Current Medicinal Chemistry - Volume 32, Issue 39, 2025
Volume 32, Issue 39, 2025
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Inflammatory Biomarkers in Hypertension
Hypertension remains a leading modifiable risk factor for cardiovascular diseases, yet its underlying mechanisms are not fully understood. Emerging evidence suggests that inflammation plays a central role in the pathogenesis and progression of hypertension. This review explores the association between inflammatory biomarkers, such as C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α), and hypertension. These biomarkers are not only indicators of inflammation but also active participants in the processes that elevate blood pressure, including endothelial dysfunction, oxidative stress, and immune system activation. Cytokines play a pivotal role in vascular remodeling and renal dysfunction, underscoring the inflammatory underpinnings of hypertension. Additionally, novel composite biomarkers like the monocyte-to-high-density lipoprotein ratio (MHR), systemic inflammation response index (SIRI), and systemic immune-inflammation index (SII) have been identified as valuable tools for assessing the inflammatory state in hypertensive patients. While renal denervation has emerged as a promising treatment for resistant hypertension, its impact on inflammatory biomarkers remains inconclusive, highlighting the need for further research.
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Oxidative Stress Biomarkers in Hypertension
Arterial hypertension is a silent and progressive disease with deleterious vascular implications on all target organs, including the heart, the brain, the kidneys, and the eyes. Oxidative stress, defined as the overproduction of Reactive Oxygen Species (ROS) over antioxidants, is capable of deteriorating not only the normal endothelial but also the cellular function with further cardiovascular implications. Xanthine oxidase activity, NADPH oxidase overexpression, and ROS production lead to hypertension and high arterial tone, culminating in end-organ damage. The inactivation of NO by superoxide reduces vasodilation and promotes peroxynitrite formation, which damages cellular components. Activation of MMPs by oxidative stress contributes to pathological neovascularization and angiogenesis. Salucin-β-induced activation of Angiotensin-II and NADPH results in vascular remodeling and fibrosis, while lipid peroxidation and PARP-1 activation further exacerbate cellular apoptosis and vascular calcification. Moreover, to reliably assess the oxidative status an emerging number of biomarkers are under investigation. Antioxidant therapy, alongside traditional antihypertensive agents such as beta-blockers and ACE inhibitors, offers the potential to mitigate oxidative stress and its detrimental effects. Additionally, polyphenols, found in plant-based foods, show promise in managing oxidative stress in hypertensive patients although this data has not been confirmed in randomized clinical trials. Understanding the intricate relationship between oxidative stress and hypertension underscores the importance of developing comprehensive therapeutic strategies to reduce cardiovascular risk and improve patient outcomes.
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Supplementation of Antioxidants in Chronic Kidney Disease: Clinical Necessity or Wishful Thinking? A Bench to Bedside Translational Research
Chronic Kidney Disease (CKD) patients are at increased risk for atherosclerosis, cardiovascular disease (CVD), and progression to end-stage kidney disease (ESKD). This heavy CVD risk cannot be solely attributed to traditional Framingham risk factors. Oxidative stress, defined as the disruption of the balance between prooxidants and antioxidants in favor of the former, has emerged as a novel risk factor for CVD and CKD progression. Specifically, lipid peroxidation has been identified as a trigger for endothelial dysfunction, the first step towards atherogenesis, and protein oxidation has been associated with CKD progression. The oxidation of proteins and lipids starts early in CKD, increases gradually with disease progression, and is further exacerbated in ESKD due to dialysis-related factors. In order to counteract the deleterious effects of free radicals and thereby ameliorate, or delay, CV disease and progression of CKD, exogenous administration of antioxidants has been proposed. Here, we attempt to summarize existing data from experimental and clinical studies that test antioxidants for their possible beneficial effects against CVD and CKD progression, such as vitamins E and C, statins, omega-3 fatty acids, trace elements, polyphenols, and N-acetylcysteine.
