Absolute quantitation of DNA methylation of 28 candidate genes in prostate cancer using pyrosequencing

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Aberrant DNA methylation plays a pivotal role in carcinogenesis and its mapping is likely to provide biomarkers for improved diagnostic and risk assessment in prostate cancer (PCa). We quantified and compared absolute methylation levels among 28 candidate genes in 48 PCa and 29 benign prostate hyperplasia (BPH) samples using the pyrosequencing (PSQ) method to identify genes with diagnostic and prognostic potential. RARB, HIN1, BCL2, GSTP1, CCND2, EGFR5, APC, RASSF1A, MDR1, NKX2-5, CDH13, DPYS, PTGS2, EDNRB, MAL, PDLIM4, HLAa, ESR1 and TIG1 were highly methylated in PCa compared to BPH (p < 0.001), while SERPINB5, CDH1, TWIST1, DAPK1, THRB, MCAM, SLIT2, CDKN2a and SFN were not. RARB methylation above 21% completely distinguished PCa from BPH. Separation based on methylation level of SFN, SLIT2 and SERPINB5 distinguished low and high Gleason score cancers, e.g. SFN and SERPINB5 together correctly classified 81% and 77% of high and low Gleason score cancers respectively. Several genes including CDH1 previously reported as methylation markers in PCa were not confirmed in our study. Increasing age was positively associated with gene methylation (p < 0.0001). Accurate quantitative measurement of gene methylation in PCa appears promising and further validation of genes like RARB, HIN1, BCL2, APC and GSTP1 is warranted for diagnostic potential and SFN, SLIT2 and SERPINB5 for prognostic potential

The Group Loss for Deep Metric Learning

Deep metric learning has yielded impressive results in tasks such as clustering and image retrieval by leveraging neural networks to obtain highly discriminative feature embeddings, which can be used to group samples into different classes. Much research has been devoted to the design of smart loss functions or data mining strategies for training such networks. Most methods consider only pairs or triplets of samples within a mini-batch to compute the loss function, which is commonly based on the distance between embeddings. We propose Group Loss, a loss function based on a differentiable label-propagation method that enforces embedding similarity across all samples of a group while promoting, at the same time, low-density regions amongst data points belonging to different groups. Guided by the smoothness assumption that "similar objects should belong to the same group", the proposed loss trains the neural network for a classification task, enforcing a consistent labelling amongst samples within a class. We show state-of-the-art results on clustering and image retrieval on several datasets, and show the potential of our method when combined with other techniques such as ensemblesComment: Accepted to European Conference on Computer Vision (ECCV) 2020, includes non-archival supplementary materia

Efficient Colonization and Therapy of Human Hepatocellular Carcinoma (HCC) Using the Oncolytic Vaccinia Virus Strain GLV-1h68

Virotherapy using oncolytic vaccinia virus strains is one of the most promising new strategies for cancer therapy. In this study, we analyzed for the first time the therapeutic efficacy of the oncolytic vaccinia virus GLV-1h68 in two human hepatocellular carcinoma cell lines HuH7 and PLC/PRF/5 (PLC) in cell culture and in tumor xenograft models. By viral proliferation assays and cell survival tests, we demonstrated that GLV-1h68 efficiently colonized, replicated in, and did lyse these cancer cells in culture. Experiments with HuH7 and PLC xenografts have revealed that a single intravenous injection (i.v.) of mice with GLV-1h68 resulted in a significant reduction of primary tumor sizes compared to uninjected controls. In addition, replication of GLV-1h68 in tumor cells led to strong inflammatory and oncolytic effects resulting in intense infiltration of MHC class II-positive cells like neutrophils, macrophages, B cells and dendritic cells and in up-regulation of 13 pro-inflammatory cytokines. Furthermore, GLV-1h68 infection of PLC tumors inhibited the formation of hemorrhagic structures which occur naturally in PLC tumors. Interestingly, we found a strongly reduced vascular density in infected PLC tumors only, but not in the non-hemorrhagic HuH7 tumor model. These data demonstrate that the GLV-1h68 vaccinia virus may have an enormous potential for treatment of human hepatocellular carcinoma in man

