Towards Endometriosis Diagnosis by Gadofosveset-Trisodium Enhanced Magnetic Resonance Imaging

Endometriosis is defined as the presence of endometrial tissue outside the uterus. It affects 10–15% of women during reproductive age and has a big personal and social impact due to chronic pelvic pain, subfertility, loss of work-hours and medical costs. Such conditions are exacerbated by the fact that the correct diagnosis is made as late as 8–11 years after symptom presentation. This is due to the lack of a reliable non-invasive diagnostic test and the fact that the reference diagnostic standard is laparoscopy (invasive, expensive and not without risks). High-molecular weight gadofosveset-trisodium is used as contrast agent in Magnetic Resonance Imaging (MRI). Since it extravasates from hyperpermeable vessels more easily than from mature blood vessels, this contrast agent detects angiogenesis efficiently. Endometriosis has high angiogenic activity. Therefore, we have tested the possibility to detect endometriosis non-invasively using Dynamic Contrast-Enhanced MRI (DCE-MRI) and gadofosveset-trisodium as a contrast agent in a mouse model. Endometriotic lesions were surgically induced in nine mice by autologous transplantation. Three weeks after lesion induction, mice were scanned by DCE-MRI. Dynamic image analysis showed that the rates of uptake (inwash), persistence and outwash of the contrast agent were different between endometriosis and control tissues (large blood vessels and back muscle). Due to the extensive angiogenesis in induced lesions, the contrast agent persisted longer in endometriotic than control tissues, thus enhancing the MRI signal intensity. DCE-MRI was repeated five weeks after lesion induction, and contrast enhancement was similar to that observed three weeks after endometriosis induction. The endothelial-cell marker CD31 and the pericyte marker α-smooth-muscle-actin (mature vessels) were detected with immunohistochemistry and confirmed that endometriotic lesions had significantly higher prevalence of new vessels (CD31 only positive) than the uterus and control tissues. The diagnostic value of gadofosveset-trisodium to detect endometriosis should be tested in human settings

Proteomic Analysis of the Secretory Response of Aspergillus niger to D-Maltose and D-Xylose

Fungi utilize polysaccharide substrates through extracellular digestion catalyzed by secreted enzymes. Thus far, protein secretion by the filamentous fungus Aspergillus niger has mainly been studied at the level of individual proteins and by genome and transcriptome analyses. To extend these studies, a complementary proteomics approach was applied with the aim to investigate the changes in secretome and microsomal protein composition resulting from a shift to a high level secretion condition. During growth of A. niger on d-sorbitol, small amounts of d-maltose or d-xylose were used as inducers of the extracellular amylolytic and xylanolytic enzymes. Upon induction, protein compositions in the extracellular broth as well as in enriched secretory organelle (microsomal) fractions were analyzed using a shotgun proteomics approach. In total 102 secreted proteins and 1,126 microsomal proteins were identified in this study. Induction by d-maltose or d-xylose resulted in the increase in specific extracellular enzymes, such as glucoamylase A on d-maltose and β-xylosidase D on d-xylose, as well as of microsomal proteins. This reflects the differential expression of selected genes coding for dedicated extracellular enzymes. As expected, the addition of extra d-sorbitol had no effect on the expression of carbohydrate-active enzymes, compared to addition of d-xylose or d-maltose. Furthermore, d-maltose induction caused an increase in microsomal proteins related to translation (e.g., Rpl15) and vesicular transport (e.g., the endosomal-cargo receptor Erv14). Millimolar amounts of the inducers d-maltose and d-xylose are sufficient to cause a direct response in specific protein expression levels. Also, after induction by d-maltose or d-xylose, the induced enzymes were found in microsomes and extracellular. In agreement with our previous findings for d-xylose induction, d-maltose induction leads to recruitment of proteins involved in proteasome-mediated degradation

Global energy governance : a review and research agenda

Over the past few years, global energy governance (GEG) has emerged as a major new field of enquiry in international studies. Scholars engaged in this field seek to understand how the energy sector is governed at the global level, by whom and with what consequences. By focusing on governance, they broaden and enrich the geopolitical and hard-nosed security perspectives that have long been, and still are, the dominant perspectives through which energy is analysed. Though still a nascent field, the literature on GEG is thriving and continues to attract the attention of a growing number of researchers. This article reviews the GEG literature as it has developed over the past 10 years. Our aim is to highlight both the progress and limitations of the field, and to identify some opportunities for future research. The article proceeds as follows. First, it traces the origins of the GEG literature (section “Origins and roots of GEG research”). The subsequent sections deal with the two topics that have received the most attention in the GEG literature: Why does energy need global governance (section “The goals and rationale of global energy governance”)? And, who governs energy (section “Mapping the global energy architecture”)? We then address a third question that has received far less attention: How well or poor is energy governed (section “Evaluating global energy governance”)? In our conclusions (section “Conclusions and outlook”), we reflect on the current state of GEG, review recent trends and innovations, and identify some questions that warrant future consideration by scholars. This article is published as part of a thematic collection on global governance

