Growth Inhibition and Apoptosis with H31 Metabolites from Marine Bacillus SW31 in Head and Neck Cancer Cells

ObjectivesTo determine whether a novel marine micro-organism with anticancer properties, H31, the metabolic product of Bacillus SW31, has anti-tumor effects on head and neck cancer, and potential for apoptotic-enhancing anti-cancer treatment of affected patients.MethodsThe cell viability and apoptosis assays were performed. Changes in the signal pathway related to apoptosis were investigated. Then, the therapeutic effects of H31 were explored in mouse xenograft model and drug toxicity of H31 was examined in zebrafish model.ResultsWe identified the anticancer activity of H31, a novel metabolic product of Bacillus SW31. Bacillus SW31, a new marine micro-organism, has 70% homology with Bacillus firmus and contains potent cytotoxic bioactivity in head and neck cancer cells using MTT assay. Combined with c-JUN, p53, cytochrome C, and caspase-3, H31 induced apoptosis of KB cells, a head and neck cancer cell line. In a separate in vivo model, tumor growth in C3H/HeJ syngeneic mice was suppressed by H31. In addition, in a zebrafish model used for toxicity testing, a considerable dose of H31 did not result in embryo or neurotoxicity.ConclusionGrowth inhibition and apoptosis were achieved both in vitro and in vivo in head and neck cancer cells after exposure to H31, a metabolite from the marine Bacillus species, without any significant toxicity effects even at considerable H31 dose concentrations

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Optimal Length of Heart Rate Variability Data and Forecasting Time for Ventricular Fibrillation Prediction Using Machine Learning

Ventricular fibrillation (VF) is a cardiovascular disease that is one of the major causes of mortality worldwide, according to the World Health Organization. Heart rate variability (HRV) is a biomarker that is used for detecting and predicting life-threatening arrhythmias. Predicting the occurrence of VF in advance is important for saving patients from sudden death. We extracted features from seven HRV data lengths to predict the onset of VF before nine different forecast times and observed the prediction accuracies. By using only five features, an artificial neural network classifier was trained and validated based on 10-fold cross-validation. Maximum prediction accuracies of 88.18% and 88.64% were observed at HRV data lengths of 10 and 20 s, respectively, at a forecast time of 0 s. The worst prediction accuracy was recorded at an HRV data length of 70 s and a forecast time of 80 s. Our results showed that features extracted from HRV signals near the VF onset could yield relatively high VF prediction accuracies

Theoretical and experimental studies on the electronic structure of crystalline and amorphous ZnSnO3 thin films

The influence of structural disorder on the electronic structure of amorphous ZnSnO3 was examined by ab-initio calculations. The calculation results are compared with the experimental results using as-deposited and annealed ZnSnO3 films grown by atomic layer deposition. The O K-edge X-ray absorption spectroscopy, X-ray diffraction, and thin-film transistors were employed in the experiment. The conduction band minima of amorphous and crystalline ZnSnO3 mainly consisted of Sn 5s state, while a higher non-uniform localization of these states was observed in the amorphous phase compared with the crystalline counterpart. The experimental results coincide well with the theoretical results.(C) 2013 AIP Publishing LLC.110141sciescopu