinoma (HNSCC) have not yet been evaluated. In this study, we analyzed 5-hmC levels and  Head and neck squamous cell carcinomas (HNSCCs) are heterogeneous diseases that involve multiple sites and cellular origins within the upper aerodigestive tract Enzymes of the ten-eleven translocation (TET) family catalyze the stepwise oxidation of 5-methylcytosine (5-mC) in DNA to 5-hydroxymethylcytosine (5-hmC) and further oxidation products, not only generating new epigenetic marks but also initiating active or passive demethylation pathways TET genes are present in nearly all solid tumor types at a relatively low frequency TET1, TET2, and TET3 mutations were identified in nine (1.8%), eight patients (1.6%), and eight patients (1.6%) of 510 patients, respectively TET mRNA is downregulated in HNSCC owing to DNA methylation; this may be a critical event in HNSCC progression. In particular, TET3 methylation confers HNSCC with unique clinicopathological features Missense and truncating mutations in TET genes and 5-hmC are associated with tumorigenesis in different types of cancers TET genes are important for predicting tumorigenesis and biological behaviors and for the development of future targeted therapies for HNSCC. However, systematic studies of the epigenetic and transcriptional regulation of 5-hmC and TET genes in HNSCC are still needed.Recent studies have shown that aberrant levels of Accordingly, in this study, we compared the 5-hmC profiles between normal mucosa and HNSCC tissues and characterized the associations between 5-hmC and HNSCC tumorigenesis, progression, and outcomes.In total, 117 primary HNSCC samples were obtained from patients during surgery at the Department of Otolaryngology, Hamamatsu University School of Medicine. All patients provided written informed consent, and the study protocol was approved by the Institutional Review Board of the Hamamatsu University School of Medicine . Clinical information, including age, sex, alcohol exposure, smoking status, tumor size, human papilloma virus (HPV) status, tumor size, lymph node status, stage, and recurrence, were obtained from the patients' clinical records.The genomic DNA from 117 primary tumors and noncancerous mucosa was extracted using a QIAamp DNA Mini Kit  according to the manufacturer's instructions. The 5hmC content of genomic DNA was determined with a Quest 5-hmC DNA ELISA Kit , according to the manufacturer's instructions. Assays were performed using 4 μg/mL anti-5-hmC polyclonal antibodies, loading 200 ng of DNA per well. Absorbance at 430 nm was evaluated using a SynergyH1 microplate reader and Gen5 software . The amount of 5-hmC was calculated as a percentage based on a standard curve generated using kit controls.TET1, TET2, TET3, and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were measured via qRT-PCR using SYBR Premix Ex Taq  and a Takara Thermal Cycler Dice Real Time System TP8000 (Takara). The data were analyzed using the ΔΔCt method. Primer sequences were as follows: TET1 forward (F), CCCTTGGAAATGCCATAGGAA; TET1 reverse (R), GAGAGCCTGCTGGAACTGTTG; TET2 F, GGCTGTTGGCCAGAGACTTA; TET2 R, ATACCTGTAGGTGTTTGCCTGTTTA; TET3 F, GCCAACTTCAACATACCCTGGAC; TET3 R, CACCTGGATGTGGGACTGTGTAA; GAPDH F, GCACCGTCAAGGCTGAGAAC; GAPDH R, TGGTGAAGACGCCAGTCTCTA.Total RNA was isolated using an RNeasy Plus Mini Kit (Qiagen), and cDNA was synthesized using a ReverTra Ace qPCR RT Kit . The mRNA levels of TET mRNA levels and all patients for comparisons between tumor and normal tissues. DFS was measured from the date of the initial treatment to the date of diagnosis. Kaplan-Meier tests were used to calculate survival probabilities, and log-rank tests were used to compare survival rates. The prognostic value of methylation status was assessed by performing multivariate Cox proportional hazards analysis adjusting for age (≥ 65 versus < 65 years), sex, smoking status, alcohol intake, and tumor stage . A p-value less than 0.05 was considered statistically significant. Statistical analyses were performed using StatMate IV software  and the Stata/SE 13.0 system .The 5-hmC and TET mRNA levels in tumors and normal mucosa and patient characteristics were analyzed statistically. Receiver-operator characteristic (ROC) curve analyses were performed for 5-hmC and P < 0.001 by paired t-tests). Notably, the 5-hmC levels exhibited highly discriminative ROC curve profiles, which clearly distinguished HNSCC from normal mucosal tissues (area under the ROC [AUROC] = 0.612). At the cutoff value of 0.407, the sensitivity and specificity were 57.3% and 64.1%, respectively  than matched normal mucosa . Tumor samples were classified as positive when the mRNA expression levels exceeded 0.580, 0.102, and 1.866 for TET1, TET2, and TET3, respectively. The cutoff mRNA expression level was chosen from the ROC curve to maximize sensitivity and specificity  was performed to examine mRNA expression of TET genes, including TET1 , TET2 , and TET3  . The 5-hmC level showed the greatest increase when all three TET genes showed high expression , oral cavity (P = 0.029), and hypopharynx (P = 0.009) cancer  and recurrence (P = 0.018). Other clinical information, including age, sex, alcohol exposure, smoking status, tumor size, HPV status, tumor size, and lymph node status, was not related to 5-hmC levels. Smoking habit was associated with mRNA expression of TET1 (P = 0.031) and TET2 (P = 0.040). Other clinical information was not related to TET1, TET2, and TET3 mRNA expression , TET2 , and TET3  among the 117 patients enrolled in this study , the adjusted risk ratio for recurrence (RR) was 2.352 . 5-hmC levels correlated positively with recurrence in patients with T3 and T4 tumor stages and positive lymph node metastasis (RR, 4.33; 95% CI, 1.62-11.5; P = 0.003 and RR, 3.38; 95% CI, 1.18-9.65; P = 0.023, respectively; Figure The associations of the risk of recurrence with 5-hmC levels and C levels 4.1%, theTET family gene levels in HNSCC. DNA methylation regulates epigenetic gene inactivation; however, the factors affecting DNA demethylation are still poorly understood in HNSCC. Recently, we showed that concurrent methylation analysis of TET genes was related to reduced DFS in unfavorable event groups TET genes and altered levels of 5-hmC were associated with tumorigenesis and that lower 5-hmC levels were correlated with reduced survival.This is the first study examining 5-hmC and  TET1 gene further increases 5-mC levels in tumor cells, thus forming a DNA methylation feedback loop mediated by DNMT and TET1 Loss of 5-hmC is associated with decreased expression of TET1 and TET2 in small intestinal neuroendocrine tumors 5-hmC is not simply an activating epigenetic mark, but is considered an intermediate in the active demethylation pathway and appears to play complex roles in gene regulation Bisulfite treatment, the gold-standard technology for detection of DNA methylation, results in the conversion of unmethylated cytosine into uracil, which will be read as thymine after PCR amplification, with both 5-mC and 5-hmC being read as cytosine, cannot distinguish between 5-mC and 5-hmC In summary, we demonstrated for the first time that 5-hmC levels were abnormally reduced in patients with HNSCC; this may be a critical event in HNSCC progression. Interestingly, the 5-hmC profiles in primary tumors may be used to identify patients with positive lymph node metastasis and high tumor stage that are at a higher risk of recurrence. Further studies are needed to examine the differences in global demethylation patterns observed between 5-hmC-low and -high tumors and their effects on the onset and progression of HNSCC in more detail.Supplementary figure and table.Click here for additional data file.


