Inter'sex/gender-related constitutiveness : – Specific Realities, Specific Norms

There are new approaches and worldviews in the natural sciences and engineering that are based on multilayered and complex systemic approaches and can also enrich the social discourse on (inter-)sex/gender-related constitutiveness. What Western scientific thought has taught us since the 18th century can also frequently be reflected in the realm of sex/gender-related constitutiveness. Variability and complex systemic strategies are a fundamental prerequisite of life

Von Menschen und inter* Mäusen : Ein Essay

Der Körper als Objekt der Begierde und des Designs: Das Modell ist keineswegs neu. Neu ist die Möglichkeit, hochentwickelte Technik anzuwenden. Genetische, biomolekulare und zelluläre High-End-Technologien ermöglichen echtes Handeln und Veränderungen; das heißt, wahrhaft neue Modifikationen der menschlichen Körperlichkeit. Pränataldiagnostik ermöglicht gezielte Selektion. Die notwendige Thematisierung von Bio- und Gentechnologie darf nicht weiter ausbleiben. Auch (Inter)Geschlechtlichkeit betreffend

Machine learning algorithms to predict breast cancer recurrence using structured and unstructured sources from electronic health records

Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recurrence. We hypothesized that combining features from structured and unstructured sources would provide better prediction results for 5-year cancer recurrence than either source alone. We collected and preprocessed clinical data from a cohort of BC patients, resulting in 823 valid subjects for analysis. We derived three sets of features: structured information, features from free text, and a combination of both. We evaluated the performance of five ML algorithms to predict 5-year cancer recurrence and selected the best-performing to test our hypothesis. The XGB (eXtreme Gradient Boosting) model yielded the best performance among the five evaluated algorithms, with precision = 0.900, recall = 0.907, F1-score = 0.897, and area under the receiver operating characteristic AUROC = 0.807. The best prediction results were achieved with the structured dataset, followed by the unstructured dataset, while the combined dataset achieved the poorest performance. ML algorithms for BC recurrence prediction are valuable tools to improve patient risk stratification, help with post-cancer monitoring, and plan more effective follow-up. Structured data provides the best results when fed to ML algorithms. However, an approach based on natural language processing offers comparable results while potentially requiring less mapping effort.European Union | Ref. 875406Fondo Europeo de Desarrollo Regional (FEDER)Xunta de Galici

The Development of Peptide-Based Tools for the Analysis of Angiogenesis

SummaryLimitations to the application of molecularly targeted cancer therapies are the inability to accurately match patient with effective treatment and the absence of a prompt readout of posttreatment response. Noninvasive agents that rapidly report vascular endothelial growth factor (VEGF) levels using positron emission tomography (PET) have the potential to enhance anti-angiogenesis therapies. Using phage display, two distinct classes of peptides were identified that bind to VEGF with nanomolar affinity and high selectivity. Co-crystal structures of these different peptide classes demonstrate that both bind to the receptor-binding region of VEGF. 18F-radiolabelling of these peptides facilitated the acquisition of PET images of tumor VEGF levels in a HM7 xenograph model. The images obtained from one 59-residue probe, 18F-Z-3B, 2 hr postinjection are comparable to those obtained with anti-VEGF antibody B20 72 hr postinjection. Furthermore, VEGF levels in growing SKOV3 tumors were followed using 18F-Z-3B as a PET probe with VEGF levels increasing with tumor size

Characterisation of insulin analogues therapeutically available to patients

The structure and function of clinical dosage insulin and its analogues were assessed. This included ‘native insulins’ (human recombinant, bovine, porcine), ‘fast-acting analogues’ (aspart, glulisine, lispro) and ‘slow-acting analogues’ (glargine, detemir, degludec). Analytical ultracentrifugation, both sedimentation velocity and equilibrium experiments, were employed to yield distributions of both molar mass and sedimentation coefficient of all nine insulins. Size exclusion chromatography, coupled to multi-angle light scattering, was also used to explore the function of these analogues. On ultracentrifugation analysis, the insulins under investigation were found to be in numerous conformational states, however the majority of insulins were present in a primarily hexameric conformation. This was true for all native insulins and two fast-acting analogues. However, glargine was present as a dimer, detemir was a multi-hexameric system, degludec was a dodecamer (di-hexamer) and glulisine was present as a dimer-hexamer-dihexamer system. However, size-exclusion chromatography showed that the two hexameric fast-acting analogues (aspart and lispro) dissociated into monomers and dimers due to the lack of zinc in the mobile phase. This comprehensive study is the first time all nine insulins have been characterised in this way, the first time that insulin detemir have been studied using analytical ultracentrifugation and the first time that insulins aspart and glulisine have been studied using sedimentation equilibrium. The structure and function of these clinically administered insulins is of critical importance and this research adds novel data to an otherwise complex functional physiological protein