Estimation of cancer incidence and mortality attributable to alcohol drinking in china

Background. Cancer constitutes a serious burden of disease worldwide and has become the second leading cause of death in China. Alcohol consumption is causally associated with the increased risk of certain cancers. Due to the current lack of data and the imperative need to guide policymakers on issues of cancer prevention and control, we aim to estimate the role of alcohol on the cancer burden in China in 2005. Methods. We calculated the proportion of cancers attributable to alcohol use to estimate the burden of alcohol-related cancer. The population attributable fraction was calculated based on the assumption of no alcohol drinking. Data on alcohol drinking prevalence were from two large-scale national surveys of representative samples of the Chinese population. Data on relative risk were obtained from meta-analyses and large-scale studies. Results. We found that a total of 78,881 cancer deaths were attributable to alcohol drinking in China in 2005, representing 4.40% of all cancers (6.69% in men, 0.42% in women). The corresponding figure for cancer incidence was 93,596 cases (3.63% of all cancer cases). Liver cancer was the main alcohol-related cancer, contributing more than 60% of alcohol-related cancers. Conclusions. Particular attention needs to be paid to the harm of alcohol as well as its potential benefits when making public health recommendations on alcohol drinking. \ua9 2010 Liang et al; licensee BioMed Central Ltd

Clinical Presentation of Hepatocellular Carcinoma (HCC) in Asian-Americans Versus Non-Asian-Americans

The incidence of HCC is rising worldwide. Studies on ethnicity-based clinical presentation of HCC remain limited. The aim is to compare the clinical presentation and stage of HCC between Asian-Americans and non-Asian-Americans. This retrospective study assessed ethnicity-based differences in HCC presentation, including demographics, laboratory results, diagnosis of underlying liver disease, and stage of HCC. Of 276 patients, 162 were Asian-Americans and 114 were non-Asian-Americans. Compared to non-Asian-Americans, Asian-Americans had a significantly higher incidence of history of hepatitis B virus (HBV) infection (55.0% vs. 4.9%, P < 0.001), family history of HBV infection (12.5% vs. 0.0%, P < 0.001) and HCC (15.2% vs. 2.9%, P = 0.002), but lower incidence of history of hepatitis C virus (HCV) infection (37.5% vs. 61.6%, P < 0.001). At diagnosis of HCC, Asian-American patients had a significantly lower frequency of hepatic encephalopathy (8.9% vs. 29.3%, P = 0.001), and ascites (26.7% vs. 57.3%, P < 0.001). Asian-Americans had lower Child-Pugh scores (class A: 62.0% vs. 31.4%, P < 0.001), and MELD scores (9.2 ± 4.4 vs. 12.0 ± 6.4, P = 0.02), and presented with a lower stage of HCC by Okuda staging (I: 43.8% vs. 22.8%, P = 0.001). Asian-American patients with HCC presented with a higher incidence of history and family history of HBV infection, lower incidence of hepatic decompensation, lower Child and MELD scores, and an early stage HCC disease

A facile chemical conversion synthesis of Sb2S3 nanotubes and the visible light-driven photocatalytic activities

We report a simple chemical conversion and cation exchange technique to realize the synthesis of Sb2S3 nanotubes at a low temperature of 90°C. The successful chemical conversion from ZnS nanotubes to Sb2S3 ones benefits from the large difference in solubility between ZnS and Sb2S3. The as-grown Sb2S3 nanotubes have been transformed from a weak crystallization to a polycrystalline structure via successive annealing. In addition to the detailed structural, morphological, and optical investigation of the yielded Sb2S3 nanotubes before and after annealing, we have shown high photocatalytic activities of Sb2S3 nanotubes for methyl orange degradation under visible light irradiation. This approach offers an effective control of the composition and structure of Sb2S3 nanomaterials, facilitates the production at a relatively low reaction temperature without the need of organics, templates, or crystal seeds, and can be extended to the synthesis of hollow structures with various compositions and shapes for unique properties

Investigation on two abnormal phenomena about thermal conductivity enhancement of BN/EG nanofluids