CD44, KRT6A, CEACAM5, SERPINB2, and down-regulated LTF and MUC5B) were identified and should be considered as new biomarkers. Pathway cross-talk analysis highlights that signaling pathways mediated by IL-4/13 and transcription factor HIF-1α and FOXA1 play crucial roles in the pathogenesis of asthma. Interestingly, three chemicals, polyphenol catechin, antibiotic lomefloxacin, and natural alkaloid boldine, were predicted and may be potential drugs for asthma treatment. Taken together, our findings shed new light on the common molecular pathogenesis mechanisms of asthma and provide theoretical support for further clinical therapeutic studies.Asthma is a common chronic airway disease worldwide. Due to its clinical and genetic heterogeneity, the cellular and molecular processes in asthma are highly complex and relatively unknown. To discover novel biomarkers and the molecular mechanisms underlying asthma, several studies have been conducted by focusing on gene expression patterns in epithelium through microarray analysis. However, few robust specific biomarkers were identified and some inconsistent results were observed. Therefore, it is imperative to conduct a robust analysis to solve these problems. Herein, an integrated gene expression analysis of ten independent, publicly available microarray data of bronchial epithelial cells from 348 asthmatic patients and 208 healthy controls was performed. As a result, 78 up- and 75 down-regulated genes were identified in bronchial epithelium of asthmatics. Comprehensive functional enrichment and pathway analysis revealed that response to chemical stimulus, extracellular region, pathways in cancer, and arachidonic acid metabolism were the four most significantly enriched terms. In the protein-protein interaction network, three main communities associated with cytoskeleton, response to lipid, and regulation of response to stimulus were established, and the most highly ranked 6 hub genes (up-regulated  By 2025, an additional 100 million people may develop asthma [Asthma is a chronic inflammatory disease of the airways, caused by genetic or environmental and lifestyle factors, which is characterized by airway hyper-responsiveness (AHR), inflammation, and variable airflow obstruction . Despitep asthma . Howeverp asthma . The totAs a T-lymphocyte-controlled airway disease, asthma is caused by inflammation, overproduction of mucus, and airway remodeling, which results in hyper-reactivity and airway obstruction. The airway epithelial cells act as the first physical and immunological barrier and play an extremely important role in controlling inflammatory, immune, and regenerative responses to microorganism infections, allergens, and environmental pollutants that contribute to asthma pathogenesis . EpithelCLCA1, POSTN, and SERPINB1) in asthmatics when compared to healthy controls [POSTN, SERPINB2, CLCA1), mast cell mediator genes (CPA3 and TPSAB1), and cystatin genes  were overexpressed in the epithelium of asthmatics [Gene expression analysis is becoming more important in diagnostic fields allowing the identification of novel biomarkers relevant to diseases. The high throughput microarray is an efficient approach that facilitates gene expression analysis, new drug target identification, and novel gene function prediction. Woodruff et al. identified 22 differentially expressed genes (DEGs) . After filtering based on dataset inclusion and exclusion criteria, 10 asthma-related microarray datasets from six disparate platforms  were selected. The detailed information of these datasets and sample descriptions is shown in To compile expression data for data integrating and subsequent investigation, each dataset was preprocessed, normalized, and then integrated for further analysis following the steps illustrated in After the quality control, 1 (GSE470), 2 (GSE4302), 2 (GSE18965), 11 (GSE41861), 4 (GSE63142), 3 (GSE64913), 7 (GSE89809), and 4 (GSE104468) samples did not meet the cut-off criteria in array quality metrics assessment and were excluded for subsequent analysis; the QC reports are presented in Based on the results of the data preprocessing, probe annotations, and gene matching, a total of 8324 genes from 556 samples shared by six microarray platforms were selected . After dCEACAM5 (carcinoembryonic antigen), CLCA1 , POSTN (periostin), CPA3 (carboxypeptidase A3), SERPINB2 (plasminogen activator inhibitor-2), KRT6A (keratin 6A), CD44 , and MUC5AC (mucin 5AC), while LTF (lactotransferrin) and MUC5B (mucin 5B) were down-regulated. Gene expression patterns of all DEGs are shown in the volcano plot , while membrane fraction , insoluble fraction , and cell fraction  from cellular components (CC) were considered as the top three decreased terms , which is consistent with the previous report that asthma status was associated with decreased risk of aggressive bladder cancer [−2) with a suppressed trend (Z-score = −0.58). Arachidonic acid metabolism was the second most significant pathway (FDR = 1.42 × 10−4). Its abnormal metabolism has been observed in asthma [−3) was the third enriched pathway. Woods et al. proposed that fatty acid levels were associated with the risk of asthma in young adults [−2, Z-score = −1.34). An abnormal calcium signaling pathway has been linked with many diseases. Mahn et al. reported that the dysregulation of Ca2+ homeostasis was probably related to abnormal asthmatic phenotype [Based on KEGG pathway mapping, DEGs were significantly enriched in 12 pathways (FDR < 0.05) involved in cancer, arachidonic acid metabolism, linoleic acid metabolism, calcium signaling, aldosterone-regulated sodium reabsorption, and so on . It is wr cancer . Moreoven asthma ,24. Dysrg adults . Black ehenotype . Our reshenotype . Thus, PRIT1, CLC, FKBP5, AGR2, CD36, RUNX2, NTRK2, GRK5, GATA2, ST6GAL1, SLC7A1, SLC18A2, and SERPINB10 were enriched. The previous studies showed that FOXOs were involved in multiple cellular processes, such as stress resistance, cell cycle, apoptosis, and metabolism [AGR2 and RUNX2 would lead to excessive secretion of mucin [GATA2 positively regulated the expression of IL-33 receptor (ST2), which stimulated the production of several pro-inflammatory factors in mast cells [IL-13 promoted the sialylation of MUC4β N-glycans by ST6GAL1 and inhibited the proliferation of damaged epithelial cells in asthmatic patients [Using the GSEA online tool, 9 DNA-binding motifs with FDR < 0.05 were identified and are listed in tabolism . In asthof mucin ,31. GATAst cells . Furtherpatients .microRNA-181a was higher in the acute asthma patients compared to the healthy controls at the beginning of asthma, then dropped to the control level when there were no new airway stimuli. Therefore, microRNA-181a is a potential pro-inflammatory factor in asthma [microRNA-26a would increase hypertrophy of human airway smooth muscle cells and promote airway remodeling by inhibition of GSK-3β [Similarly, 24 potential regulatory microRNAs were identified (FDR < 0.05) . A previn asthma . Mohamedf GSK-3β .CSTA, GATA2, CPA3, P2RY14, and AADAC) and 1 down-regulated gene (HEG1) were located in q21 region (FDR = 9.65 × 10−5), while the remaining 3 down-regulated genes  were located out of q21 region on chromosome 3. Our results indicated that chr3q21 was a new locus associated with asthma.For many chromosomal loci, gene mutation and dysregulation of gene expression often result in many diseases including prostate cancer  and breaCD44, KRT6A, LTF, SERPINB2, MUC5B, and CEACAM5), bridge genes connecting different communities  and leaf-node genes with one neighbor , as shown in To better understand the mechanism of asthma and identify the crucial hub genes among the DEGs, PPI network was constructed using network analysis, which enables the analysis of protein-protein interaction for multiple genes using NetworkAnalyst . To cateWithin this network, CD44 encoding a cell surface adhesion receptor was the most highly ranked hub gene (degree = 59). A previous study showed that CD44 was significantly up-regulated in the bronchial epithelium in asthmatics compared with the controls . Higher Within bridge genes, MUC5AC is a glycoprotein and significantly increased when the respiratory tract was exposed to external stimulus . High exp < 0.001). Combined with gene enrichment analysis, we found that they were associated with the regulation of response to stimulus, cytoskeleton, and response to lipid, respectively -based systems approach. Among them, 17 molecules probably promote the progression of asthma, such as Prestwick-1082, ricinine, and milrinone. On the contrary, 3 molecules have potential therapeutic effects, including catechin, lomefloxacin, and boldine  genes encoding ECM and ECM-associated proteins (M5889); 2) ECM-affiliated proteins, ECM-regulators and secreted factors (M5885); 3) HIF-1α transcription factor network; 4) FOXA1 transcription factor network; 5) termination of O-glycan biosynthesis, and 6) interleukin-4 and 13 signaling . InteresIt is also worth noting that the networks driven by transcription factors HIF-1α and FOXA1 and the signaling mediated by the interleukin-4 and 13 (IL4 and IL13) receptors were enriched for asthma . PreviouMUC5AC via NF-kB-mediated signaling pathway in asthma. Knocking down HIF-1α by siRNA decreased MUC5AC expression under hypoxia even in IL-1β-treated cells. The above results suggest that HIF-1α may be a therapeutic target for asthma [In addition, hypoxia-induced HIF-1α could increase the expression of r asthma .MMP1, ALOX15, CD36, VEGFA, FOS, NOS2, CLCA1, HIF-1α, TIMP1, and FN1 [HIF-1α, were identified in this study. Therefore, targeting this pathway through the inhibition of activating IL13 and IL4, and their receptors, and other pathway components should have therapeutic effects on asthma.Cytokine receptors binding to IL-4 activate the JAK-STAT signaling pathway that regulates the expression of downstream genes  and FN1 . All tarhttp://www.ncbi.nlm.nih.gov/geo/) using the