Viral delivery of antioxidant genes as a therapeutic strategy in experimental models of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder with no effective treatment to date. Despite its multi-factorial aetiology, oxidative stress is hypothesized to be one of the key pathogenic mechanisms. It is thus proposed that manipulation of the expression of antioxidant genes that are downregulated in the presence of mutant SOD1 may serve as a therapeutic strategy for motor neuronal protection. Lentiviral vectors expressing either PRDX3 or NRF2 genes were tested in the motor neuronal-like NSC34 cell line, and in the ALS tissue culture model, NSC34 cells expressing the human SOD1(G93A) mutation. The NSC34 SOD1(G93A) cells overexpressing either PRDX3 or NRF2 showed a significant decrease in endogenous oxidation stress levels by 40 and 50% respectively compared with controls, whereas cell survival was increased by 30% in both cases. The neuroprotective potential of those two genes was further investigated in vivo in the SOD1(G93A) ALS mouse model, by administering intramuscular injections of adenoassociated virus serotype 6 (AAV6) expressing either of the target genes at a presymptomatic stage. Despite the absence of a significant effect in survival, disease onset or progression, which can be explained by the inefficient viral delivery, the promising in vitro data suggest that a more widespread CNS delivery is needed

Training an automated circulating tumor cell classifier when the true classification is uncertain

Circulating tumor cell (CTC) and tumor-derived extracellular vesicle (tdEV) loads are prognostic factors of survival in patients with carcinoma. The current method of CTC enumeration relies on operator review and, unfortunately, has moderate interoperator agreement (Fleiss’ kappa 0.60) due to difficulties in classifying CTC-like events. We compared operator review, ACCEPT automated image processing, and refined the output of a deep-learning algorithm to identify CTC and tdEV for the prediction of survival in patients with metastatic and nonmetastatic cancers. Operator review is only defined for CTC. Refinement was performed using automatic contrast maximization CM-CTC of events detected in cancer and in benign samples (CM-CTC). We used 418 samples from benign diseases, 6,293 from nonmetastatic breast, 2,408 from metastatic breast, and 698 from metastatic prostate cancer to train, test, optimize, and evaluate CTC and tdEV enumeration. For CTC identification, the CM-CTC performed best on metastatic/nonmetastatic breast cancer, respectively, with a hazard ratio (HR) for overall survival of 2.6/2.1 vs. 2.4/1.4 for operator CTC and 1.2/0.8 for ACCEPT-CTC. For tdEV identification, CM-tdEV performed best with an HR of 1.6/2.9 vs. 1.5/1.0 with ACCEPT-tdEV. In conclusion, contrast maximization is effective even though it does not utilize domain knowledge

The dual role of LSD1 and HDAC3 in STAT5-dependent transcription is determined by protein interactions, binding affinities, motifs and genomic positions

STAT5 interacts with other factors to control transcription, and the mechanism of regulation is of interest as constitutive active STAT5 has been reported in malignancies. Here, LSD1 and HDAC3 were identified as novel STAT5a interacting partners in pro-B cells. Characterization of STAT5a, LSD1 and HDAC3 target genes by ChIP-seq and RNA-seq revealed gene subsets regulated by independent or combined action of the factors and LSD1/HDAC3 to play dual role in their activation or repression. Genes bound by STAT5a alone or in combination with weakly associated LSD1 or HDAC3 were enriched for the canonical STAT5a GAS motif, and such binding induced activation or repression. Strong STAT5 binding was see

Tumour-derived extracellular vesicles in blood of metastatic cancer patients associate with overall survival