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Markers of Vascular Dysfunction in Hypertension
Hypertension is a modifiable cardiovascular risk factor and displays a rapidly growing incidence due to aging and the acquisition of an unhealthy lifestyle. Hypertension is linked to the development of target organ damage in several vascular beds such as coronary arteries, peripheral, cerebral, and renal arteries. Besides, along with the presence of other cardiovascular risk factors, it aggravates vascular dysfunction due to the aging process. The mechanisms of vascular dysfunction in hypertension are complex and involve excessive salt intake and water retention, activation of neurohormonal systems, induction of endothelial dysfunction of large arteries and microcirculation, development of arterial stiffness, and complex interactions with cellular pathways of inflammation, oxidative stress, and thrombosis. The extent of vascular dysfunction in patients with hypertension can be assessed by evaluating endothelial function, measuring arterial stiffness, and testing the levels of circulating biomarkers of oxidative stress, pro-inflammatory cytokines, and thrombosis. Assessing these markers in subjects with and without hypertension could aid in identifying those at risk of vascular damage and improving risk prediction for future cardiovascular events. While several lifestyle and pharmacological therapies have shown promise in addressing vascular dysfunction in hypertension, none of these biomarkers have been established as an independent risk factor or treatment target. Therefore, in this article, we review the literature on the evidence that exists regarding the role of vascular dysfunction in the pathophysiology, diagnosis, progression, and treatment of hypertension, highlighting the lack of conclusive evidence in this field.
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Endothelial Function Biomarkers in Hypertension
Hypertension (HTN) is a major cardiovascular risk factor, contributing to over 10.4 million deaths annually. HTN's pathophysiology involves complex mechanisms, including altered vascular resistance and hormonal regulation. Endothelial dysfunction, a hallmark of HTN, is characterized by reduced vasodilator production and increased vasoconstrictor and inflammatory cytokine generation, leading to elevated blood pressure (BP) and vascular damage. Early detection and intervention are crucial to prevent long-term complications. Identifying biomarkers of endothelial function in HTN can aid early disease detection and offer insights into underlying mechanisms. Blood sample-derived biomarkers include nitric oxide (NO), asymmetric dimethylarginine (ADMA), matrix metalloproteinases (MMPs), vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and endothelial microparticles. Imaging-based biomarkers such as flow-mediated dilation (FMD) and coronary flow reserve (CFR) are also significant. These biomarkers provide the means to identify inflammation, endothelial dysfunction, and vascular injury, enhancing disease pathogenesis understanding. Combined with accurate BP measurements, they contribute to early diagnosis and provide valuable insights that may inform treatment strategies. Baseline and sequential plasma biomarker measurements also indicate treatment efficacy. However, large-scale, prospective population studies are necessary to fully validate these biomarkers for clinical use.
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Microalbuminuria as a Prognostic Marker in Essential Hypertension
Essential hypertension is a major cardiovascular pathology globally, with an estimated prevalence of approximately 33%, and it is a significant contributor to both mortality and adverse cardiovascular events. Finding early prognostic markers in such individuals could, thus, provide enhanced risk stratification and identification of patients with higher odds of target-organ damage or adverse events. Microalbuminuria is defined as an abnormal excretion of albumin in urine, is well associated with vascular disease, endothelial dysfunction, and low-grade inflammation, and is a marker of subclinical renal damage. Through the years, microalbuminuria at baseline has been well correlated with increasing blood pressure levels and blood pressure patterns, i.e., non-dipping phenotype. At the same time, its presence in hypertensive individuals indicated increased rates of mortality, renal disease progression, and major adverse cardiovascular outcomes, including stroke and myocardial infarction. Thus, microalbuminuria can provide a prognostic marker of future adverse events in hypertensive individuals. Interestingly, standard antihypertensive pharmacotherapy and newer drugs have shown regression of microalbuminuria extent and renoprotection in both diabetic as well as hypertensive individuals, implying that early therapy could decrease the rate of disease progression and limit target-organ damage. Thus, the aim of this review is to analyze the available studies documenting the predictive role of microalbuminuria for both mortality, target-organ damage, and adverse events, as well as describe the impact of pharmacotherapy in the presence and extent of subclinical renal damage, as shown by the levels of this marker.
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Thrombosis in Hypertension: Pathophysiology, Biomarkers, and the Effect of Antihypertensive Treatment
Hypertension, characterized by elevated blood pressure levels, remains a global health concern due to its association with cardiovascular complications, notably thrombosis. Thrombosis, the formation of blood clots within blood vessels, poses a significant risk for myocardial infarction, stroke, and limb ischemia, leading to adverse patient outcomes. Understanding the pathophysiological mechanisms underlying thrombosis in hypertension is crucial for developing effective preventive and therapeutic strategies. Hypertension induces structural and functional alterations in the vasculature, endothelium, and platelets, creating a prothrombotic milieu. Endothelial dysfunction, increased platelet activation, and alterations in coagulation factors contribute to the heightened thrombotic risk observed in hypertensive individuals. Biomarkers associated with thrombotic events, such as mean platelet volume, D-Dimer, and fibrinogen offer valuable insights into the pathogenesis of thrombosis and may serve as prognostic indicators for cardiovascular events in hypertensive populations. Investigating the impact of antihypertensive treatment on thrombotic risk is essential, as these medications exert pleiotropic effects on the vasculature and hemostatic system. By elucidating the intricate interplay between hypertension and thrombosis, this review aims to enhance our understanding of cardiovascular risk in hypertensive individuals and identify novel therapeutic targets for preventing thrombotic complications.