keyword “asthma”. The raw datasets were manually checked and only those that met the following criteria were included for subsequent analysis: 1) gene expression profiling in asthmatics and controls, 2) cell type: airway epithelial cell, but not nasal epithelium, 3) gene expression data were generated by a single-channel microarray platform (Affymetrix or Agilent chips), 4) availability of raw CEL or TXT files, and 5) samples with detailed descriptions.Publicly available microarray gene expression datasets for asthma were retrieved from the Gene Expression Omnibus Database (GEO)  analysis was performed for each microarray data using the arrayQualityMetrics package in R. Datasets were excluded from subsequent analysis when they failed to pass any one of the following assessments: 1) pairwise distances between arrays, 2) boxplots; 3) MA plots .Briefly, the raw Affymetrix CEL files were normalized using the robust multi-array averaging (RMA) approach in the Affy package in Bioconductor Project with the following parameters: background correction, normalization and summarization , and retIn this study, each dataset from all studies was preprocessed separately and then combined into one large dataset for further analysis following the steps illustrated in The direct data integration (DDI) strategy presented in our previous publication  was applTo reduce potential study-specific batch effects, the preprocessed and normalized individual dataset was subjected to correction using the ComBat algorithm, which used the empirical Bayes method to adjust the extreme expression ratios and stabilized gene variances across all other genes and protected their reference from artifacts in the data . The resDifferentially expressed genes (DEGs) in integrated datasets were identified using limma package . The linhttps://david.ncifcrf.gov/). The gene list was uploaded and analyzed using the annotation clustering for biological processes (BP), cellular components (CC), and molecular functions (MF). GO terms were considered to be significant when adjusted p < 0.01. The enrichment results were visualized using GOplot package [http://www.broadinstitute.org/gsea/msigdb/index.jsp) [To study the function of DEGs, enrichment of gene ontology (GO) was performed using DAVID ( package . Additiodex.jsp) ; KEGG paupN, downN represent the number of up- or down-regulated genes between asthmatics and healthy controls, respectively. The count is the number of DEGs belonging to this term.To identify up- or down-regulated terms based on DEGs, the Z-score proposed by Walter was adopted and calculated using the following formula :Z-scoreTo investigate the biological pathway most relevant to asthma, functional pathway enrichment analyses of DEGs were performed using ToppGene Suite .To explore potential protein-protein interaction associated with asthma, DEGs with fold change > 1.5 were mapped to the PPI data using NetworkAnalyst  and its InfoMap algorithm [The asthma-relevant hub-genes were screened using the node degrees calculated in Cytoscape, and the detection of communities in the PPI network was performed with the lgorithm .Analysis of key transcription factors and their putative target genes was carried out using the GSEA online tool . The staTo study whether chromosome position affected gene expression patterns, all DEGs were mapped and enriched on chromosomes using the GSEA online tool. The mapping results (FDR < 0.01) were visualized using the karyoploteR package .The Connectivity Map was a database of gene expression patterns from cultured human cells treated with bioactive small chemical molecules, in which 6100 groups of small molecule interference experiments and 7056 corresponding gene-expression profiles were stored . CMap anCEACAM5, CLCA1, POSTN, CPA3, SERPINB2, KRT6A, CD44, MUC5AC, and down-regulated LTF and MUC5B. Especially, the present study suggests that CD44, KRT6A, LTF, SERPINB2, MUC5B, and CEACAM5 could serve as hub genes in asthma-relevant PPI network and could further act as the biomarkers of asthma. Furthermore, the cross-talking of the IL-4/13 signaling pathway and networks intermediated by transcription factor HIF-1α and FOXA1 play a crucial role in the pathogenesis of asthma. Drug candidate prediction showed that compounds catechin, lomefloxacin, and boldine may be potential drugs for the treatment of asthma caused by inflammation and allergy. Our results elucidated the possible pathogenesis mechanisms of bronchial asthma and also provided several targets for further investigation.To investigate the characteristics of gene expression profiles of bronchial epithelium from asthmatic patients, data integration and systematic bioinformatics approaches were applied in this study. A total of 78 significantly up-regulated and 75 down-regulated genes were identified. Further analyses revealed that 10 differentially expressed genes are possibly instrumental in asthma, including up-regulated


After a first VTE and continuing TT, 11 thrombophilic cases had a second VTE despite adequate anticoagulation, 6 of whom, still anticoagulated, had a third VTE. The greatest density of thrombotic events was at three months after starting TT, with a rapid decline by 10 months. From <1 to 8 months after starting TT, 65% of VTE occurred, which may reflect TT-induced depletion of susceptible thrombophilic patients, leaving a winnowed residual group with fewer VTE events despite the continuation of TT. Before starting TT, we suggest screening for FVL, lipoprotein(a), and the lupus anticoagulant to identify patients at increased VTE risk, with an adverse risk-to-benefit ratio for TT. We suggest that TT should not be started in patients with known thrombophilia–hypofibrinolysis, and should not be continued after a first VTE. When TT is given to patients with thrombophilia–hypofibrinolysis, VTE may occur and then recur despite adequate anticoagulation.In our sequential studies of 67 and 21 patients, testosterone therapy (TT) interacted with thrombophilia–hypofibrinolysis, leading to venous thromboembolism (VTE). Compared to 111 VTE controls not taking TT (VTE-no TT), the 67 and 21 cases were more likely ( In June 2014, based on post-marketing surveillance reports including citation of some of our studies  added a VTE, particularly pulmonary embolism (PE), is associated with significant mortality risk , is a maThe sole currently available placebo-controlled clinical trial is the National Institutes of Health-supported prospective placebo-controlled Testosterone Trial of 790 men over age 65 with low serum testosterone levels (<275 ng/dL) and evidence of sexual dysfunction, physical dysfunction, or reduced vitality ,11,12,13Ultimately, the risk-to-benefit ratio of TT could optimally be explained by a placebo-controlled clinical trial comparable to the Women’s Health Initiative trials , which wOur studies of 67 and 21 patients with VTE after starting TT, and in 111 controls with VTE not taking TT (VTE-no TT), were carried out with signed informed consent, following protocols approved by our institutional Institutional Review Board IRB ,16, as wWe excluded from entry into the studies both TT patients and VTE-no TT controls whose VTE was provoked, associated with cancer, polycythemia vera, recent soft tissue trauma, bone fracture, hip-knee-foot surgery, airline flights >8 hours, or immobilization for >2 weeks. Hence, by selection, thrombotic events, both in TT cases and in VTE-no TT controls entered into the study, occurred spontaneously without superimposed acute triggering factors.The 88 patients and 111 VTE-no TT controls were studied in their serial order of referral over the past 4 years to our thrombosis center by their family physicians for evaluation of thrombophilia–hypofibrinolysis as a pathoetiology of their venous thrombotic events. TT had been prescribed by the referring physicians, and if not already stopped, it was discontinued by us before our assessment of thrombophilia–hypofibrinolysis. Measurements of thrombophilia–hypofibrinolysis were carried out at least 2 months after the cases’ initial thrombotic event.Because we did not initiate TT in the 88 TT-treated patients with VTE, we did not know the etiology of hypogonadism in the TT-treated group.Our studies of 88 patients with thrombotic events after starting TT along with 111 VTE-no TT controls represent a clinical case-control series examining interactions between TT and underlying familial and acquired thrombophilia–hypofibrinolysis in patients referred by virtue of unprovoked venous thrombotic events. These studies amplify findings from our earlier publication ,19. On a2 tests and by stepwise logistic regression after adjusting for age and gender.TT case versus VTE-no TT control comparisons of coagulation factors were made both by Mantel–Haenszel χIn the 88 patients and 111 VTE-no TT controls, laboratory assessment of thrombophilia–hypofibrinolysis included the following assays.PCR measures of thrombophilia  C677T/A198C) and hypofibrinolysis (plasminogen activator inhibitor (PAI-1 SERPINE 1) gene polymorphism 4G/5G) were performed in all cases and controls using previously published methods  by laborSerologic measures of thrombophilia included Factors VIII and XI, homocysteine, antigenic proteins antithrombin III, C, S, and free S, as well as the antiphospholipid antibody APL syndrome , the lupus anticoagulant, anti-beta2-glycoprotein). Established, previously published methods were used . High hoPlasminogen activator inhibitor-1 activity levels, associated with hypofibrinolysis, were not measured.In 2016 , we asseMean ± SD age was 57 ± 14 years. Testosterone gel (50 mg/day) was used by 58%, intramuscular T (150–200 mg/week) by 31%, human chorionic gonadotropin HCG by 2%, a patch by 3%, pellets by 4%, and clomiphene by 1%. Of the 67 patients, 70% had VTE , 24% had osteonecrosis, and 6% had ocular  thrombosis. Mean ± SD duration of testosterone therapy before the occurrence of a thrombotic event was a median of 6 months, a mean ± SD of 10.7 ± 13.3 months, and a 25th–75th percentile of 3–12 months .p = 0.038) and for the lupus anticoagulant (9/64 cases (14%) vs. 4/106 (4%) VTE-no TT controls, p = 0.019). Our findings that 24% of our TT-VTE patients had FVL heterogeneity versus 12% of our VTE-no TT controls emphasized the importance of FVL mutations for VTE 63] carri. Sharma , in a rep = 0.17).As emphasized by Corona et al. , there hIn a recent systemic review and meta-analysis of TT and VTE, Houghton et al.  concludeWithout large randomized trials of men, a “Men’s Health Initiative (MHI)” powered to assess the risk of cardiovascular disease, VTE, prostate cancer, and all-cause mortality of testosterone replacement therapy, there will be persistent controversy over whether TT is good, bad, or indeterminate. An optimal study, paralleling the Women’s Health Initiative WHI studies in women ,20, woulOur two recent studies of 88 patients (67  and 21  altogeth


