1B), whereas the development of anemia (hemoglobin <100

g/L) occurred gradually over the course of treatment (Fig. 1C). The baseline demographics of patients who developed anemia compared with those who did not are shown in Table 1. Patients who developed anemia were more likely to be female and significantly older with lower body weight, body mass index, creatinine clearance, hemoglobin levels, white cell counts and platelet counts than patients who did not become anemic. Patients with hemoglobin decline >30 g/L were more likely to be older, female, and with lower body weight and higher baseline Rapamycin nmr hemoglobin than patients with a maximal hemoglobin decline ≤30 g/L (data not shown). The allocated and mean dosages received for PEG-IFN and ribavirin at weeks 12, 24, and 48 of therapy are shown in Table 2. At baseline, more patients who became anemic were allocated a lower dose of ribavirin (1,000 mg versus 1,200 mg) than patients who did not become anemic (61% versus 44%; P = 0.0002). The mean daily ribavirin dosage was significantly lower in patients who developed anemia compared with those who did not become anemic at week 12 (998 ± 143 mg/day versus 1,052 ± 152 mg/day; P = 0.0001) and week 24 (967 ± 169

mg/day versus 1030 ± 210 mg/day; P = 0.0002); there was no significant difference in ribavirin exposure at week 48. The mean weekly PEG-IFN dosage at week 48 was significantly lower in patients who did not become anemic compared with anemic patients for both standard and induction BGJ398 therapy arms; there was no significant difference

in PEG-IFN exposure at earlier times. Similar outcomes were observed when PEG-IFN and ribavirin exposure were analyzed as a percentage of planned target dose (data not shown). Virological responses at the end of treatment (ETR) and at the end of follow-up (SVR) were significantly different between patients with hemoglobin <100 g/L at any time during treatment compared with those with hemoglobin ≥100 g/L (ETR, 80% versus 65%, respectively, P = 0.003; SVR, 61% versus 50%, respectively, P = 0.02). Relapse rates were similar, however (Fig. 2A). Similarly, ETR and SVR rates were significantly higher in patients with hemoglobin decline >30 g/L compared with those ADAM7 with hemoglobin decline ≤30 g/L. An ETR occurred in 72% of patients with a hemoglobin decline >30 g/L compared with 52% of those without a similar change in hemoglobin (P < 0.001). Similarly, a SVR occurred in 54% with a hemoglobin decline >30 g/L compared with 46% with a hemoglobin decline ≤30 g/L (P = 0.049). Relapse rates were similar (Fig. 2B). In separate multiple logistic regression analyses, both hemoglobin <100 g/L (protocol defined anemia) and maximum hemoglobin decline >30 g/L during treatment were significantly associated with SVR rate. The odds ratio estimate for SVR for hemoglobin <100 g/L was 1.97 (95% confidence interval, 1.08-3.62; P = 0.028). The odds ratio estimate for hemoglobin decline >30 g/L was 2.17 (95% confidence interval, 1.31-3.

5B). In contrast, HBV-Ab19 had a weaker effect in blocking

the release of viral particles from the cells, but its effect was more prolonged which may be due to a greater uptake within cells, as indicated by the western blot (Fig. 4). Experimental data indicate that in Ulixertinib cost some viral infections, antibody binding to viral antigens expressed on the cell surface can modulate viral replication within cells. For example, treatment of alphavirus-infected rat neurons with monoclonal antibodies to E2 envelope protein was found to mediate viral clearance from the neurons28; antibodies to measles virus added to virus-infected cells were shown to interfere with viral protein expression inside the cells29; the addition of pseudorabies-specific immunoglobulins to pseudorabies-infected monocytes induced internalization of plasma membrane–bound viral protein via endocytosis.30 A different type of antibody-mediated interaction with infected cells was Selleck DAPT observed by IgA anti-hemagglutinin antibodies.31 Polymeric IgA anti-hemagglutinin was found to be actively transported

into epithelial cells by polymeric Ig receptor and to mediate intracellular neutralization of influenza virus by binding to viral proteins within the cell and preventing viral assembly.31 This study reveals that the antiviral effect of anti-HBs against HBV involves not only binding of viral particles in the circulation, but it also involves intracellular antiviral