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Milk Thistle (Silybum marianum): Potential Role in Cancer Prevention
Authors: Geir Bjørklund, Olha Storchylo, Monica Butnariu, Maryam Dadar and Salvatore ChirumboloMilk thistle compounds have recently gained attention for their potential role in cancer prevention and treatment. Despite most evidence reporting this property refers to in vitro and animal studies, milk thistle flavonoids may provide insightful suggestions about novel chemopreventive agents. This narrative review provides an overview of the current understanding of milk thistle's effects on cancer cells and highlights possible mechanisms of action. The active compounds in milk thistle mainly exhibit antioxidant and anti-inflammatory effects, which protect cells and enhance their survival responses, even inhibiting cancer development. In addition, the compounds possess immunomodulatory properties crucial in preventing cancer progression. Another important mechanism is the induction of apoptosis, promoting cancer cell death and inhibiting tumour growth. These compounds inhibit angiogenesis, preventing tumour growth and spread. Due to their potential to inhibit cancer progression, they modulate cell signalling pathways, including the MAPK and PI3K/Akt pathways, which are involved in cell growth and survival. Although current research is promising, it is crucial to address the current gaps in knowledge about milk thistle compounds in cancer prevention and treatment. Future studies should focus on rigorous clinical trials, dose optimization, mechanistic investigations, combination therapy approaches, and personalized medicine to maximize their potential. Basic experimental evidence can provide new clues to establish clinical trials to improve cancer care and reassure patients and healthcare professionals.
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Protective Effect of Curcumin on Metabolic Syndrome Components through the Microbiota
More LessCurcumin, a natural polyphenolic compound found in turmeric, has garnered increasing research interest due to its potential health benefits, particularly in the context of the rising global prevalence of metabolic syndrome (MetS). With MetS affecting a significant portion of the global population and serving as a precursor to chronic diseases, such as type 2 diabetes and cardiovascular diseases, identifying effective, accessible, and safe interventions has become a critical public health priority. This review explores curcumin’s role in regulating gut microbiota composition, enhancing intestinal barrier function, and reducing inflammation, which can collectively improve key components of MetS, such as hyperglycemia, dyslipidemia, obesity, and hypertension. Supplementation with curcumin has shown promising results in improving metabolic health by promoting the production of short-chain fatty acids (SCFAs), such as butyric and propionic acids. These effects may protect against dyslipidemia and reduce the risk of chronic conditions. Furthermore, curcumin has demonstrated potential in reducing hypertension through various mechanisms, including inflammation reduction, modulation of lipopolysaccharide (LPS) production, activation of G-protein-coupled receptor 43 (GPR43), and increased levels of SCFAs. Given the significant public health implications of MetS, understanding curcumin's impact on gut microbiota presents an opportunity for developing novel therapeutic strategies that address this urgent health challenge. Despite its promise, further research is necessary to fully comprehend the underlying mechanisms involved. Additionally, determining the optimal dosage and duration of curcumin supplementation for achieving its effects on metabolic syndrome is crucial for future therapeutic applications. This review highlights curcumin's potential as a natural compound with multifaceted health benefits, particularly in the context of metabolic syndrome and its associated complications, emphasizing the pressing need for clinical studies to validate findings and inform evidence-based therapeutic applications.
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A Gene Signature Developed Based on Reactive Oxygen Species to Predict the Metabolism, Immunity, Mutational Status, and Prognostic Survival for Glioblastoma
Authors: Liqian Xie, Huasong Gao and Shukun HuAimTo explore the mechanism of regulatory genes related to reactive oxygen species (ROS) in glioblastoma (GBM).
BackgroundGBM is a brain malignancy with a poor prognosis. ROS plays a critical role in cellular metabolism, signaling, and senescence, and abnormalities in ROS are closely associated with cancer initiation and development. However, the role of ROS-regulated genes in GBM remained unknown.
ObjectiveTo explore the role of ROS-regulated genes in GBM and to build a ROS-related prognostic model.
MethodsRNA sequencing data and clinical data from GBM patients were collected from public databases. The enrichment scores of ROS-correlated pathway gene sets obtained from The Molecular Signatures Database (MSiDB) were calculated using single sample gene set enrichment analysis (ssGSEA). Subsequently, key ROS-correlated gene modules were sectioned by weighted gene co-expression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were performed to screen ROS-related genes, which were used to develop a risk model. In addition, the correlation between patients in high-risk and low-risk groups and clinicopathological features, metabolism-related pathways, and pathways related to tumor progression was analyzed. Finally, the difference in immune cell infiltration between patients in the two risk groups was calculated using CIBERSORT.