Recently, we reported a physical and functional interaction of DDC with the major signaling regulator phosphoinosite-3-kinase (PI3K). Here, we provide compelling evidence for the involvement of DDC in viral infections. Studying dengue (DENV) and hepatitis C (HCV) virus infection in hepatocytes and HCV replication in liver samples of infected patients, we observed a negative association between DDC and viral replication. Specifically, replication of both viruses reduced the levels of DDC mRNA and the ~120 kDa SDS-resistant DDC immunoreactive functional complex, concomitant with a PI3K-dependent accumulation of the ~50 kDa DDC monomer. Moreover, viral infection inhibited PI3K-DDC association, while DDC did not colocalize with viral replication sites. DDC overexpression suppressed DENV and HCV RNA replication, while DDC enzymatic inhibition enhanced viral replication and infectivity and affected DENV-induced cell death. Consistently, we observed an inverse correlation between DDC mRNA and HCV RNA levels in liver biopsies from chronically infected patients. These data reveal a novel relationship between DDC and Flaviviridae replication cycle and the role of PI3K in this process. In mammalian tissue, the enzyme is also commonly referred to as aromatic l-amino acid decarboxylase (AADC), since it has been found to decarboxylate other aromatic l-amino acids into biogenic amines, such as serotonin, histamine, and trace amines [e amines ,6,7. Apae amines ,13,14,15e amines ,17,18, ae amines . In humae amines . Interese amines . PI3K ene amines ,23. Givee amines .The tissue specific expression pattern of DDC and the enzyme structure are incompletely known. The single copy gene encoding for the enzyme is located on chromosome 7 loci p12.1–12.3)  and is c.1–12.3  Dopamine expressed in peripheral tissues has been shown to affect cellular metabolism, proliferation, apoptosis and the progression of certain cancers, including hepatocellular carcinoma (HCC) ,39,40,41Flaviviridae virus family, to which HCV and DENV belong, are major causes of morbidity and mortality worldwide. DENV causes widely distributed and endemic diseases with manifestations in visceral organs and in the central nervous system [Members of the s system ,47,48. Is system . The virs system ,51,52,53s system . The HCVs system ,56. DENVs system ,58.Both DENV and HCV interact with the PI3K/AKT pathway to facilitate viral replication and virus spread. At the early stage of infection, DENV activates PI3K signaling to block apoptosis and enhance virus replication , whereasv/v O2) conditions, and liver samples from HCV-infected patients. Furthermore, we studied the effect of viral infection on DDC-PI3K complex formation and DDC subcellular distribution in relation to the viral replication sites. Finally, we addressed the implication of PI3K in virus–DDC relationship.Based on our recently reported DDC–PI3K interaction and the role of PI3K/AKT in the HCV and DENV life cycles, here we investigated the possible role of DDC in HCV and DENV replication and virus–host interaction. For this, we employed efficient infectious models, based on hepatocytes adapted to atmospheric or hypoxic  fetal calf serum (referred to as complete DMEM). To create oxygen tensions lower than the atmospheric one, cells were cultured in a fully humidified incubator supplied with pure nitrogen gas to reduce oxygen as well as with 5% (v/v) CO2 at 37 °C  [Huh7 , Huh7.5 IL, USA) .Total RNA from 12 human liver fine-needle biopsy specimens, obtained from patients with chronic HCV infection, was previously isolated and analyzed for HCV RNA and cellular mRNA levels . Sample Renilla luciferase reporter gene) and plasmids pFK-Jc1 and pFK-i389RLuc2ACore-3′-Jc1 (JcR2a), carrying the full-length HCV genome, have been described previously [Firefly luciferase gene), based on the HCV JFH1 strain, have been described previously [Plasmids carrying the full-length DV-2 genomes (16681 strain) pFK-DVs and pFK-DVR2A -DDC into Huh7.5 cells was performed as described elsewhere . A cappeescribed , or the  Cytomix  containiDENV virus stocks were generated in Vero E6 cells as described elsewhere  and used5 cells per well in 24-well plates and incubated overnight. Cells were infected with 10-fold serial dilutions of virus stocks and incubated for 1 h. The inoculum was removed, and the plates were overlaid with 1.5% carboxymethylcellulose  in minimal essential medium (MEM) . Plates were incubated for seven days and then were fixed with 10% formaldehyde and stained with 1% crystal violet  in 10% methanol for 20 min to visualize plaques. Viral titers were expressed as plaque forming units (PFU)/mL. HCV was titrated as described elsewhere [50)/mL.DENV virus titers were determined by standard plaque assay (PFU) on target VeroE6 cells as previously described . In shorlsewhere . InfectiDenaturing SDS-polyacrylamide gel electrophoresis and Western blotting was performed as described elsewhere . DilutioCo-immunoprecipitation of DDC from Huh7 cell lysate (input samples) was performed as described previously . In brieFirefly luciferase (F-Luc) activity in cell lysates was measured using a Luciferase Assay System , as recommended by the manufacturer. Renilla luciferase (R-Luc) activity in cell lysates was measured using 12 μM coelenterazine  in assay buffer . Measurements were taken in a GloMax 20/20 single-tube luminometer  for 10 s. Luciferase activities were normalized to the total protein amount determined using the Bradford assay reagent .ATP was measured using the ViaLight HS BioAssay kit  according to the manufacturer’s protocol in a GloMax 20/20 single-tube luminometer  for 1 s. ATP levels were normalized to total protein amounts.6 Huh7 cells were seeded into 10-cm-diameter dishes the day before infection. Cells were infected with DENV at an MOI of 1 for 4 h at 37 °C. After 48 h, cells were washed three times with ice-cold PBS, trypsinized, and collected by centrifugation (700× g). Fractions were isolated as described previously [Subcellular fractionation of cytosolic, membrane, nuclear, and postnuclear fractions was performed by adapting the previously reported method . In brieeviously  using di4 cells per well. At 48 h post-infection, the cells were fixed with 500 μL of 3% paraformaldehyde for 10 min at room temperature and permeabilized by incubation in 500 μL of 0.5% Triton X-100 in PBS for 5 min. Staining of DDC was performed by using anti-DDC C-T polyclonal antibody at a dilution of 1:20, staining of DENV NS3 was performed by using a mouse monoclonal antibody  at a dilution of 1:1000, and staining of JFH1 NS5A was performed by using a mouse monoclonal antibody  at a didy  according to the manufacturer’s instructions. cDNA synthesis was performed using Moloney murine leukemia virus reverse transcriptase  according to the manufacturer’s protocol and a mixture of the specific primers DV-A10940 (5′-ACCATTCCATTTTCTGGCGTT-3′) and YWHAZ-R for the DENV positive-strand RNA and the housekeeping gene 14-3-3-zeta polypeptide (YWHAZ) mRNA, respectively (3.5 pmol/μL of each primer), or oligo(dT) primers  for the DDC transcripts. Real-time quantitative PCR was performed using KAPA SYBR FAST qPCR Master Mix  as well as primer pairs specific for the DENV 3′UTR (DV-S10873: 5′-GAAAGACCAGAGATCCTGCTGTCT-3′ and DV-A10940), or the exons 10-12 of full-length DDC mRNAs (DDC-F: 5′-GAACAGACTTAACGGGAGCCTTT-3′ and DDC-R: 5′-AATGCCGGTAGTCAGTGATAAGC-3′). YWHAZ housekeeping gene was used as a normalization control in all reactions (YWHAZ-F: 5′-GCTGGTGATGACAAGAAAGG-3′ and YWHAZ-R: 5′-GGATGTGTTGGTTGCATTTCCT-3′), as it was confirmed that its expression was not affected upon viral infection or under low-oxygen conditions .l-dopa, Triton X-114, and protein A agarose beads were purchased from Sigma-Aldrich .LY294002 (panPI3K inhibitor) was obtained from Cayman Chemical . Carbidopa, 5-hydroxytryptophan (5-HTP), t-test with p ≤ 0.05 were considered as statistically significant. Statistical calculations were carried out using Excel Microsoft Office®  or Prism .In all diagrams, bars represent mean values of at least three independent experiments in triplicate or tetraplicate. Error bars represent standard deviation. Only results subjected to statistical analysis using Student’s Flaviviridae viruses HCV and DENV. For this, liver hepatoma Huh7 or Huh7.5 cells were used in infection studies, performed, in parallel, under two oxygen tensions: atmospheric (20% v/v), which is traditionally used in cell culture, and hypoxic (3% v/v), which is physiologically sensed by most hepatocytes in the liver and favors DENV and HCV RNA replication [DDC, a cellular enzyme that exerts neurotransmitter biosynthetic function, has a wide distribution in a series of peripheral organs, including the liver, in which its biologic function is yet to be determined. Although DDC enzymatic products or their receptors have been reported to influence the entry of HCV and DENV ,43,44,45lication ,69.v/v) O2 for 18 h, were mock-infected or inoculated with DENV  at a