activity by blocking viral particle release from the cells. We previously demonstrated that anti-HBs is endocytosed into hepatocyte-derived cell lines regardless of the presence or absence of HBsAg.10 This is likely to occur as a receptor-mediated endocytosis of IgG via the major histocompatibility complex class I–like Fc-receptor, FcRn. We have shown that FcRn Ribonuclease T1 is expressed on several liver cell lines and Fc elimination abrogated the IgG biding to the cells, as well as its effect on HBsAg secretion.10 FcRn is the transport receptor for IgG and protects IgG from catabolism after entry into cells.32, 33 This process is likely to operate during chronic HBV infection, because anti-envelope antibodies have been detected in the serum of virtually all patients with chronic hepatitis B, when sensitive assays are used.34 Intracellular binding and blocking the secretion of HBV particles may have a role for containment of HBV when it is present at low level within cells, for example, in subjects with spontaneously resolved HBV infection35 or in liver transplant recipients having effective long-term hepatitis B Ig prophylaxis without clinical HBV recurrence.9, 36 The antiviral activity of HBV-neutralizing antibodies may have clinical implications for treatment of chronic hepatitis B. Posttreatment rebound of HBV replication occurs frequently after stopping direct antivirals even after prolonged treatment for many years.

Arrebola, Nicolás Olea, Javier Fernández-Mena, Jorge L. González-Calvin

Understanding the genetics of NASH will aid in unraveling its pathogenesis. Aim: To identify gene networks and pathways in NASH. Methods: Hepatic gene expression was performed using Affymetrix Human Gene 1.0 Array in 10 this website women undergoing bariatric surgery (4 NASH; 4 Bland Steatosis [BS]; 2 normal liver). Expression profiles were compared with ANOVA. Genes with > 1.5-fold change between NASH vs BS; and NASH vs Normal, were analyzed by Ingenuity Pathways. Results: Mean age was 37±10 years and median BMI: 52 kg/m2[IQR, 46-58]. All were non-diabetic. Median NAS was 3 [IQR, 2-4]. Most patients had no fibrosis (70%); 30% had Stage 1. No single gene reached statistical significance after genomewide adjustment. There were 95 genes with >1.5-fold change in expression between NASH vs BS and these were analyzed with canonical pathway analysis yielding the following pathways: LXR/RXR Activation (p 0.008); PXR/RXR Activation (p 0.008); LPS/IL-1 Mediated Inhibition of RXR Function (p 0.002); Glutathione-Mediated Detoxification (p 0.009); Valine Degradation (p 0.005). In gene network analyses, the significant cellular/molecular biological functions associated with the NASH genes were: Lipid Metabolism (p 0.0001-0.04); Molecular Transport (p 0.0001-0.04); Small Molecule Biochemistry (p 0.0001-0.04); Amino Acid

Metabolism (p 0.001-0.03); Cellular Development Rapamycin research buy PFKL (p 0.002-0.04). The top scoring gene network in the comparison

of NASH vs BS is outlined in the Table. We also identified 448 genes with >1.5-fold change in expression between NASH vs Normal liver and the top scoring gene network in this comparison is also demonstrated in the Table. Conclusion: These data reveal canonical pathways, gene networks, and biological functions associated with NASH in patients undergoing bariatric surgery, demonstrating the utility of gene pathway analyses to facilitate identification of higher priority target candidates in NASH. Disclosures: The following people have nothing to disclose: Kiran Bambha, Jonathan A. Schoen, Kevin Rothchild, Susan C. Hartley, Linling Cheng, Lucy Golden-Mason, Ivana Yang, Hugo R. Rosen AIM: To validate in clinical practice the potential of NASHMRi as a non-invasive method for the diagnosis of steatohepatitis in patients with non-alcoholic fatty liver disease (NAFLD). METHODS: Seventy-seven consecutive patients suffering from biopsy-proven NAFLD were included, mean age 51 + 14 years, 62% male, 39 patients showed steatohepatitis. One non-contrast-enhanced MRI protocol was performed using 1.5 Tesla General Electric MRI (n=41) and Philips MRI system (n=36). Optical analysis and architectural neural networks was used to define NASHMRi [Estimators E28, E42, E48, 74] as previously reported (Gallego-Durán et al. J Hepatol 2013;58:S8). RESULTS: Eighty-one patients were recruited for the study.