The thermal conductivity of boron nitride/ethylene glycol (BN/EG) nanofluids was investigated by transient hot-wire method and two abnormal phenomena was reported. One is the abnormal higher thermal conductivity enhancement for BN/EG nanofluids at very low-volume fraction of particles, and the other is the thermal conductivity enhancement of BN/EG nanofluids synthesized with large BN nanoparticles (140 nm) which is higher than that synthesized with small BN nanoparticles (70 nm). The chain-like loose aggregation of nanoparticles is responsible for the abnormal increment of thermal conductivity enhancement for the BN/EG nanofluids at very low particles volume fraction. And the difference in specific surface area and aspect ratio of BN nanoparticles may be the main reasons for the abnormal difference between thermal conductivity enhancements for BN/EG nanofluids prepared with 140- and 70-nm BN nanoparticles, respectively

A Classification Method Based on Principal Components of SELDI Spectra to Diagnose of Lung Adenocarcinoma

Lung cancer is the leading cause of cancer death worldwide, but techniques for effective early diagnosis are still lacking. Proteomics technology has been applied extensively to the study of the proteins involved in carcinogenesis. In this paper, a classification method was developed based on principal components of surface-enhanced laser desorption/ionization (SELDI) spectral data. This method was applied to SELDI spectral data from 71 lung adenocarcinoma patients and 24 healthy individuals. Unlike other peak-selection-based methods, this method takes each spectrum as a unity. The aim of this paper was to demonstrate that this unity-based classification method is more robust and powerful as a method of diagnosis than peak-selection-based methods.The results showed that this classification method, which is based on principal components, has outstanding performance with respect to distinguishing lung adenocarcinoma patients from normal individuals. Through leaving-one-out, 19-fold, 5-fold and 2-fold cross-validation studies, we found that this classification method based on principal components completely outperforms peak-selection-based methods, such as decision tree, classification and regression tree, support vector machine, and linear discriminant analysis.The classification method based on principal components of SELDI spectral data is a robust and powerful means of diagnosing lung adenocarcinoma. We assert that the high efficiency of this classification method renders it feasible for large-scale clinical use

Diagnostic value of fine-needle aspiration biopsy for breast mass: a systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>Fine-needle aspiration biopsy (FNAB) of the breast is a minimally invasive yet maximally diagnostic method. However, the clinical use of FNAB has been questioned. The purpose of our study was to establish the overall value of FNAC in the diagnosis of breast lesions.</p> <p>Methods</p> <p>After a review and quality assessment of 46 studies, sensitivity, specificity and other measures of accuracy of FNAB for evaluating breast lesions were pooled using random-effects models. Summary receiver operating characteristic curves were used to summarize overall accuracy. The sensitivity and specificity for the studies data (included unsatisfactory samples) and underestimation rate of unsatisfactory samples were also calculated.</p> <p>Results</p> <p>The summary estimates for FNAB in diagnosis of breast carcinoma were as follows (unsatisfactory samples was temporarily exluded): sensitivity, 0.927 (95% confidence interval [CI], 0.921 to 0.933); specificity, 0.948 (95% CI, 0.943 to 0.952); positive likelihood ratio, 25.72 (95% CI, 17.35 to 28.13); negative likelihood ratio, 0.08 (95% CI, 0.06 to 0.11); diagnostic odds ratio, 429.73 (95% CI, 241.75 to 763.87); The pooled sensitivity and specificity for 11 studies, which reported unsatisfactory samples (unsatisfactory samples was considered to be positive in this classification) were 0.920 (95% CI, 0.906 to 0.933) and 0.768 (95% CI, 0.751 to 0.784) respectively. The pooled proportion of unsatisfactory samples that were subsequently upgraded to various grade cancers was 27.5% (95% CI, 0.221 to 0.296).</p> <p>Conclusions</p> <p>FNAB is an accurate biopsy for evaluating breast malignancy if rigorous criteria are used. With regard to unsatisfactory samples, futher invasive procedures are required in order to minimize the chance of a missed diagnosis of breast cancer.</p