ResultsWe found that ROS-related genes could predict the prognosis of patients suffering from GBM and that abnormal activation of the ROS pathway increased the metabolism of sugars, fats, and amino acids. WGCNA identified gene modules closely associated with ROS. A prognostic risk model was created using three key genes (OSMR, SLC6A6, and UPP1). Immune infiltration analysis showed that high-risk Patients had higher levels of macrophage infiltration, and a high-RiskScore was positively correlated with multiple metabolism processes, programmed death, and epithelial-mesenchymal transition (EMT) pathway activity.
ConclusionThe ROS-associated risk model could accurately predict tumor immunity and progression for GBM patients, acting as an effective predictor of GBM prognosis. The present discovery provided a novel understanding of the diagnosis and treatment of GBM patients.
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Machine Learning-based Macrophage Signature for Predicting Prognosis and Immunotherapy Benefits in Cholangiocarcinoma
Authors: Junkai Huang, Yu Chen, Zhiguo Tan, Yinghui Song, Kang Chen, Sulai Liu, Chuang Peng and Xu ChenAimsWe aimed to develop a macrophage signature for predicting clinical outcomes and immunotherapy benefits in cholangiocarcinoma.
BackgroundMacrophages are potent immune effector cells that can change phenotype in different environments to exert anti-tumor and anti-tumor functions. The role of macrophages in the prognosis and therapy benefits of cholangiocarcinoma was not fully clarified.
ObjectiveThe objective of this study is to develop a prognostic model for cholangiocarcinoma.
MethodsThe macrophage-related signature (MRS) was developed using 10 machine learning methods with TCGA, GSE89748 and GSE107943 datasets. Several indicators (TIDE score, TMB score and MATH score) and two immunotherapy datasets (IMvigor210 and GSE91061) were used to investigate the performance of MRS in predicting the benefits of immunotherapy.
ResultsThe Lasso + CoxBoost method's MRS was considered a robust and stable model that demonstrated good accuracy in predicting the clinical outcome of patients with cholangiocarcinoma; the AUC of the 2-, 3-, and 4-year ROC curves in the TCGA dataset were 0.965, 0.957, and 1.000. Moreover, MRS acted as an independent risk factor for the clinical outcome of cholangiocarcinoma cases. Cholangiocarcinoma cases with higher MRS scores are correlated with a higher TIDE score, higher tumor escape score, higher MATH score, and lower TMB score. Further analysis suggested high MRS score indicated a higher gene set score correlated with cancer-related hallmarks.
ConclusionWith regard to cholangiocarcinoma, the current study created a machine learning-based MRS that served as an indication for forecasting the prognosis and therapeutic advantages of individual cases.
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Elemene Injection Suppresses Pancreatic Cancer Progress through Regulating Cell Adhesion: A Research Based upon Network Pharmacology and Verification Test
Authors: Jiangang Zhao, Fenglin Zhang and Ping LiBackgroundThis study investigates the potential effects of elemene injection on pancreatic cancer using network pharmacology and experimental validation.
MethodsGEO database were used to acquire genes which are differentially expressed between pancreatic cancer tissue and normal tissue. The vigorous energetic ingredients were identified in research and the object genes were obtained from BATMAN-TCM. The key targets and signaling pathways of elemene injection were identified using compound-target network analysis, protein-protein interaction network analysis, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. in vitro experiments were carried out to confirm the accuracy of the network pharmacology predictions.
ResultsTwo hundred and eleven target genes that may be involved in Elemene's impact on pancreatic cancer were identified. Bioinformatics analysis was conducted to determine the two active mixtures and one key target. GO and KEGG enrichment analyses indicated that elemene injection exerts therapeutic effects on pancreatic cancer, regulating the cell adhesion by ECM-receptor interaction pathway. The experiments verified that elemene injection suppressed the growth and movement of pancreatic cancer cell lines Panc02 and MiaPaca-2 and the mechanism is related to regulating ECM-receptor interaction pathway-related genes. FN1 was identified as core targets by bioinformatics analysis. The FN1 was downregulated by elemene injection and was validated by QPCR and Western Blot.
ConclusionThe findings of the current study emphasized that elemene injection might control cell attachment, decrease metastasis, and suppresses pancreatic cancer progress. FN1 might be a therapeutic target for pancreatic cancer.