A RediPlate 96 EnzChek Tyrosine Phosphatase Assay Kit (R-22067) was used for SHP-1 activity assay (Molecular Probes, Invitrogen, Carlsbad, CA). For the subcutaneous (SC) model (n = 10), each mouse was inoculated SC in the dorsal flank with 1 × 106 PLC5 cells suspended in 0.1 mL of serum-free medium containing

50% Matrigel (BD Biosciences, Bedford, MA). When tumors reached 100-200 mm3, mice received sorafenib, SC-43, or SC-40 (10 mg/kg per oral, once-daily). Tumors were measured twice-weekly using calipers, and their volumes were calculated using the following standard formula: width × length × height × 0.523. For the orthotopic find more model (n = 6), mice were inoculated into the liver directly

with luc2-expressed PLC5 cells. The treatment initiates when the luciferase activity of mice can be monitored. Mice were randomized into vehicle, sorafenib (10 mg/kg/day), and SC-43 (10 mg/kg/day). The survival curve was determined by the endpoint of treatment. Other extensive methods were moved to a Supporting Information section. Comparisons of mean values were performed using the independent samples t test in SPSS for Windows 11.5 software (SPSS, Inc., Chicago, IL). Sorafenib significantly enhanced the phosphatase activity of SHP-1 in a dose-dependent manner in all tested HCC cell lines (Fig. 1A). Sorafenib activated Palbociclib SHP-1 in SHP-1-containing IP extract at very low concentrations (nM), whereas the activity was not affected in SHP-1 catalytic dead mutant (C453S)-expressing cell extract Baricitinib (Fig. 1B). Incubation of sorafenib with cell-free SHP-1 proteins increased SHP-1 activity significantly at low concentrations (Fig. 1C), suggesting that sorafenib activates SHP-1 through direct interaction with SHP-1 proteins. Notably, sorafenib did not alter interactions between SHP-1 and STAT3 (Fig. 1D), although sorafenib down-regulated p-STAT3-related proteins in HCC cell lines in a dose-dependent manner (Fig. 1E). Sorafenib-treatment in PLC5 with high levels of SHP-1 showed more inhibition of p-STAT3 and induced more apoptosis (Fig.

1F). Otherwise, sorafenib did not alter the activity of SHP-2 significantly either in HCC cell lines or purified SHP-2 proteins (Supporting Fig. 1). These data suggest that SHP-2 is not a major target of sorafenib. Next, we generated a series of domain-deletion mutants of SHP-1 and further assayed their phosphatase activity and susceptibility to dephosphorylation of STAT3 (Fig. 2A). Notably, the intramolecular inhibition of SHP-1 is protected by various biochemical associations between N1 and the PTP catalytic domain, such as Asp61 and Lys362 (salt bridge).[11] The dN1 or D61A mutants demonstrated significantly increased SHP-1 activity, indicating that these two mutants mimic the open conformation and serve as constitutive activators (Fig. 2B).

In addition to assessments of efficacy, clinical trials that evaluate treatment moderators and mechanisms of action are essential, given our

click here limited knowledge in this area. Many patients with headache and headache medicine practitioners use or recommend evidence-based behavioral interventions and mind/body interventions to manage headache pain, but many unanswered questions remain. In consideration of unique methodological challenges that arise from the complex nature of the non-pharmacological interventions under study, we have outlined key research questions and goals for future studies in hopes of furthering the evaluation and dissemination of these interventions for patients with primary headache disorders. Research http://www.selleckchem.com/products/PLX-4032.html that adheres to published guideline recommendations and is designed to properly answer key questions is most likely to lead to progress in these goals. “
“Background.— Neuromodulators such as topiramate (TPM) and divalproex sodium (DVS) are effective in the preventive treatment of migraine. Nonetheless, patients often discontinue their use due to side effects. Objectives.—

The study aims to determine whether the combination of lower doses of TPM and DVS may be useful for patients responsive to higher doses of the individual drugs but experiencing intolerable side effects. Methods.— This clinic-based study was conducted to evaluate a series of patients who experienced at least a 50% reduction in headache frequency after 6 weeks of treatment with either TPM 100 mg/day or DVS 750 mg/day, but suffered intolerable

drug-related side effects. At that point, patients were switched to TPM (50 mg in the morning and 25 mg at night) plus DVS 500 mg/day (single O-methylated flavonoid dose) and reevaluated after 6 further weeks. Results.— Thirty-eight patients were evaluated. Mean age was 37 years, and 84% were female. Of the 38, 17 (77.3%) initially were using TPM only, and 10 (62.5%) initially were using DVS only. After 6 weeks on combination therapy, 27 (62.9%) reported improved tolerability without any decrease in efficacy. Five patients who initially were using TPM only and six using DVS only failed to return for follow-up or were noncompliant with treatment due to persistent or worsening side effects. Conclusions.— This small, open-label study suggests that the combination of TPM and DVS in doses lower than those typically used for migraine prophylaxis may be an effective option for patients who benefited from higher doses of these same medications used as monotherapy but were unable to tolerate such treatment due to side effects. “
“We sought to assess the experiences, growth, and distribution of accredited headache medicine fellowships since accreditation began in 2007, and to examine the number and current practice locations of fellows graduated from those programs.