multiplicity of infection (MOI) of 1 for 4 h and, after medium exchange, further cultured for 24, 48, or 72 h at the conditions of preincubation. To investigate a putative regulation of DDC by DENV, Huh7 cells, preincubated at 20% or 3% (v/v) O2 reduced DDC transcription in both DENV-infected and mock-infected cells  . Consist monomer B, in a v monomer  right. Tondition , as conf2.Similarly, HCV also exerted a negative effect on the 120 kDa DDC complex with a concomitant accumulation of 50 kDa monomer, with similar kinetics in the two oxygen conditions D, as shoOn the other hand, viral infection does not seem to affect the levels of the other SDS-resistant DDC immunoreactive species B,D, withTo examine whether the regulation of DDC by DENV and HCV is dependent on the viral RNA replication stage, Huh7 and Huh7-Lunet cells were electroporated with a subgenomic reporter replicon of DENV-2 16,681 or HCV JFH1, respectively, and further cultured for different hours post-transfection (p.t). Both DDC mRNA A and proFlaviviridae viruses DENV and HCV on the levels of DDC mRNA and the 120 kDa putatively functional DDC complex, concomitant with an accumulation of the 50 kDa DDC monomer, but with different kinetics between the two viruses. Moreover, these virus-mediated effects on DDC were validated in a more biologically relevant oxygen condition.Thus, we provide evidence for a conserved negative, viral genome replication-related effect from both Several lines of evidence have shown that DDC is localized both in the cytoplasm and in the cellular membrane fractions as an integral or membrane-associated protein, as well as that the membrane-bound protein is released through an enzyme-dependent mechanism ,92,93,94Similarly, viral infection does not influence the biochemical properties of DDC protein, and more specifically, the hydrophobicity of DDC species, as shown in DENV- or mock-infected Huh7 cells subjected to phase separation assay using Triton X-114 and western blot analysis . MoreoveNext, we examined the localization of DDC relative to DENV and HCV replication sites, by immunofluorescence analysis in infected Huh7.5 cells, as compared to mock-infected ones. We observed that DDC did not colocalize significantly with DENV NS3  or HCV NS5A  B,C, despNext, we sought to investigate a putative effect of DENV on the physical interaction of DDC with PI3K, which we have recently shown for the first time . For thiRenilla luciferase. The levels of HCV and DENV RNA or DENV replication-derived Renilla luciferase activity were determined in cell lysates at the indicated h p.i. As shown, the overexpression of DDC affected negatively the replication of DENV , in non-cytotoxic concentrations, reduced viral replication . Despite the limited number of clinical samples, these results argue for an in vivo inverse correlation between DDC expression and HCV replication.To examine if there is a relationship between the replication levels of a et genes . As showThus, our observations from the in vitro and in vivo conditions highlight the importance of DDC as a potential novel determinant of virus replication and virus–host interaction.l-dopa decarboxylase (DDC), an enzyme that catalyzes the biosynthesis of dopamine, is a determinant factor of the Flaviviridae viruses DENV and HCV life cycle and, in turn, is negatively regulated by viral infection. Specifically, both DDC mRNA and protein are inversely correlated with the viral genome replication levels in hepatocytes, as indicated by infection and replicon transfection studies, as well as, in the case of DDC mRNA, by the use of liver biopsies of chronic HCV patients. Furthermore, DDC overexpression or enzymatic inhibition reduced or enhanced, respectively, DENV and HCV viral propagation. Finally, based on our previous evidence of DDC interaction with PI3K [In the present study, we reveal that ith PI3K , as wellDDC gene expression upon HCV and DENV infection in Huh7-derived cells. In the case of DENV, this downregulation was already apparent at 24 h p.i (v/v O2), used conventionally in tissue culture, as well as in conditions that mimic liver hypoxia (3% v/v O2) and favor viral RNA replication [A negative effect was observed on 24 h p.i A,C, undelication ,69. Howe2, which could be attributed to the early downregulation of the DDC gene referred to above. At 3% O2, the 50 kDa monomer has already accumulated at 24 h p.i., possibly due to the enhanced viral RNA replication under hypoxia . In thechanisms . Virus-mchanisms ), has a Moreover, our results showed that viral infection reduces the levels of cytoplasmic 120 kDa DDC and increases the membrane-associated 50 kDa DDC, while it does not change their distribution in the individual cell fractions . Interestingly, the detection of the 50 kDa monomer in the membranous and the insoluble fractions A, is in In consistence with the results on DDC mRNA, DENV- and HCV-infected cells contain significantly lower total intracellular DDC protein amounts, as compared to mock-infected ones B. MoreovInterestingly, DENV negatively affects the levels of PI3K-DDC complexes , that weDDC gene expression upon PI3K inhibition could be attributed to a cell response for survival, since DDC has been implicated in the apoptotic machinery [In turn, the activity of the PI3K/AKT pathway, that is known to contribute to the establishment of DENV acute/apoptotic and HCV chronic/persistent infection ,64,65,66achinery . Thus, wl-dopa and 5-HTP reduced viral RNA levels (DDC gene transcription to compensate for the loss of DDC function. The effect of carbidopa on DDC expression is opposite than the one exerted by the PI3K inhibitor LY294002, suggesting a negative functional correlation between DDC and PI3K, which was characterized in our previous report [In addition, our data support that DDC, in turn, inhibits DENV and HCV propagation, as overexpression of DDC protein or treatment with its substrates A levels , while tA levels . In contA levels D right, A levels E, which A levels D. MoreovA levels D left anA levels C,E, in bs report .Interestingly, the negative effect of DENV infection on the amount of the PI3K-DDC complex  is similIt is important that analyses of liver biopsy specimens derived from HCV patients with liver fibrosis due to chronic infection, showed a significant inverse correlation between DDC mRNA and HCV genome levels . Moreovel-dopa decarboxylase has been previously classified as a neglected and misunderstood enzyme, and its physiological function in peripheral tissues still remains unknown [In conclusion, although  unknown ,17,18, o unknown , we hypoFlaviviridae family.Finally, although HCV and DENV exhibit significant differences concerning the course of the disease -persistent chronic liver disease and acute/self-limiting infection, respectively, and the effect on cell viability, these differences have no significant role in the interaction of the viruses with DDC. Thus, we suggest that this bidirectional inverse relationship between DDC and viral propagation is probably conserved among the members of the


Non-small-cell lung cancer (NSCLC) is the predominant type of lung cancer in the world. Lung adenocarcinoma (LADC) and lung squamous cell carcinoma (LSCC) are subtypes of NSCLC. We usually regard them as different disease due to their unique molecular characteristics, distinct cells of origin and dissimilar clinical response. However, the differences of genetic and epigenetic progression mechanism between LADC and LSCC are complicated to analyze. Therefore, we applied systems biology approaches and big databases mining to construct genetic and epigenetic networks (GENs) with next-generation sequencing data of LADC and LSCC. In order to obtain the real GENs, system identification and system order detection are conducted on gene regulatory networks (GRNs) and protein-protein interaction networks (PPINs) for each stage of LADC and LSCC. The core GENs were extracted via principal network projection (PNP). Based on the ranking of projection values, we got the core pathways in respect of KEGG pathway. Compared with the core pathways, we found significant differences between microenvironments, dysregulations of miRNAs, epigenetic modifications on certain signaling transduction proteins and target genes in each stage of LADC and LSCC. Finally, we proposed six genetic and epigenetic multiple-molecule drugs to target essential biomarkers in each progression stage of LADC and LSCC, respectively. Lung cancer is the most common malignancy resulting in the largest number of cancer-related deaths worldwide , 2. OnlyBased on histopathological features and gene expression signatures, LADC and LSCC are widely thought to be characterized by a different cell of origin and a distinct pattern of molecular alterations. In general, for LADCs, which are thought to origin from the bronchiolar or alveolar epithelium (Clara cells or type II pneumocytes), mainly arise from the peripherally located airways and can be characterized by the production of mucin and/or the occurrence of glandular differentiation. For LSCCs, which typically often origin from the bronchial epithelium of larger and more central airways , mostly arise from central lung and can be characterized by the morphological features of squamous differentiation, including squamous pearl formation, individual cell keratinisation, and intercellular bridges , 7–9.One major risk factor of these two histologies is tobacco smoke and the other risk factors are asbestos, radon, and environmental/occupational exposure to polycyclic aromatic hydrocarbons and other pollutants contributing to the development of lung cancer, including LADC and LSCC , 11. It Recent studies indicate that carcinogenesis and cancer development not only be accounted for genetic alterations alone, but also involve epigenetic changes. Both genetic alterations and epigenetic changes could lead to the dysregulation of key tumor suppressor genes, oncogenes, and DNA repair/housekeeping