Pi0 and Eta measurement with photon conversions in ALICE in proton-proton collisions at sqrt(s) = 7 TeV

We present a measurement of the Pi0 transverse momentum spectrum and of the Eta/Pi0 ratio in proton-proton collisions at sqrt(s) = 7 TeV at the CERN LHC. In this analysis the reconstruction of Pi0 and Eta mesons has been done via photon conversions in the central tracking system of ALICE. Therefore, this method is completely independent from the electromagnetic calorimeters. It makes the Pi0 (Eta) measurement possible down to pt = 0.4 (0.6) GeV/c with a very good resolution and a very small background. For 100 Mio. pp collisions the pt reach is 7 GeV/c. The results are compared to NLO pQCD calculations.Comment: Proceedings to talk at HardProbes 2010, 4 page

Charakteristika von Repräsentationen im Biologieunterricht aus Sicht von Schülerinnen und Schülern der Sekundarstufe II

ZusammenfassungExterne Repräsentationen sind von zentraler Bedeutung für den Biologieunterricht. In diesem Zusammenhang existieren zahlreiche Befunde bezüglich der Kompetenzen von Lernenden im Umgang mit fachspezifischen Texten, Bildern sowie Multiplen Externen Repräsentationen (MER). Charakteristika von Repräsentationen wurden bisher überwiegend domänenübergreifend und auf theoretischer, kognitionspsychologischer Ebene klassifiziert. Eine solche Klassifikation wird im vorliegenden Beitrag genutzt, um die Lernendenperspektive auf Repräsentationen im Fach Biologie strukturiert zu erfassen. Zu diesem Zweck wurden fünf Leitfadeninterviews mit Schülerinnen und Schülern der Sekundarstufe II durchgeführt und mithilfe der Methode der qualitativen Inhaltsanalyse ausgewertet. Die Ergebnisse zeigen u.a., dass die Schülerinnen und der Schüler die sachliche, wissenschaftliche Natur von biologischen Texten und Bilder für charakteristisch halten. Bezüglich der MER ist festzustellen, dass Darstellungen von Prozessen und Abläufen in Bildern und Texten als typisch für den Biologieunterricht wahrgenommen werden. Die Beschreibung des fachbezogenen Umgangs mit Repräsentationen lässt Hinweise bezüglich der Optimierung von Unterricht und Lernen zu.AbstractExternal Representations are particularly important for biology teaching in school. In this context, numerous findings exist regarding student’s competences in dealing with biological texts, pictures and multiple external representations (MER). Characteristic of representations haven’t been classified domain specific but on a theoretical, cognitive psychological level. In this article such a classification is used to analyse the learner perspective on representations in biology class in a structured way. To this end, five guided interviews were conducted with students from secondary school. The interviews were analysed employing qualitative content analysis. Among other things the results show that from the learner perspective the objective, scientific nature of biological texts and pictures is characteristic. Regarding MER it can be noted that representations of processes and procedures in pictures and texts are perceived as typical for biology class. The description of subject-related dealing with representations permits guidance for optimizing teaching and learning

Artificial Intelligence to Predict the BRAF V595E Mutation in Canine Urinary Bladder Urothelial Carcinomas

In dogs, the BRAF mutation (V595E) is common in bladder and prostate cancer and represents a specific diagnostic marker. Recent advantages in artificial intelligence (AI) offer new opportunities in the field of tumour marker detection. While AI histology studies have been conducted in humans to detect BRAF mutation in cancer, comparable studies in animals are lacking. In this study, we used commercially available AI histology software to predict BRAF mutation in whole slide images (WSI) of bladder urothelial carcinomas (UC) stained with haematoxylin and eosin (HE), based on a training (n = 81) and a validation set (n = 96). Among 96 WSI, 57 showed identical PCR and AI-based BRAF predictions, resulting in a sensitivity of 58% and a specificity of 63%. The sensitivity increased substantially to 89% when excluding small or poor-quality tissue sections. Test reliability depended on tumour differentiation (p < 0.01), presence of inflammation (p < 0.01), slide quality (p < 0.02) and sample size (p < 0.02). Based on a small subset of cases with available adjacent non-neoplastic urothelium, AI was able to distinguish malignant from benign epithelium. This is the first study to demonstrate the use of AI histology to predict BRAF mutation status in canine UC. Despite certain limitations, the results highlight the potential of AI in predicting molecular alterations in routine tissue sections

Artificial Intelligence to Predict the BRAF V595E Mutation in Canine Urinary Bladder Urothelial Carcinomas.

