81 research outputs found
Cancer immunotherapy: Benefit and harm?
In this article, evidence is reviewed suggesting that the outcome of cancer immunotherapy depends on pre-treatment immune parameters of a patient. The results described in the article show that immunotherapy may prolong survival in certain subgroups of cancer patients, while in other subgroups a cancer-promoting effect of this treatment modality cannot be excluded
Can metabolomics in addition to genomics add to prognostic and predictive information in breast cancer?
Genomic data from breast cancers provide additional prognostic and predictive information that is beginning to be used for patient management. The question arises whether additional information derived from other 'omic' approaches such as metabolomics can provide additional information. In an article published this month in BMC Cancer, Borgan et al. add metabolomic information to genomic measures in breast tumours and demonstrate, for the first time, that it may be possible to further define subgroups of patients which could be of value clinically
Effect of diesel particulate filter regeneration on fuel consumption and emissions performance under real-driving conditions
Diesel particulate filters (DPF) are widely adopted in diesel vehicles to meet the increasingly stringent emission regulations, which require continuous passive regenerations or/and periodic active regenerations to burn off the accumulated particulate matter (PM). In spite of many laboratory studies using DPF benches and engine/chassis dynamometers, there is currently a lack of investigation on DPF regeneration under real-world conditions. Therefore, this study was conducted to investigate the impact of active DPF regenerations on the fuel consumption and gaseous and particulate emissions performance of a diesel light goods vehicle under real-driving conditions by using the state-of-the-art portable emission measurement system. In total, 60 real-driving emission (RDE) tests (∼1200 km in total) were performed on the same route during the same periods of a day, to minimise the effect of uncontrollable real-world factors on the performance evaluation. The results showed that real-world active DPF regenerations occurred every 130 km for the studied vehicle. Although they did not occur frequently, DPF regenerations increased the trip-averaged fuel consumption rate by 13% on average. CO and THC emission factors tended to increase with DPF regenerations because the post combustion used to achieve the high exhaust temperature for regeneration of the filter occurred under oxygen-lean conditions. Total NOx emissions were not affected but NO2/NOx ratio was greatly reduced by DPF regeneration due to lower NO oxidation by the diesel oxidation catalyst and higher NO2 reduction by the DPF. Finally, DPF regenerations sharply increased PM emission factors by 27 times compared with a trip without DPF regeneration, resulting in significant exceedance of the emission limit
Analysis of the Constituents in Rat Serum after Oral Administration of Fufang Zhenzhu Tiaozhi Capsule by UPLC–Q–TOF–MS/MS
A rapid and sensitive UPLC/Q–TOF–MS method has been established for analysis of the constituents in rat serum after oral administration of Fufang Zhenzhu Tiaozhi (FTZ) capsule, an effective compound prescription for treating hyperlipidemia in the clinic. The UPLC/MS information of samples was obtained first in FTZ preparation and FTZ-treated rat serum. Mass spectra were acquired in both negative and positive ion modes. Thirty-six constituents in rat serum after oral administration of FTZ were detected, including the alkaloids, ginsenosides, pentacyclic triterpenes, and their metabolites. These chemicals were identified based on the retention time and mass spectrometry data with those of authentic standards or comparison of the literatures reports. Twenty-seven prototype components originated from FTZ and nine were the metabolites of the FTZ constituents. These results shed light on the potential active constituents of the complex traditional Chinese medicinal formulas
CD57+ Memory T Cells Proliferate In Vivo
A central paradigm in the field of lymphocyte biology asserts that replicatively senescent memory T cells express the carbohydrate epitope CD57. These cells nonetheless accumulate with age and expand numerically in response to persistent antigenic stimulation. Here, we use in vivo deuterium labeling and ex vivo analyses of telomere length, telomerase activity, and intracellular expression of the cell-cycle marker Ki67 to distinguish between two non-exclusive scenarios: (1) CD57+ memory T cells do not proliferate and instead arise via phenotypic transition from the CD57− memory T cell pool; and/or (2) CD57+ memory T cells self-renew via intracompartmental proliferation. Our results provide compelling evidence in favor of the latter scenario and further suggest in conjunction with mathematical modeling that self-renewal is by far the most abundant source of newly generated CD57+ memory T cells. Immunological memory therefore appears to be intrinsically sustainable among highly differentiated subsets of T cells that express CD57
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Human cytomegalovirus protein RL1 degrades the antiviral factor SLFN11 via recruitment of the CRL4 E3 ubiquitin ligase complex.