1). In addition, we review currently available strategies that might be used to target the HSC activation process in the treatment of liver metastases. α-SMA, alpha-smooth muscle actin; EC, endothelial cells; ECM, extracellular matrix; HCC, hepatocellular carcinoma; HGF, hepatocyte growth factor; HSC, hepatic stellate cell; PDGF, platelet-derived click here growth factor; MMP, matrix metalloproteinase; NO, nitric oxide; SDF-1, stromal cell-derived factor 1; TGF-β, transforming growth factor β; TIMP, tissue inhibitor of metalloproteinases; VEGF, vascular endothelial growth factor. Why do tumor cells preferentially metastasize to the liver?

Two theories have been developed to explain the organ-specific spreading of cancer cells: (1) the Seed and Soil Theory, developed by Paget in 1889, which proposed that it was due to the dependence of the seeds (the cancer cells) on the soil (specific organs),7-9 and (2) Ewing’s Theory, developed in the 1920s, which hypothesized that mechanical factors (circulatory patterns, blood flow patterns, and nonspecific trapping of cancer cells by the first capillary bed that they encounter) were sufficient for organ-specific metastasis.9, 10 However,

recent studies have suggested that these two theories are not mutually exclusive, and that both mechanical and seed-soil compatibility factors may DAPT chemical structure contribute to the ability of cancer cells to metastasize to specific organs such as the liver.1, 9 The combination of hemodynamic features of the liver and its unique microenvironment makes the liver one of the most targeted organs by cancer metastases. The liver is able to arrest circulating cancer cells (particularly gastrointestinal cancer cells) efficiently, because of its specific location and the slow and tortuous blood acetylcholine flow in the sinusoidal capillaries. However, not all tumor cells retained in the liver develop into metastases. Indeed,

liver metastasis is a very inefficient process: an experimental liver metastasis model showed that less than 0.02% of intraportally injected B16F1 melanoma cells developed into macroscopic tumors in the mouse liver.11 Before they develop into macroscopic metastases, tumor cells must go through multiple selective steps in the liver, including (1) survival of anoikis or the innate immune response, (2) extravasation into the parenchyma, (3) formation of preangiogenic micrometastases, and finally (4) development of angiogenesis and macroscopic tumors.1, 2 Of all the steps, initiation of the growth of extravasated cancer cells and the development of macroscopic tumors from preangiogenic micrometastases are considered as rate-limiting.11 This suggests that liver metastases are highly dependent on the interactions between tumor cells (or tumor stem cells) and tumor-activated stromal factors in the liver.

1). In addition, we review currently available strategies that might be used to target the HSC activation process in the treatment of liver metastases. α-SMA, alpha-smooth muscle actin; EC, endothelial cells; ECM, extracellular matrix; HCC, hepatocellular carcinoma; HGF, hepatocyte growth factor; HSC, hepatic stellate cell; PDGF, platelet-derived selleck chemical growth factor; MMP, matrix metalloproteinase; NO, nitric oxide; SDF-1, stromal cell-derived factor 1; TGF-β, transforming growth factor β; TIMP, tissue inhibitor of metalloproteinases; VEGF, vascular endothelial growth factor. Why do tumor cells preferentially metastasize to the liver?

Two theories have been developed to explain the organ-specific spreading of cancer cells: (1) the Seed and Soil Theory, developed by Paget in 1889, which proposed that it was due to the dependence of the seeds (the cancer cells) on the soil (specific organs),7-9 and (2) Ewing’s Theory, developed in the 1920s, which hypothesized that mechanical factors (circulatory patterns, blood flow patterns, and nonspecific trapping of cancer cells by the first capillary bed that they encounter) were sufficient for organ-specific metastasis.9, 10 However,