Background: Circulating tumour cells (CTCs) in blood associate with overall survival (OS) of cancer patients, but they are detected in extremely low numbers. Large tumour-derived extracellular vesicles (tdEVs) in castration-resistant prostate cancer (CRPC) patients are present at around 20 times higher frequencies than CTCs and have equivalent prognostic power. In this study, we explored the presence of tdEVs in other cancers and their association with OS. Methods: The open-source ACCEPT software was used to automatically enumerate tdEVs in digitally stored CellSearch® images obtained from previously reported CTC studies evaluating OS in 190 CRPC, 450 metastatic colorectal cancer (mCRC), 179 metastatic breast cancer (MBC) and 137 non-small cell lung cancer (NSCLC) patients before the initiation of a new treatment. Results: Presence of unfavourable CTCs and tdEVs is predictive of OS, with respective hazard ratios (HRs) of 2.4 and 2.2 in CRPC, 2.7 and 2.2 in MBC, 2.3 and 1.9 in mCRC and 2.0 and 2.4 in NSCLC, respectively. Conclusions: tdEVs have equivalent prognostic value as CTCs in the investigated metastatic cancers. CRPC, mCRC, and MBC (but not NSCLC) patients with favourable CTC counts can be further prognostically stratified using tdEVs. Our data suggest that tdEVs could be used in clinical decision-making.</p

Cancer-ID:Toward Identification of Cancer by Tumor-Derived Extracellular Vesicles in Blood

Extracellular vesicles (EVs) have great potential as biomarkers since their composition and concentration in biofluids are disease state dependent and their cargo can contain disease-related information. Large tumor-derived EVs (tdEVs, >1μm) in blood from cancer patients are associated with poor outcome, and changes in their number can be used to monitor therapy effectiveness. Whereas, small tumor-derived EVs (<1μm) are likely to outnumber their larger counterparts, thereby offering better statistical significance, identification and quantification of small tdEVs are more challenging. In the blood of cancer patients, a subpopulation of EVs originate from tumor cells, but these EVs are outnumbered by non-EV particles and EVs from other origin. In the Dutch NWO Perspectief Cancer-ID program, we developed and evaluated detection and characterization techniques to distinguish EVs from non-EV particles and other EVs. Despite low signal amplitudes, we identified characteristics of these small tdEVs that may enable the enumeration of small tdEVs and extract relevant information. The insights obtained from Cancer-ID can help to explore the full potential of tdEVs in the clinic

Image analysis technique as a tool to identify morphological changes in Trametes versicolor pellets according to exopolysaccharide or laccase production

Image analysis technique was applied to identify morphological changes of pellets from white-rot fungus Trametes versicolor on agitated submerged cultures during the production of exopolysaccharide (EPS) or ligninolytic enzymes. Batch tests with four different experimental conditions were carried out. Two different culture media were used, namely yeast medium or Trametes defined medium and the addition of lignolytic inducers as xylidine or pulp and paper industrial effluent were evaluated. Laccase activity, EPS production, and final biomass contents were determined for batch assays and the pellets morphology was assessed by image analysis techniques. The obtained data allowed establishing the choice of the metabolic pathways according to the experimental conditions, either for laccase enzymatic production in the Trametes defined medium, or for EPS production in the rich Yeast Medium experiments. Furthermore, the image processing and analysis methodology allowed for a better comprehension of the physiological phenomena with respect to the corresponding pellets morphological stages.The authors acknowledge Portucel-Empresa de Celulose e Papel, Cacia, Portugal, SA for the pulp and paper Kraft effluent used in this work. This work was funded by FEDER Funds through the Programa Operacional Factores de Competitividade-COMPETE, and national funds through FCT-Fundacao para a Ciencia e a Tecnologia under the projects PEst-C/CTM/LA/0011/2013 and PEst-C/EQB/LA0020/2013. A. P. M. Tavares acknowledge the financial support of (Programme Ciencia 2008) FCT, Portugal

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Enhanced MPPT control of a two-stage grid-connected PV system under fast-changing irradiance conditions

In this paper, an enhanced Maximum Power Point Tracking (MPPT) strategy for a two-stage gridconnected PV system is proposed, which enables accurate tracking of the maximum power point irrespective of the rate of change in solar irradiance levels. The analysis is performed both in the frequency and time domains, using a suitable linearized model of the system. A comparative assessment of the proposed MPPT strategy versus a conventional Perturbation and Observation (P&amp;O) method is carried out for operation under trapezoidal irradiance profiles.<br/