genes. Despite the well-known role of genetic alterations, including copy number alterations and mutations in oncogenesis, it has been reported that epigenetic changes are much more frequent than genetic alterations in lung cancer , 13. Theet al. have demonstrated that the locations of miRNA genes are frequently found at fragile sites in the genome, suggesting that the aberrant expression of miRNAs is associated with tumorigenesis  and gy[n] denote the expression level of the j-th protein and the g-th protein for the n-th sample, respectively; αjg is the interaction ability between the j-th protein and the g-th protein, which is interactive protein of the j-th protein; jJ represents the number of proteins interacting with the j-th protein and J is number of protein with candidate PPIN; N denotes the number of data samples. jb represents the basal level of protein j. jv [n] is the stochastic noise of the j-th protein for the sample n due to model uncertainty and data noise. The meaning of protein interactions model equation (1) can be explained that the expression level of the j-th protein is related to the interactions with jJ other proteins in the candidate PPIN.where i-th gene of lung cells for sample n, is given by the following:The gene regulatory model of candidate GRN, describing the transcriptional regulation of the i=1, ...,I and n=1, ...,Nfor ix[n], jy[n], ql[n] and pr [n] denote the expression level of the i-th target gene, the j-th TF, q-th lncRNA and p-th miRNA for the n-th sample, respectively; ijβ and iqτ are the transcription regulatory ability of the j-th TF and the q-th lncRNA on their corresponding binding target gene i, respectively. δip indicates the post-transcriptional regulatory ability of the p-th miRNA to inhibit the i-th target gene (-ip ≤ 0δ). iJ, iQ and iP represent the number of TFs, lncRNAs and miRNAs binding to the i-th target gene, respectively; I and N denotes the number of genes with candidate GRN and the number of data samples, respectively. ik represents the basal level of target gene i. εi [n] is the stochastic noise of the i-th target gene for the sample n due to model uncertainty and data noise. iM [n] denotes the methylation regulation of the i-th gene through its effect on the binding affinities of TFs, miRNAs, lncRNAs, and RNA polymerase on the target gene [ij yjβ[n]iM[n], ipxiδ[n]pr[n]iM[n], iqlqτ[n] iM[n], iMik[n] denote the effect of methylation on the binding affinities of TFs, miRNAs, lncRNAs, and RNA polymerase to the i-th target gene, respectively. The methylation regulation of the i-th target gene iM [n] by DNA methylation profile im[n] can be defined as follows  indicates the DNA methylation profile of the i-th gene for the sample n. In equation (3), we can find that the range of effect of DNA methylation on target gene iiM [n] is 1 to 0.2 while DNA methylation profile im[n] range from 0 to1. From the biological viewpoint, the meaning of equation (3) is that the higher DNA methylation level, the weaker binding affinity between TFs, miRNAs, lncRNAs, and RNA polymerase and their target gene. In contrast, the lower DNA methylation level, the stronger binding affinity between TFs, miRNAs, lncRNAs, and RNA polymerase and their target genes. Besides, the methylation regulation iM [n] in equation (3) still has regulation value (iM [n] = 0.2) while DNA methylation profile is 1, representing the bindings of TFs, miRNAs, lncRNAs and RNA polymerase to the i-th target gene are still exist. The expression level of the i-th gene results from transcriptional regulations of TFs and lncRNAs, the post-transcriptional regulations of miRNAs, and expression level of basal level of i-th gene with stochastic noise. Besides, the transcriptional regulations of TFs and lncRNAs, the post-transcriptional regulations of miRNAs and expression level of basal level (binding of RNA polymerase) can be affected by DNA methylation.where p-th miRNA of lung cells for sample n, is given by the following:The miRNA regulatory model of candidate GRN, describing the transcriptional expression of the p = 1, ...,P and n = 1, ...,Nfor pr[n], jy[n], and zr[n] denote the expression level of the p-th miRNA, the j-th TF and the z-th miRNA for the n-th sample, respectively; pjλ and pzψ are the transcription regulatory ability of the j-th TF on miRNA p and the post-transcriptional regulatory ability of the p-th miRNA to inhibit the p-th miRNA (-pz ≤ 0ψ). pJ represents the number of TF binding to the p-th target miRNA; pP denotes the number of miRNAs binding to the p-th target miRNA and the number of miRNAs with candidate GRN. P denotes the number of miRNA in the candidate GRN. N indicates the number of data samples. pe represents the basal level of target miRNA p. ωp[n] is the stochastic noise of the p-th target miRNA for the sample n due to model uncertainty and data noise. pM [n] denotes methylation regulation of the p-th miRNA as shown in equation (3) and pM [n] has the effect on the binding affinities of TFs, miRNAs, and RNA polymerase on the target miRNA. The terms λpjyj[n]pM[n], pzrpψ[n]zr[n]pM[n], pMie[n] can express the effect of methylation on the binding affinities of TFs, miRNAs, and RNA polymerase to p-th target miRNA, respectively.where q-th lncRNA of lung cells for sample n, is given by the following:Moreover, the lncRNA regulatory model of candidate GRN, describing the transcriptional expression level of the q=1, ...,Q and n=1, ...,Nfor ql[n], jy[n], and pr [n] denote the expression level of the q-th target lncRNA, the j-th TF and p-th miRNA for the n-th sample, respectively; γqj and qpζ are the transcription regulatory ability of the j-th TF on binding lncRNA q and the post-transcriptional regulatory ability of the p-th miRNA to inhibit the q-th lncRNA (-qp ≤ 0ζ). qJ and qP represent the number of TFs and miRNAs binding to the q-th lncRNA, respectively; Q and N denotes the number of lncRNAs in candidate GRN and the number of data samples. qf represents the basal level of lncRNA q. gη[n] is the stochastic noise of the q-th target lncRNA for the sample n due to model uncertainty and data noise. qM [n] denotes methylation regulation of the q-th lncRNA as shown in equation (3) and qM [n] has the effect on the binding affinities of TFs, miRNAs, and RNA polymerase on the target lncRNA. The terms qjyjγ[n]qM[n], qplqζ[n]pr[n]qM[n], qMqf[n] can express the effect of methylation on the binding affinities of TFs, miRNAs, and RNA polymerase to q-th target lncRNA, respectively.where jg, jb in protein interactive model and gene/miRNA/lncRNA regulatory parameters ijβ, ipδ, iq, kiτ, pjλ, pzψ, pe, γqj, qpζ, qf in gene/miRNA/lncRNA regulatory models by gene/miRNA/lncRNA expression data and DNA methylation profiles of each stage of LADC and LSCC. Moreover, it is noted that there are many false-positives existing in candidate PPINs and candidate GRNs due to experimental errors. Hence, we used system order detection method to prune false-positives for obtaining real GENs of each stage of LADC and LSCC which are shown in After constructing the protein interactive regression model (1) of candidate PPIN and gene/miRNA/lncRNA regulatory models 2), (4), and (5) of candidate GRN, we applied system identification method to do parameter estimation getting the protein interactive parameters α, (4), anIn this study, based on mRNA/miRNA/lncRNA and DNA methylation profiles in NGS data, we respectively constructed the GENs for normal stage, early stage, middle stage, and advanced stage of LADC and LSCC to compare the differential genetic and epigenetic progression mechanisms between LADC and LSCC via big data mining, system identification, and system order detection methods. However, the real GENs are still too complex. We used PNP method to obtain core GENs for each stage of LADC and LSCC, respectively. By comparing core GENs among the different stages of LADC and LSCC and with the denotation of KEGG pathways, we further had core pathways in LADC and LSCC between normal lung cells to early stage, early stage to middle stage and middle stage to advanced stage to explore the differential molecular mechanisms between LADC and LSCC. Finally, we investigated how the microenvironment changes, epigenetic modifications, miRNA regulations, and lncRNA regulations to affect the differential progression molecular mechanisms between LADC and LSCC. In addition, some significant drug targets are selected from identified network biomarkers based on proteins with significant expression change between later stage and normal stage, we proposed six designed genetic and epigenetic multiple-molecular drugs for therapeutic treatment of early stage, middle stage, and advanced stage LADC and LSCC, respectively. The six designed genetic and epigenetic multiple-molecular drugs are (1) hydralazine, ketoconazole, and promethazine to target SLC22A18, TERT, RET, POLR2D, E2F1, PDGFB, EGFL7, S100A10, PDGFRA, TLR4, CCL2, RB1, TGFB1, PER1, SFTPA2, and MYC for treating early stage LADC; (2) betulin, nordihydroguaiaretic acid, and proadifen to target HP, LTA, APH1A, MMP8, HIF1A, PRDM14, NOTCH1, HGF, ITGA4, VIM, MYH9, ETS1, and ZEB1 for treating middle stage LADC; (3) iloprost, methotrexate, and MK-886 to target EGF, CDH2, LOXL2, XRCC4, CNIH4, MTOR, BGN, ITGB2, EPOR, IQGAP1, FN1, RHOB, TSGA10, AR, and STAT3 for treating advanced stage LADC; (4) pimozide, mepacrine, and repaglinide to target COL3A1, DDR1, CHRNA5, RPL30, CIAPIN1, GSK3B, IGF2BP3, SLC6A11, ERCC1, SUSD4, TERT, SHOX2, YBX1, SP1, TP63, FGF2, FGFR1, PDGFB, PDGFRB, FKBP5, DAPK3, and ETS1 for treating early stage LSCC; (5) ribavirin, procainamide, and ketoconazole to target COL1A1, JAG1, IGF1, IGF1R, TRAF4, SUSD4, PARG, TNS1, ACTA2, CCL21, CCR7, MYLK, ITGB1, TSC2, GATA2, JUN, ETS1, and JUNB for treating middle stage LSCC; (6) clomipramine, rolipram, and rolipram to target CDH3, CHIC2, TUBB3, LIN7C, YBX1, FN1, ITGA8, TGFB1, ERBB4, DDX5, EMR2, MSN, CHD3, FOXO3, and GATA3 for treating advanced stage LSCC, respectively.