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Machine Learning-based Gene Biomarker Identification for Improving Prognosis and Therapy in Hepatocellular Carcinoma
Authors: Lingyan Deng, Lei Dou, Xinyu Huang, Peng Wang and Na ShenIntroductionTraditional clinical evaluations based on pathological classification have shown limited effectiveness in predicting prognosis and guiding treatment for patients with hepatocellular carcinoma (HCC). This study aims to identify a robust molecular biomarker for improving prognosis and therapy in HCC.
MethodsThe International Cancer Genome Consortium (ICGC), Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) provided expression data and clinicopathological information for several cohorts. First, Cox regression analysis and differentially expressed analysis were performed to identify robust prognostic genes. Next, machine learning algorithms, including 101 statistical models, were employed to pinpoint key genes in HCC. Single-cell sequencing analysis was conducted to explore the potential subcellular functions of each key gene. Based on these findings, an HCC Prognosis-Related Index (HPRI) was developed from the identified key genes, and HPRI-based nomogram models were validated across multiple cohorts. Additionally, tumor microenvironment analysis and drug sensitivity analysis were performed further to assess the clinical significance of the HPRI in HCC.
ResultsA total of 36 robust prognostic genes with differential expression in HCC were identified, from which seven key genes-DCAF13, EEF1E1, GMPS, OLA1, PLOD2, PABPC1, and PPARGC1A-were filtered using machine learning algorithms. Except for PPARGC1A, all these genes were highly expressed in malignant cells, followed by fibroblasts. Notably, we developed the HPRI based on the key genes and validated its clinical relevance. Results demonstrated that the HPRI and HPRI-derived nomogram models had good predictive performance across multiple cohorts. Following tumor microenvironment analysis revealed that a high HPRI was linked to a higher likelihood of immune evasion. Drug sensitivity analysis suggested that patients with a high HPRI might benefit from chemotherapeutic agents like sorafenib, as well as novel compounds such as ML323 and MK-1775.
ConclusionOur study demonstrates a well-rounded approach by integrating gene expression, machine learning, tumor microenvironment analysis, and drug sensitivity profiling. HPRI may serve as a promising predictor for guiding prognosis and personalized treatment in HCC.
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Comparative Glycoproteomic Analysis of Mouse 4T1 Breast Cancer Model
BackgroundGlycosylation is a post-translational modification process that plays a fundamental role in malignant transformation. Moreover, aberrant glycosylation is known to be associated with cancer progression. Thus, the characterization of cancer-specific protein glycosylation profiles might reveal important diagnostic and/or prognostic biomarkers for cancer.
ObjectiveIn the present study, we have analysed serum protein and glycoprotein profiles during breast cancer progression using a mouse model. Specifically, 4T1 tumour cells were injected into the mammary fat pad of BALB/c mice to induce tumours.
MethodsSera samples were subsequently collected weekly for four weeks and examined using two-dimensional electrophoresis (2D-E) coupled with lectin-based analysis, followed by mass spectrometry.
ResultsThis glycoproteomic profiling identified eight differentially expressed proteins, of which alpha-1 protease inhibitor 2, contraption (CON), haptoglobin (HP), and kininogen-1 were significantly up-regulated during the first 4 weeks of tumour progression. Notably, aberrantly N-glycosylated prothrombin was also detected in sera samples from all mice over the 4 weeks post-tumour injection. Additionally, O-glycosylated alpha-2-macroglobulin, CON, and HP were detected in weeks 1 and 2, whereas O-glycosylated alpha-2-HS-glycoprotein and CON were detected on weeks 3 and 4 post-implantation.
ConclusionOur findings indicate that the combination of 2D-E with lectin-based chromatography represents an effective approach for identifying prognostic biomarkers for breast cancer.
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Volumes & issues
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Volume 32 (2025)
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Volume (2025)
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Volume 31 (2024)
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Volume 30 (2023)
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Volume 29 (2022)
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Volume 28 (2021)
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Volume 27 (2020)
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Volume 26 (2019)
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Volume 25 (2018)
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Volume 24 (2017)
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Volume 23 (2016)
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Volume 22 (2015)
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Volume 21 (2014)
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Volume 20 (2013)
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Volume 19 (2012)
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Volume 18 (2011)
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Volume 17 (2010)
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Volume 16 (2009)
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Volume 15 (2008)
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Volume 14 (2007)
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Volume 13 (2006)
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Volume 12 (2005)
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Volume 11 (2004)
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Volume 10 (2003)
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Volume 9 (2002)
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Volume 8 (2001)
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Volume 7 (2000)
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