Inter-laboratory analysis of cereal beta-glucan extracts of nutritional importance : An evaluation of different methods for determining weight-average molecular weight and molecular weight distribution

In an interlaboratory study we compare different methods to determine the weight-average molecular weight (Mw) and molecular weight distribution of six cereal beta-glucan isolates of nutritional importance. Size exclusion chromatography (SEC) with multi-angle light scattering (MALS), capillary viscometry, sedimentation velocity analytical ultracentrifugation and one asymmetric flow field-flow fractionation (AF4)-MALS method all yielded similar Mw values for mostly individual chains of dissolved beta-glucan molecules. SEC with post-column calcofluor detection underestimated the Mw of beta-glucan > 500 x 10(3) g/mol. The beta-glucan molecules analysed by these methods were primarily in a random coil conformation as evidenced from individual MarkHouwink-Kuhn-Sakurada (MHKS) scaling coefficients between 0.5 and 0.6 and Wales-Van Holde ratios between 1.4 and 1.7. In contrast, a second AF4-MALS method yielded much larger Mw values for these same samples indicating the presence and detection of beta-glucan aggregates. Storage of the six beta-glucan solutions in the dark at 4 C for 4 years revealed them to be stable. This suggests an absence of storage-induced irreversible aggregation phenomena or chain-scission. Shear forces in SEC and the viscometer capillary and hydrostatic pressure in analytical ultracentrifugation probably led to the reversable dissociation of beta-glucan aggregates into molecularly dissolved species. Thus, all these methods yield true weight-average molecular weight values not biased by the presence of aggregates as was the case in one of the AF4 based methods employed.Peer reviewe

Developing European conservation and mitigation tools for pollination services: approaches of the STEP (Status and Trends of European Pollinators) project

Pollinating insects form a key component of European biodiversity, and provide a vital ecosystem service to crops and wild plants. There is growing evidence of declines in both wild and domesticated pollinators, and parallel declines in plants relying upon them. The STEP project (Status and Trends of European Pollinators, 2010-2015, www.stepproject.net) is documenting critical elements in the nature and extent of these declines, examining key functional traits associated with pollination deficits, and developing a Red List for some European pollinator groups. Together these activities are laying the groundwork for future pollinator monitoring programmes. STEP is also assessing the relative importance of potential drivers of pollinator declines, including climate change, habitat loss and fragmentation, agrochemicals, pathogens, alien species, light pollution, and their interactions. We are measuring the ecological and economic impacts of declining pollinator services and floral resources, including effects on wild plant populations, crop production and human nutrition. STEP is reviewing existing and potential mitigation options, and providing novel tests of their effectiveness across Europe. Our work is building upon existing and newly developed datasets and models, complemented by spatially-replicated campaigns of field research to fill gaps in current knowledge. Findings are being integrated into a policy-relevant framework to create evidence-based decision support tools. STEP is establishing communication links to a wide range of stakeholders across Europe and beyond, including policy makers, beekeepers, farmers, academics and the general public. Taken together, the STEP research programme aims to improve our understanding of the nature, causes, consequences and potential mitigation of declines in pollination services at local, national, continental and global scales

Metabolic implication of tigecycline as an efficacious second-line treatment for sorafenib-resistant hepatocellular carcinoma

Sorafenib represents the current standard of care for patients with advanced-stage hepatocellular carcinoma (HCC). However, acquired drug resistance occurs frequently during therapy and is accompanied by rapid tumor regrowth after sorafenib therapy termination. To identify the mechanism of this therapy-limiting growth resumption, we established robust sorafenib resistance HCC cell models that exhibited mitochondrial dysfunction and chemotherapeutic crossresistance. We found a rapid relapse of tumor cell proliferation after sorafenib withdrawal, which was caused by renewal of mitochondrial structures alongside a metabolic switch toward high electron transport system (ETS) activity. The translation-inhibiting antibiotic tigecycline impaired the biogenesis of mitochondrial DNA-encoded ETS subunits and limited the electron acceptor turnover required for glutamine oxidation. Thereby, tigecycline prevented the tumor relapse in vitro and in murine xenografts in vivo. These results offer a promising second-line therapeutic approach for advanced-stage HCC patients with progressive disease undergoing sorafenib therapy or treatment interruption due to severe adverse events