Rat and human subcellular fractions, relatively specific substrates, corresponding coenzymes and HPLC, spectrophotometric or spectrofluorometric analysis of product formation were used. The results showed significant inhibition of cytochromes P450  activities by all tested sesquiterpenes in rat as well as in human hepatic microsomes. On the other hand, all tested sesquiterpenes did not significantly affect the activities of carbonyl-reducing enzymes and conjugation enzymes. The results indicate that acyclic sesquiterpenes might affect CYP1A, CYP2B and CYP3A mediated metabolism of concurrently administered drugs and other xenobiotics. The possible drug–sesquiterpene interactions should be verified in in vivo experiments.Sesquiterpenes, 15-carbon compounds formed from three isoprenoid units, are the main components of plant essential oils. Sesquiterpenes occur in human food, but they are principally taken as components of many folk medicines and dietary supplements. The aim of our study was to test and compare the potential inhibitory effect of acyclic sesquiterpenes,  Sesquiterpenes, defined as 15-carbon compounds formed from three isoprenoid units, are an extremely diverse, heterogeneous and large group of natural compounds. Sesquiterpenes, together with monoterpenes, represent the major components of plant essential oils, widely used in folk medicines, health-supporting preparations and cosmetics [Farnesol occurs in, among others, cabreuva, ambrette, jasmine, ylang, and rose essential oils. FAR has a broad spectrum of biological activities including antioxidant, anti-inflammatory, anti-allergic, chemo-preventive and anticancer effects. For example, FAR ameliorates serum allergic antibody titres and lipid profiles in ovalbumin-challenged mice , and migtrans and a cis form. They can be found in cabreuva, niaouli and neroli oils, among others. NER is a common ingredient in many food and cosmetic products. In organisms, it exerts many biological effects e.g., antioxidant, antibacterial, anti-parasite and anticancer [Nerolidol (NER) is the allylic isomer of farnesol and exists in two geometric isomers, a ticancer . For exaticancer  and schiticancer . Moreoveticancer . Neuroprticancer . Using Hticancer .Taken together, both acyclic sesquiterpenes mentioned above (structures are presented in Cytochrome P450 (CYP)-catalyzed oxidative reactions are the most common phase I reactions in drug metabolism. However, CYPs are not the only enzymes involved in the phase I metabolism of drugs and other xenobiotics—carbonyl reduction is the major phase I reaction for an array of xenobiotics . Carbonytrans-nerolidol (TNER) and cis-nerolidol (CNER) on the activities of CYPs, CBR1, NQO1, AKRs, GSTs, UGTs and SULTs. With respect to possible inter-species differences in an action of inhibitors on drug-metabolizing enzymes, both rat and human hepatic subcellular fractions were used as consequent in vivo experiments in rat are being planned.Therefore, the present study was designed to evaluate the inhibitory effect of three abundant acyclic and biologically active sesquiterpenes farnesol, cis-nerolidol (CNER), trans-nerolidol (TNER), and farnesol (FAR), which are commonly found in the human diet, on cytosolic and microsomal biotransformation enzymes, were tested in human and rat liver subcellular fractions.In the present study, inhibitory effects of acyclic sesquiterpenes First, the inhibitory effect of sesquiterpenes at final concentrations of 100 µM on the main hepatic biotransformation enzymes was assessed by measuring enzyme activities towards specific substrates. This high concentration was tested first to find out whether there is any inhibition at all. Specific activities of selected cytochromes P450 , with and without sesquiterpenes in rat and human microsomes, are given in From all the tested enzymes, only CYP1A2 (EROD activity) and CYP2B/3A (BROD activity), both in human and rat microsomal fractions, were inhibited by CNER, TNER and FAR. Non-enzymatic interference of sesquiterpenes, with some compounds in the reaction mixtures (fluorescence quenching), was considered and excluded.50) in human and rat microsomes. Obtained IC50 values and their 95% confidence intervals are given in CYP1A2 (EROD activity) and CYP2B/3A (BROD activity) were strongly inhibited by testing sesquiterpenes in screening experiment. These enzymes were selected for further testing including determination of 50% inhibition concentration  and CYP3A4 inhibitor ketoconazole (KET) were used for comparison of the inhibitory effect with sesquiterpenes. The 5 µM ANF inhibited EROD activity by 92% but 5 µM FAR, CNER and TNER, only by 77%, 50%, and 38%, respectively. On the other hand, the 5 µM KET inhibited BROD activity by 66%, while the inhibitory effect of 5 µM sesquiterpenes was stronger: FAR inhibited BROD activity by 85%, CNER by 71%, and TNER by 68%.50 values were determined, as high inhibitory effect of acyclic sesquiterpenes toward EROD and BROD activities was found in screening experiment. However, no such a high inhibition was observed in other CYP activities. Data are presented in The inhibitory effect of CNER, TNER and FAR on other human CYP activities catalysed by CYP2A6, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4/5 and corresponding ICThe type of inhibition for CYP1A2 (EROD activity) and CYP2B/3A (BROD activity) by TNER was determined in human and rat microsomal fractions. When the inhibition of CYPs was tested, microsomes were incubated with different concentrations of ethoxyresorufin or benzyloxyresorufin (0.5–5.0 µM) in the presence or absence of TNER (5 µM).M and apparent K’M values and lower apparent V´MAX than VMAX values were found in both species. Kinetic parameters are given in The results of kinetic study are presented in Inhibition of drug-metabolizing enzymes is important from several points of view. Regarding drugs and toxic xenobiotics, the inhibition of the enzymes catalyzing their deactivation leads to augmented plasma concentration of biologically active/toxic substance. By this way, drug efficacy can be prolonged and, together with increased risk of undesired effects and the toxic effect of xenobiotics, can get worse. On the other hand, the inhibition of enzymes that activate xenobiotics into more reactive metabolites can decrease cellular toxicity of these xenobiotics and could contribute to chemo-prevention. In every way, it is necessary to know if all components of human food, as well as all potential drugs, are able to inhibit the main drug-metabolizing enzymes. For that reason, the inhibitory effects of many natural compounds, such as flavonoids, towards drug-metabolizing enzymes have been intensively studied e.g., ,20,21,22Curcuma aromatica, were evaluated for their ability to inhibit CYPs, the sesquiterpene -(+)-germacrone-4,5-epoxide inhibited certain CYPs very potently with IC50 = 1.0 µM [50 value of 3.6 µM in human liver microsomes [Although sesquiterpenes as highly lipophilic compounds can be considered as probable inhibitors of drug-metabolizing enzymes, the information about their potential inhibitory effects is limited. Moreover, all studies have been focused only on cytochromes P450 (CYPs). When ten sesquiterpenes, isolated from the rhizomes of = 1.0 µM . Sesquit= 1.0 µM . Anothercrosomes . Cedrol,crosomes .In our study, the potential inhibitory effect of three acyclic sesquiterpenes FAR, CNER and TNER on the main drug-metabolizing enzymes was studied in rat and human hepatic subcellular fractions. In addition to CYPs, the activities of carbonyl-reducing enzymes and the main conjugation enzymes were also included in the study, with the aim to obtain more complex information. With respect to the necessity of further verifying of the results obtained in vitro in subsequent in vivo experiments, both rat and human samples were used in the present study. We aim to know if the sensitivity of drug-metabolizing enzymes to sesquiterpenes in rats is similar to those in humans, and thus rats could be a suitable experimental animal for planned evaluation of drug–sesquiterpene interactions in vivo.Firstly, the inhibitory potency of acyclic sesquiterpenes at fixed concentration (100 µM) toward the main drug-metabolizing enzymes was screened in rat and human hepatic cytosols and microsomes. While marked inhibition of two CYP-mediated activities (EROD and BROD) by all three sesquiterpenes was observed, the activities of other enzymes were not affected by any sesquiterpene. Although the specific activities of individual enzymes mostly differed between rat and human, the effect of sesquiterpenes seemed to be similar: acyclic sesquiterpenes inhibited only EROD and BROD activities in both species.50 values, and to find out the type of inhibition. EROD activity is ascribed mainly to CYP1A2 in liver microsomes, while BROD activity mainly to CYP2B1 in rat, and to CYP3A4/2B6 activities in human [Based on these results, the inhibitory effects of acyclic sesquiterpenes toward EROD and BROD activities were tested in details to obtain ICin human .50 values of three sesquiterpenes tested were similar  and they were slightly lower in humans (1.3–2.4 µM) than in rats (4.4–6.4 µM) microsomes. Interestingly, the inhibitory effect of acyclic sesquiterpenes was stronger than the effect of