Non-B hepatocellular carcinoma: influence of age, sex, alcohol, family clustering, blood transfusion and chronic liver disease.

In 144 cases of hepatocellular carcinoma (HCC), 166 cases of cirrhosis without HCC and 142 cases of chronic hepatitis, we examined HBsAg, anti-HBs and anti-HBc in sera and compared the following factors between hepatitis B virus marker-negative and -positive patients: age, sex, alcohol consumption, family clustering of liver diseases, and histories of blood transfusion and post-transfusion hepatitis. Results of this study demonstrated several distinct differences in clinical backgrounds between non-B (negative for HBsAg, anti-HBs and anti-HBc) and B (positive for HBsAg) patients with HCC. Non-B patients were significantly older, had a lower frequency of familial tendencies for liver diseases, and more frequently had cancers other than HCC in their families. Some of these differences were also observed between non-B and B patients with cirrhosis and chronic hepatitis. Among patients with chronic hepatitis, the non-B patients had received blood transfusion or had post-transfusion hepatitis more frequently than the B patients. However, this difference was not apparent in patients with liver cirrhosis or HCC, suggesting that progression of non-A, non-B post-transfusion hepatitis to cirrhosis and HCC may not be as frequent as progression to chronic hepatitis.</p

Astellas' Drug Discovery Strategy: Focus on Oncology

Based on the goal of delivering innovative and reliable pharmaceutical products to cancer patients for whom no effective treatments exist, Astellas is focusing its efforts on a strategy of precision medicine in its drug discovery which is carried out at three research sites with diversity in their research platforms and research styles

Clinical and histological features of sporadic non-A, non-B hepatitis.

The incidence of hepatitis A (HA), hepatitis B (HB), and non-A, non-B hepatitis (NANBH) was 27%, 30% and 43% among 73 patients with sporadic hepatitis. Epidemiological data (geographical distribution, seasonal variation, age, sex, and occupation) were not distinguishing of the type of hepatitis. Neither intrafamilial infection nor previous contact with viral hepatitis patients could be demonstrated in the NANBH cases. Fever and jaundice were less frequent in NANBH than in HA. Maximum levels of SGPT, serum bilirubin, ZTT, and gamma-globulin were significantly lower in NANBH than in HA and HB. Ten of 29 NANBH patients (35%) presented abnormal SGPT activities for more than 6 months, and four (14%) more than 12 months. In the ten patients with prolonged courses, jaundice was more frequent and maximum levels of SGPT were higher than in patients with transient courses. Histopathologic findings were not markedly different from those of HA and HB. Bile duct damage, fatty deposition, and giant multi-nucleated cells were recognized in 6, 12, and 2 NANBH patients, respectively. There were no characteristic ultrastructural changes in NANBH.</p

Physiological modeling of isoprene dynamics in exhaled breath

Human breath contains a myriad of endogenous volatile organic compounds (VOCs) which are reflective of ongoing metabolic or physiological processes. While research into the diagnostic potential and general medical relevance of these trace gases is conducted on a considerable scale, little focus has been given so far to a sound analysis of the quantitative relationships between breath levels and the underlying systemic concentrations. This paper is devoted to a thorough modeling study of the end-tidal breath dynamics associated with isoprene, which serves as a paradigmatic example for the class of low-soluble, blood-borne VOCs. Real-time measurements of exhaled breath under an ergometer challenge reveal characteristic changes of isoprene output in response to variations in ventilation and perfusion. Here, a valid compartmental description of these profiles is developed. By comparison with experimental data it is inferred that the major part of breath isoprene variability during exercise conditions can be attributed to an increased fractional perfusion of potential storage and production sites, leading to higher levels of mixed venous blood concentrations at the onset of physical activity. In this context, various lines of supportive evidence for an extrahepatic tissue source of isoprene are presented. Our model is a first step towards new guidelines for the breath gas analysis of isoprene and is expected to aid further investigations regarding the exhalation, storage, transport and biotransformation processes associated with this important compound.Comment: 14 page

Trace species detection in the near infrared using Fourier transform broadband cavity enhanced absorption spectroscopy: Initial studies on potential breath analytes

Cavity enhanced absorption measurements have been made of several species that absorb light between 1.5 and 1.7 µm using both a supercontinuum source and superluminescent light emitting diodes. A system based upon an optical enhancement cavity of relatively high finesse, consisting of mirrors of reflectivity ∼99.98%, and a Fourier transform spectrometer, is demonstrated. Spectra are recorded of isoprene, butadiene, acetone and methane, highlighting problems with spectral interference and unambiguous concentration determinations. Initial results are presented of acetone within a breath-like matrix indicating ppm precision at &lt;∼10 ppm acetone levels. Instrument sensitivities are sufficiently enhanced to enable the detection of atmospheric levels of methane. Higher detection sensitivities are achieved using the supercontinuum source, with a minimum detectable absorption coefficient of ∼4 × 10(-9) cm(-1) reported within a 4 min acquisition time. Finally, two superluminescent light emitting diodes are coupled together to increase the wavelength coverage, and measurements are made simultaneously on acetylene, CO(2), and butadiene. The absorption cross-sections for acetone and isoprene have been measured with an instrumental resolution of 4 cm(-1) and are found to be 1.3 ± 0.1 × 10(-21) cm(2) at a wavelength of 1671.9 nm and 3.6 ± 0.2 × 10(-21) cm(2) at 1624.7 nm, respectively

Integrating Statistical Predictions and Experimental Verifications for Enhancing Protein-Chemical Interaction Predictions in Virtual Screening

Predictions of interactions between target proteins and potential leads are of great benefit in the drug discovery process. We present a comprehensively applicable statistical prediction method for interactions between any proteins and chemical compounds, which requires only protein sequence data and chemical structure data and utilizes the statistical learning method of support vector machines. In order to realize reasonable comprehensive predictions which can involve many false positives, we propose two approaches for reduction of false positives: (i) efficient use of multiple statistical prediction models in the framework of two-layer SVM and (ii) reasonable design of the negative data to construct statistical prediction models. In two-layer SVM, outputs produced by the first-layer SVM models, which are constructed with different negative samples and reflect different aspects of classifications, are utilized as inputs to the second-layer SVM. In order to design negative data which produce fewer false positive predictions, we iteratively construct SVM models or classification boundaries from positive and tentative negative samples and select additional negative sample candidates according to pre-determined rules. Moreover, in order to fully utilize the advantages of statistical learning methods, we propose a strategy to effectively feedback experimental results to computational predictions with consideration of biological effects of interest. We show the usefulness of our approach in predicting potential ligands binding to human androgen receptors from more than 19 million chemical compounds and verifying these predictions by in vitro binding. Moreover, we utilize this experimental validation as feedback to enhance subsequent computational predictions, and experimentally validate these predictions again. This efficient procedure of the iteration of the in silico prediction and in vitro or in vivo experimental verifications with the sufficient feedback enabled us to identify novel ligand candidates which were distant from known ligands in the chemical space