In dogs, the BRAF mutation (V595E) is common in bladder and prostate cancer and represents a specific diagnostic marker. Recent advantages in artificial intelligence (AI) offer new opportunities in the field of tumour marker detection. While AI histology studies have been conducted in humans to detect BRAF mutation in cancer, comparable studies in animals are lacking. In this study, we used commercially available AI histology software to predict BRAF mutation in whole slide images (WSI) of bladder urothelial carcinomas (UC) stained with haematoxylin and eosin (HE), based on a training (n = 81) and a validation set (n = 96). Among 96 WSI, 57 showed identical PCR and AI-based BRAF predictions, resulting in a sensitivity of 58% and a specificity of 63%. The sensitivity increased substantially to 89% when excluding small or poor-quality tissue sections. Test reliability depended on tumour differentiation (p < 0.01), presence of inflammation (p < 0.01), slide quality (p < 0.02) and sample size (p < 0.02). Based on a small subset of cases with available adjacent non-neoplastic urothelium, AI was able to distinguish malignant from benign epithelium. This is the first study to demonstrate the use of AI histology to predict BRAF mutation status in canine UC. Despite certain limitations, the results highlight the potential of AI in predicting molecular alterations in routine tissue sections

β2-Syntrophin Is a Cdk5 Substrate That Restrains the Motility of Insulin Secretory Granules

The molecular basis for the interaction of insulin granules with the cortical cytoskeleton of pancreatic β-cells remains unknown. We have proposed that binding of the granule protein ICA512 to the PDZ domain of β2-syntrophin anchors granules to actin filaments and that the phosphorylation/dephosphorylation of β2-syntrophin regulates this association. Here we tested this hypothesis by analyzing INS-1 cells expressing GFP-β2-syntrophin through the combined use of biochemical approaches, imaging studies by confocal and total internal reflection fluorescence microscopy as well as electron microscopy. Our results support the notion that β2-syntrophin restrains the mobility of cortical granules in insulinoma INS-1 cells, thereby reducing insulin secretion and increasing insulin stores in resting cells, while increasing insulin release upon stimulation. Using mass spectrometry, in vitro phosphorylation assays and β2-syntrophin phosphomutants we found that phosphorylation of β2-syntrophin on S75 near the PDZ domain decreases its binding to ICA512 and correlates with increased granule motility, while phosphorylation of S90 has opposite effects. We further show that Cdk5, which regulates insulin secretion, phosphorylates S75. These findings provide mechanistic insight into how stimulation displaces insulin granules from cortical actin, thus promoting their motility and exocytosis

Nuclear Morphometry using a Deep Learning-based Algorithm has Prognostic Relevance for Canine Cutaneous Mast Cell Tumors

Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics (morphometry) can improve reproducibility, but manual methods are time consuming. In this study, we evaluated fully automated morphometry using a deep learning-based algorithm in 96 canine cutaneous mast cell tumors with information on patient survival. Algorithmic morphometry was compared with karyomegaly estimates by 11 pathologists, manual nuclear morphometry of 12 cells by 9 pathologists, and the mitotic count as a benchmark. The prognostic value of automated morphometry was high with an area under the ROC curve regarding the tumor-specific survival of 0.943 (95% CI: 0.889 - 0.996) for the standard deviation (SD) of nuclear area, which was higher than manual morphometry of all pathologists combined (0.868, 95% CI: 0.737 - 0.991) and the mitotic count (0.885, 95% CI: 0.765 - 1.00). At the proposed thresholds, the hazard ratio for algorithmic morphometry (SD of nuclear area $\geq 9.0 \mu m^2$) was 18.3 (95% CI: 5.0 - 67.1), for manual morphometry (SD of nuclear area $\geq 10.9 \mu m^2$) 9.0 (95% CI: 6.0 - 13.4), for karyomegaly estimates 7.6 (95% CI: 5.7 - 10.1), and for the mitotic count 30.5 (95% CI: 7.8 - 118.0). Inter-rater reproducibility for karyomegaly estimates was fair ($\kappa$ = 0.226) with highly variable sensitivity/specificity values for the individual pathologists. Reproducibility for manual morphometry (SD of nuclear area) was good (ICC = 0.654). This study supports the use of algorithmic morphometry as a prognostic test to overcome the limitations of estimates and manual measurements

IL4I1 Is a Metabolic Immune Checkpoint that Activates the AHR and Promotes Tumor Progression

Immune checkpoint blockade therapy induces the AHR-activating enzyme IL4I1, which promotes tumor progression, through its effects on tumor cell motility and adaptive immunity

Brain structure and function: a multidisciplinary pipeline to study hominoid brain evolution