KET, a well-known CYP3A4 inhibitor. As CYP3A4 metabolizes about 50% of all drugs, its inhibition by sesquiterpenes might result in drug–sesquiterpene interactions. In the kinetic study, TNER (as a selected representative) acted as non-competitive inhibitor in both species.Concerning BROD activities, ICIn the case of EROD activity, the inhibitory potency differed more among sesquiterpenes, as well as between rat and human microsomes. Model CYP1A inhibitor ANF had a stronger effect than acyclic sesquiterpenes. TNER inhibited EROD competitively in humans but non-competitively in rats. The sesquiterpene mediated inhibition of CYP1A could represent a protective effect of sesquiterpenes, as CYP1A often catalyzes formation of toxic metabolites from environmental pollutants.50 values were determined. However, none or weak inhibition by acyclic sesquiterpenes have been observed. Surprisingly, hydroxylation of midazolam and testosterone, both ascribed to CYP3A enzymes, were inhibited only mildly, although BROD activity  was strongly inhibited by all sesquiterpenes tested. TNER was the most potent inhibitor of testosterone hydroxylation with IC50 51 µM, while CNER was the most effective toward midazolam hydroxylation with IC50 66 µM. The discrepancy of these results can be explained by different substrate concentrations used in the enzyme assays , and by different binding sites of these substrates [Consequently, the inhibitory effects of sesquiterpenes were followed up in other CYP-mediated activities in human liver microsomes. Nine substrates relatively specific for CYP2A6, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4/5 were used, and corresponding ICbstrates .Until now, the inhibitory effect of FAR on CYPs was tested only in rabbit liver microsomes. The obtained results showed that ethoxycoumarin deethylase and diclofenac-4-hydroxylase activities were most sensitive to FAR, while caffeine-8-hydroxylation and taxol-6-hydroxylation were not inhibited at all. The observed inhibition appeared to be reversible, and was not strictly competitive, but rather mixed in nature . Concerncis-nerolidol (CNER), trans-nerolidol (TNER), farnesol (FAR), and other chemicals benzyloxyresorufin, ethoxyresorufin, resorufin, coumarin, 7-ethoxy-4-(trifluoromethyl)coumarin, S-mephenytoin, diclofenac, bufuralol, testosterone, midazolam, chlorzoxazone, menadione, 1-chloro-2,4-dinitrobenzene, p-nitrophenol, p-nitrophenylsulphate, 2-napthol, 3’-phosphoadenosine-5’-phosphate, acenaphthenol, reduced glutathione, UDP-glucuronic acid, cytochrome c, NADH, NADP and NADPH, were purchased from Sigma-Aldrich . All other chemicals used were of HPLC or analytical grade.Sesquiterpenes Male Wistar rats (10–12 weeks old) were obtained from Velaz . They were housed in air-conditioned animal quarters with a 12 h light/dark cycle. Food (a standard rat chow diet) and water were provided ad libitum. The animal protocols used in this work were evaluated and approved by the Ethic Committee of the Ministry of Education, Youth and Sports (Protocol MSMT-24185/2015-11). The protocols were in accordance with the Guide for the Care and Use of Laboratory Animals .Human liver samples were obtained from livers excluded from transplantation for medical reasons  and were used in compliance with National Ethic Laws.v/v), using a Potter-Elvehjem homogenizer and sonication with Sonopolus . The subcellular fractions were isolated by differential centrifugation of the tissue homogenate [Frozen liver (both rat and human) was thawed at room temperature for up to 15 min and processed to microsomal and cytosolic fractions. Briefly, livers were homogenized in a 0.1 M sodium phosphate buffer, pH 7.4, at the ratio of 1:6 (mogenate  and storProtein concentrations were assayed using the bicinchoninic acid (BCA) assay according to manufacturer’s instructions (Sigma-Aldrich). Human liver microsomal fraction contains 8.1 mg of protein in 1 mL, and cytosolic fraction 12.1 mg of protein in 1 mL. Rat liver microsomal fraction contains 8.5 mg of protein in 1 ml, and cytosolic fraction 13.1 mg of protein in 1 mL.v/v).Enzyme activities were assayed in human and rat liver cytosolic and microsomal fractions. The enzyme assays (each performed in 4–8 replicates) were repeated three times  and UV or fluorescence detection, according to the cited literature. Further incubation details are described either in the corresponding references, as well as in the papers from this laboratory e.g., [Enzyme activities of individual CYP forms were measured according to established protocols . The folxylation , CYP2D6 xylation , CYP2E1,xylation  and CYP3xylation , and midxylation ,41. Actiry e.g., ,43,44. CS-transferase , UDP-glase (GST ).50) value and the mechanism of enzyme inhibition was revealed. Sesquiterpenes CNER, TNER and FAR, non-volatile liquids, were pipetted, and proper concentration was calculated according to density. All compounds were dissolved in DMSO. The final solvent concentration in the inhibition assays was 1%, which had no effect on the enzyme activity (data not shown). Non-enzymatic interference of sesquiterpenes with some compounds in the reaction mixtures  was considered and excluded. All experiments were performed in three replicates, if not stated otherwise.Sesquiterpenes were first screened for inhibition of biotransformation enzymes in subcellular fractions in vitro, then the half-maximal inhibitory concentration . The IC50 values for each sesquiterpene were determined by plotting sigmoidal dose response curves of specific enzyme activity vs. logarithm of sesquiterpene concentration using GraphPad Prism version 6.07 for Windows .The concentration of sesquiterpenes required for 50% inhibition of enzyme activity, the ICThe kinetic inactivation study of the CYP1A2 (EROD activity) and CYP2B/3A (BROD activity), both in rat and human, with TNER, was performed to find out the mechanism of enzyme inhibition by this sesquiterpene. Mechanism of EROD and BROD inhibition was tested at the final ethoxyresorufin or benzyloxyresorufin concentrations 0.5–5.0 µM. The concentration of TNER was 5.0 µM.Experimental data were fitted to the Michaelis-Menten equation, basic kinetic parameters were determined using the program GraphPad Prism version 6.07 for Windows. The type of inhibition was estimated using a Lineweaver-Burk  plot.p < 0.05. Data are presented as the mean ± standard deviation.All experiments (each sample performed in four replicates) were repeated three times (HPLC measurement of CYP activities only twice). All calculations were done using Microsoft Excel and GraphPad Prism 6.07. Statistical significance was tested by one-way Anova, and differences were considered statistically significant when Taken together, acyclic sesquiterpenes FAR, CNER, and TNER showed certain potency to inhibit CYP1A, CYP2B and CYP3A activities in liver. On the other hand, these sesquiterpenes did not seriously affect other CYPs, carbonyl-reducing enzymes and conjugation enzymes. As CYP3A4 metabolizes about 50% of all drugs, its inhibition by sesquiterpenes might result in drug—sesquiterpene interactions. Nevertheless, the results obtained in vitro should be verified in vivo. Rat seems to be suitable model for these in vivo studies, as comparable sensitivity of drug-metabolizing enzymes to these sesquiterpenes have been observed in rat and human samples.


Metarhizium rileyi (formerly known as Nomuraea rileyi) is a potential agent for microbial control of many insect pests from the order Lepidoptera, the damages of which can cause considerable loss of productivity in agriculture. We report the genome sequence and annotation of M. rileyi strain Cep018-CH2/ARSEF 7053. Metarhizium rileyi (formerly known as Nomuraea rileyi) is a potential agent for microbial control of many insect pests from the order Lepidoptera, the damages of which can cause considerable loss of productivity in agriculture. We report the genome sequence and annotation of M. rileyi strain Cep018-CH2/ARSEF 7053. Metarhizium rileyi is a cosmopolitan species of entomopathogenic fungi of the family Clavicipitaceae  with extensive literature published under its synonym Nomuraea rileyi  on 4 April 2001, in Chivilcoy , and it was deposited at the Centro de Estudios Parasitológicos y de Vectores (CEPAVE) collection, La Plata, Buenos Aires, Argentina, and also at ARSEF (de novo (Fasteris SA) paired-end libraries with insert sizes of 250 to 350 bp, and two Nextera  mate pair libraries with insert sizes of 3,000 and 5,000 bp, producing a total of 182,506,935 read pairs. The average read length was 125 bp for both sets of libraries. The quality of the sequencing raw reads was assessed with FastQC version 0.11.5 , which has a total assembly length of 32,013,981 bp and 8,764 protein-coding genes (Gene prediction and annotation using Funannotate version 1.5.0-b99af2c , with thng genes . Secondang genes , identifng genes , UniProtng genes , eggNOG ng genes , CAZy (2ng genes , MEROPS ng genes , InterPrng genes , and antng genes  databaseSBHS00000000. The version described in this paper is version SBHS01000000. The raw reads were deposited in the NCBI Sequence Read Archive under the BioProject accession number PRJNA503201.This whole-genome shotgun project has been deposited at DDBJ/ENA/GenBank under the accession number