Human cytomegalovirus (HCMV) is an important human pathogen and a paradigm of viral immune evasion, targeting intrinsic, innate, and adaptive immunity. We have employed two orthogonal multiplexed tandem mass tag-based proteomic screens to identify host proteins down-regulated by viral factors expressed during the latest phases of viral infection. This approach revealed that the HIV-1 restriction factor Schlafen-11 (SLFN11) was degraded by the poorly characterized, late-expressed HCMV protein RL1, via recruitment of the Cullin4-RING E3 Ubiquitin Ligase (CRL4) complex. SLFN11 potently restricted HCMV infection, inhibiting the formation and spread of viral plaques. Overall, we show that a restriction factor previously thought only to inhibit RNA viruses additionally restricts HCMV. We define the mechanism of viral antagonism and also describe an important resource for revealing additional molecules of importance in antiviral innate immunity and viral immune evasion
Pleosporales
One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae
ATP Release from Vascular Endothelia Occurs Across Cx43 Hemichannels and Is Attenuated during Hypoxia
Background: Extracellular ATP is an important signaling molecule for vascular adaptation to limited oxygen availability (hypoxia). Here, we pursued the contribution of vascular endothelia to extracellular ATP release under hypoxic conditions. Methodology, Principal Findings: We gained first insight from studying ATP release from endothelia (HMEC-1) pre-exposed to hypoxia. Surprisingly, we found that ATP release was significantly attenuated following hypoxia exposure (2 % oxygen, 2263 % after 48 h). In contrast, intracellular ATP was unchanged. Similarly, lactate-dehydrogenase release into the supernatants was similar between normoxic or hypoxic endothelia, suggesting that differences in lytic ATP release between normoxia or hypoxia are minimal. Next, we used pharmacological strategies to study potential mechanisms for endothelialdependent ATP release (eg, verapamil, dipyridamole, 18-alpha-glycyrrhetinic acid, anandamide, connexin-mimetic peptides). These studies revealed that endothelial ATP release occurs – at least in part- through connexin 43 (Cx43) hemichannels. A real-time RT-PCR screen of endothelial connexin expression showed selective repression of Cx43 transcript and additional studies confirmed time-dependent Cx43 mRNA, total and surface protein repression during hypoxia. In addition, hypoxia resulted in Cx43-serine368 phosphorylation, which is known to switch Cx43 hemi-channels from an open to a closed state. Conclusions/Significance: Taken together, these studies implicate endothelial Cx43 in hypoxia-associated repression o
Joint cooperative spectrum sensing and MAC protocol design for multi-channel cognitive radio networks
Semi-supervised protein subcellular localization
<p>Abstract</p> <p>Background</p> <p>Protein subcellular localization is concerned with predicting the location of a protein within a cell using computational method. The location information can indicate key functionalities of proteins. Accurate predictions of subcellular localizations of protein can aid the prediction of protein function and genome annotation, as well as the identification of drug targets. Computational methods based on machine learning, such as support vector machine approaches, have already been widely used in the prediction of protein subcellular localization. However, a major drawback of these machine learning-based approaches is that a large amount of data should be labeled in order to let the prediction system learn a classifier of good generalization ability. However, in real world cases, it is laborious, expensive and time-consuming to experimentally determine the subcellular localization of a protein and prepare instances of labeled data.</p> <p>Results</p> <p>In this paper, we present an approach based on a new learning framework, semi-supervised learning, which can use much fewer labeled instances to construct a high quality prediction model. We construct an initial classifier using a small set of labeled examples first, and then use unlabeled instances to refine the classifier for future predictions.</p> <p>Conclusion</p> <p>Experimental results show that our methods can effectively reduce the workload for labeling data using the unlabeled data. Our method is shown to enhance the state-of-the-art prediction results of SVM classifiers by more than 10%.</p
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