recent studies have suggested that these two theories are not mutually exclusive, and that both mechanical and seed-soil compatibility factors may Z-VAD-FMK concentration contribute to the ability of cancer cells to metastasize to specific organs such as the liver.1, 9 The combination of hemodynamic features of the liver and its unique microenvironment makes the liver one of the most targeted organs by cancer metastases. The liver is able to arrest circulating cancer cells (particularly gastrointestinal cancer cells) efficiently, because of its specific location and the slow and tortuous blood N-acetylglucosamine-1-phosphate transferase flow in the sinusoidal capillaries. However, not all tumor cells retained in the liver develop into metastases. Indeed,

liver metastasis is a very inefficient process: an experimental liver metastasis model showed that less than 0.02% of intraportally injected B16F1 melanoma cells developed into macroscopic tumors in the mouse liver.11 Before they develop into macroscopic metastases, tumor cells must go through multiple selective steps in the liver, including (1) survival of anoikis or the innate immune response, (2) extravasation into the parenchyma, (3) formation of preangiogenic micrometastases, and finally (4) development of angiogenesis and macroscopic tumors.1, 2 Of all the steps, initiation of the growth of extravasated cancer cells and the development of macroscopic tumors from preangiogenic micrometastases are considered as rate-limiting.11 This suggests that liver metastases are highly dependent on the interactions between tumor cells (or tumor stem cells) and tumor-activated stromal factors in the liver.

[47] The prevalence of anti-HEV IgG was significantly higher among individuals living in the northern part of Japan (Hokkaido, Tohoku, Kanto and Chubu) than among those living in the southern part of Japan (Kinki, Chugoku, Shikoku and Kyushu) (6.7% vs 3.2%, P < 0.0001). Notably, the prevalence of anti-HEV IgG was significantly higher among males than among females in all eight regions of Japan (Fig. 2). All but one individual with

HEV RNA or anti-HEV IgM and/or anti-HEV IgA lived in the northern part of Japan. In other words, the prevalence of HEV RNA or anti-HEV IgM and/or anti-HEV IgA was also significantly higher among individuals living in the northern part of Japan than among those living in the southern part of Japan (15/13 182 [0.11%] vs 1/8845 [0.01%], P = 0.0056]. Similar regional Selleckchem Acalabrutinib differences in the anti-HEV IgG prevalence rate also have been found in blood donors in Japan.[51] Of interest, when the prevalence rate of anti-HEV IgG was compared with the number of pigs raised on swine farms in each of the 30 prefectures studied (http://www.maff.go.jp/j/tokei/kouhyou/tikusan/index.html), a positive correlation was observed (correlation coefficient = 0.5104). The prevalence rate

of anti-HEV IgG also correlated closely with the monthly expenditure for pork in each prefecture (http://www2.ttcn.ne.jp/~honkawa/7238.html) ALK tumor (correlation coefficient = 0.5102). These observations may explain the regional differences in the prevalence of HEV infection in Japan, and support the importance of pigs as reservoirs for HEV infection in humans. In 2003, we summarized the clinical courses and symptoms of domestic HEV infections in Japan,[10] by analyzing 46 Japanese patients who were diagnosed with hepatitis E in our laboratory based on the

presence of both anti-HEV IgM and HEV RNA in their sera that had been obtained at ifenprodil admission, including 11 of 87 (13%) patients who had previously been diagnosed with sporadic acute hepatitis of non-ABC etiology[8] and three of 18 (17%) patients who had received a diagnosis of fulminant hepatitis of unknown etiology.[9] Until the end of 2012, we had an opportunity to diagnose hepatitis E in 153 additional patients who had neither history of travel to endemic areas nor contact with travelers abroad or foreigners within 3 months before disease onset. In this review, we therefore summarize the characteristics of 199 domestic hepatitis E cases in Japan, in comparison to eight patients with imported hepatitis E (Table 1). To diagnose hepatitis E, serum samples were tested for the presence of anti-HEV IgG, IgM and IgA by an in-house enzyme-linked immunoassay (ELISA) with recombinant ORF2 protein,[52] as well as for HEV RNA by nested reverse transcription polymerase chain reaction (RT–PCR) with primers targeting the ORF2 region.