Proteomics of industrial fungi: trends and insights for biotechnology

Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis

‘Medusa head ataxia’: the expanding spectrum of Purkinje cell antibodies in autoimmune cerebellar ataxia. Part 3: Anti-Yo/CDR2, anti-Nb/AP3B2, PCA-2, anti-Tr/DNER, other antibodies, diagnostic pitfalls, summary and outlook

Serological testing for anti-neural autoantibodies is important in patients presenting with idiopathic cerebellar ataxia, since these autoantibodies may indicate cancer, determine treatment and predict prognosis. While some of them target nuclear antigens present in all or most CNS neurons (e.g. anti-Hu, anti-Ri), others more specifically target antigens present in the cytoplasm or plasma membrane of Purkinje cells (PC). In this series of articles, we provide a detailed review of the clinical and paraclinical features, oncological, therapeutic and prognostic implications, pathogenetic relevance, and differential laboratory diagnosis of the 12 most common PC autoantibodies (often referred to as ‘Medusa head antibodies’ due to their characteristic somatodendritic binding pattern when tested by immunohistochemistry). To assist immunologists and neurologists in diagnosing these disorders, typical high-resolution immunohistochemical images of all 12 reactivities are presented, diagnostic pitfalls discussed and all currently available assays reviewed. Of note, most of these antibodies target antigens involved in the mGluR1/calcium pathway essential for PC function and survival. Many of the antigens also play a role in spinocerebellar ataxia. Part 1 focuses on anti-metabotropic glutamate receptor 1-, anti-Homer protein homolog 3-, anti-Sj/inositol 1,4,5-trisphosphate receptor- and anti-carbonic anhydrase-related protein VIII-associated autoimmune cerebellar ataxia (ACA); part 2 covers anti-protein kinase C gamma-, anti-glutamate receptor delta-2-, anti-Ca/RhoGTPase-activating protein 26- and anti-voltage-gated calcium channel-associated ACA; and part 3 reviews the current knowledge on anti-Tr/delta notch-like epidermal growth factor-related receptor-, anti-Nb/AP3B2-, anti-Yo/cerebellar degeneration-related protein 2- and Purkinje cell antibody 2-associated ACA, discusses differential diagnostic aspects and provides a summary and outlook

Second Language Processing Shows Increased Native-Like Neural Responses after Months of No Exposure

Although learning a second language (L2) as an adult is notoriously difficult, research has shown that adults can indeed attain native language-like brain processing and high proficiency levels. However, it is important to then retain what has been attained, even in the absence of continued exposure to the L2—particularly since periods of minimal or no L2 exposure are common. This event-related potential (ERP) study of an artificial language tested performance and neural processing following a substantial period of no exposure. Adults learned to speak and comprehend the artificial language to high proficiency with either explicit, classroom-like, or implicit, immersion-like training, and then underwent several months of no exposure to the language. Surprisingly, proficiency did not decrease during this delay. Instead, it remained unchanged, and there was an increase in native-like neural processing of syntax, as evidenced by several ERP changes—including earlier, more reliable, and more left-lateralized anterior negativities, and more robust P600s, in response to word-order violations. Moreover, both the explicitly and implicitly trained groups showed increased native-like ERP patterns over the delay, indicating that such changes can hold independently of L2 training type. The results demonstrate that substantial periods with no L2 exposure are not necessarily detrimental. Rather, benefits may ensue from such periods of time even when there is no L2 exposure. Interestingly, both before and after the delay the implicitly trained group showed more native-like processing than the explicitly trained group, indicating that type of training also affects the attainment of native-like processing in the brain. Overall, the findings may be largely explained by a combination of forgetting and consolidation in declarative and procedural memory, on which L2 grammar learning appears to depend. The study has a range of implications, and suggests a research program with potentially important consequences for second language acquisition and related fields

An exploration of scenarios to support sustainable land management using integrated environmental socio-economic models

Scenario analysis constitutes a valuable deployment method for scientific models to inform environmental decision-making, particularly for evaluating land degradation mitigation options, which are rarely based on formal analysis. In this paper we demonstrate such an assessment using the PESERA–DESMICE modeling framework with various scenarios for 13 global land degradation hotspots. Starting with an initial assessment representing land degradation and productivity under current conditions, options to combat instances of land degradation are explored by determining: (1) Which technologies are most biophysically appropriate and most financially viable in which locations; we term these the “technology scenarios”; (2) how policy instruments such as subsidies influence upfront investment requirements and financial viability and how they lead to reduced levels of land degradation; we term these the “policy scenarios”; and (3) how technology adoption affects development issues such as food production and livelihoods; we term these the “global scenarios”. Technology scenarios help choose the best technology for a given area in biophysical and financial terms, thereby outlining where policy support may be needed to promote adoption; policy scenarios assess whether a policy alternative leads to a greater extent of technology adoption; while global scenarios demonstrate how implementing technologies may serve wider sustainable development goals. Scenarios are applied to assess spatial variation within study sites as well as to compare across different sites. Our results show significant scope to combat land degradation and raise agricultural productivity at moderate cost. We conclude that scenario assessment can provide informative input to multi-level land management decision-making processes