[47] The prevalence of anti-HEV IgG was significantly higher among individuals living in the northern part of Japan (Hokkaido, Tohoku, Kanto and Chubu) than among those living in the southern part of Japan (Kinki, Chugoku, Shikoku and Kyushu) (6.7% vs 3.2%, P < 0.0001). Notably, the prevalence of anti-HEV IgG was significantly higher among males than among females in all eight regions of Japan (Fig. 2). All but one individual with

HEV RNA or anti-HEV IgM and/or anti-HEV IgA lived in the northern part of Japan. In other words, the prevalence of HEV RNA or anti-HEV IgM and/or anti-HEV IgA was also significantly higher among individuals living in the northern part of Japan than among those living in the southern part of Japan (15/13 182 [0.11%] vs 1/8845 [0.01%], P = 0.0056]. Similar regional click here differences in the anti-HEV IgG prevalence rate also have been found in blood donors in Japan.[51] Of interest, when the prevalence rate of anti-HEV IgG was compared with the number of pigs raised on swine farms in each of the 30 prefectures studied (http://www.maff.go.jp/j/tokei/kouhyou/tikusan/index.html), a positive correlation was observed (correlation coefficient = 0.5104). The prevalence rate

of anti-HEV IgG also correlated closely with the monthly expenditure for pork in each prefecture (http://www2.ttcn.ne.jp/~honkawa/7238.html) GDC-0068 (correlation coefficient = 0.5102). These observations may explain the regional differences in the prevalence of HEV infection in Japan, and support the importance of pigs as reservoirs for HEV infection in humans. In 2003, we summarized the clinical courses and symptoms of domestic HEV infections in Japan,[10] by analyzing 46 Japanese patients who were diagnosed with hepatitis E in our laboratory based on the

presence of both anti-HEV IgM and HEV RNA in their sera that had been obtained at Gefitinib admission, including 11 of 87 (13%) patients who had previously been diagnosed with sporadic acute hepatitis of non-ABC etiology[8] and three of 18 (17%) patients who had received a diagnosis of fulminant hepatitis of unknown etiology.[9] Until the end of 2012, we had an opportunity to diagnose hepatitis E in 153 additional patients who had neither history of travel to endemic areas nor contact with travelers abroad or foreigners within 3 months before disease onset. In this review, we therefore summarize the characteristics of 199 domestic hepatitis E cases in Japan, in comparison to eight patients with imported hepatitis E (Table 1). To diagnose hepatitis E, serum samples were tested for the presence of anti-HEV IgG, IgM and IgA by an in-house enzyme-linked immunoassay (ELISA) with recombinant ORF2 protein,[52] as well as for HEV RNA by nested reverse transcription polymerase chain reaction (RT–PCR) with primers targeting the ORF2 region.

It is difficult and expensive to perform full cohort serum analyses, whereas the nested case-control design utilized here can provide substantial reductions in cost and effort with little loss of statistical efficiency.36 Another major strength of our study is that it incorporated, in a strict and in-depth manner, hepatitis virus infection status and HCC cases were identified through the Hiroshima Tumor and Tissue Registry and Nagasaki Cancer Registry,

supplemented by additional cases detected by way of pathological review of related diseases.26 A limitation of our study is that the joint effects of radiation and hepatitis virus infection could not be estimated from the standpoint of causality. As discussed previously, HBV and possibly HCV infection may act as intermediate risk factors in radiation-associated HCC. Previous studies have consistently demonstrated PD0325901 molecular weight that prevalence of HBsAg increases with radiation dose within the AHS,17-19 although no dose response for anti-HCV Ab has been detected.20 Therefore, when the risk of HCC for radiation is estimated while

controlling for HBV infection, some of the radiation risk may be absorbed in the coefficient for HBV infection. In other words, the radiation risk coefficient does not represent Selleckchem Bortezomib the radiation effect independent of mediation by HBV infection and the HCC risk for HBV infection itself is not correctly estimated, because the actual causal pathway is not explicitly modeled. In addition, we cannot easily disentangle the joint effects of radiation and HBV infection

using standard regression models, because HBV infection is not a true confounding risk factor but an intermediate risk factor. Nevertheless, that the radiation risk did not decrease with concomitant adjustment for viral infection suggests that the practical extent of mediation may be small. We are currently developing methods of statistical analysis that jointly consider the dose response for the intermediate viral factor as well many as the joint risk of HCC for both hepatitis virus infection and radiation in the countermatched, nested case-control design. In conclusion, radiation exposure was associated with increased risk of HCC, even after adjusting for HBV or HCV infection, alcohol consumption, BMI, and smoking habit. Moreover, radiation exposure was an independent risk factor for non-B, non-C HCC with no apparent confounding by alcohol consumption, BMI, or smoking habit. The mechanistic form of joint effects of radiation and HBV or HCV infection on HCC risk could not be estimated, but the development of new statistical methods that jointly consider the dose response for the intermediate viral factor will make such an analysis possible in the future.