To decipher the evolution of the hominoid brain and its functions, it is essential to conduct comparative studies in primates, including our closest living relatives. However, strong ethical concerns preclude in vivo neuroimaging of great apes. We propose a responsible and multidisciplinary alternative approach that links behavior to brain anatomy in non-human primates from diverse ecological backgrounds. The brains of primates observed in the wild or in captivity are extracted and fixed shortly after natural death, and then studied using advanced MRI neuroimaging and histology to reveal macro- and microstructures. By linking detailed neuroanatomy with observed behavior within and across primate species, our approach provides new perspectives on brain evolution. Combined with endocranial brain imprints extracted from computed tomographic scans of the skulls these data provide a framework for decoding evolutionary changes in hominin fossils. This approach is poised to become a key resource for investigating the evolution and functional differentiation of hominoid brains

Sourcing high tissue quality brains from deceased wild primates with known socio‐ecology

The selection pressures that drove dramatic encephalisation processes through the mammal lineage remain elusive, as does knowledge of brain structure reorganisation through this process. In particular, considerable structural brain changes are present across the primate lineage, culminating in the complex human brain that allows for unique behaviours such as language and sophisticated tool use. To understand this evolution, a diverse sample set of humans' closest relatives with varying socio-ecologies is needed. However, current brain banks predominantly curate brains from primates that died in zoological gardens. We try to address this gap by establishing a field pipeline mitigating the challenges associated with brain extractions of wild primates in their natural habitat. The success of our approach is demonstrated by our ability to acquire a novel brain sample of deceased primates with highly variable socio-ecological exposure and a particular focus on wild chimpanzees. Methods in acquiring brain tissue from wild settings are comprehensively explained, highlighting the feasibility of conducting brain extraction procedures under strict biosafety measures by trained veterinarians in field sites. Brains are assessed at a fine-structural level via high-resolution MRI and state-of-the-art histology. Analyses confirm that excellent tissue quality of primate brains sourced in the field can be achieved with a comparable tissue quality of brains acquired from zoo-living primates. Our field methods are noninvasive, here defined as not harming living animals, and may be applied to other mammal systems than primates. In sum, the field protocol and methodological pipeline validated here pose a major advance for assessing the influence of socio-ecology on medium to large mammal brains, at both macro- and microstructural levels as well as aiding with the functional annotation of brain regions and neuronal pathways via specific behaviour assessments.Output Status: Forthcoming/Available Online Additional authors: Richard McElreath, Alfred Anwander, Philipp Gunz, Markus Morawski, Angela D. Friederici, Nikolaus Weiskopf, Fabian H. Leendertz, Roman M. Wittig EBC Cosortium: Karoline Albig, Bala Amarasekaran, Sam Angedakin, Alfred Anwander, Daniel Aschoff, Caroline Asiimwe, Laurent Bailanda, Jacinta C. Beehner, Raphael Belais, Thore J. Bergman, Birgit Blazey, Andreas Bernhard, Christian Bock, Pénélope Carlier, Julian Chantrey, Catherine Crockford, Tobias Deschner, Ariane Düx1, Luke Edwards, Cornelius Eichner, Géraldine Escoubas2, Malak Ettaj, Karina Flores, Richard Francke, Angela D. Friederici, Cédric Girard-Buttoz, Jorge Gomez Fortun, Zoro Bertin GoneBi, Tobias Gräßle, Eva Gruber-Dujardin, Philipp Gunz, Jess Hartel, Daniel B. M. Haun, Michael Henshall, Catherine Hobaiter, Noémie Hofman, Jenny E. Jaffe, Carsten Jäger, Anna Jauch, Stomy Kahemere, Evgeniya Kirilina, Robert Klopfleisch, Tobias Knauf-Witzens, Kathrin S. Kopp, Guy Landry Mamboundou Kouima, Bastian Lange, Kevin Langergraber, Arne Lawrenz, Fabian H. Leendertz, Ilona Lipp, Matys Liptovszky, Tobias Loubser Theron, Christelle Patricia Lumbu, Patrice Makouloutou Nzassi, Kerstin Mätz-Rensing, Richard McElreath, Matthew McLennan, Zoltan Mezö, Sophie Moittie, Torsten Møller, Markus Morawski, David Morgan, Timothy Mugabe, Martin Muller, Matthias Müller, Inoussa Njumboket, Karin Olofsson-Sannö, Alain Ondzie, Emily Otali, Michael Paquette, Simone Pika, Kerrin Pine, Andrea Pizarro, Kamilla Pléh, Jessica Rendel, Sandra Reichler-Danielowski, Martha M. Robbins, Alejandra Romero Forero, Konstantin Ruske, Liran Samuni, Crickette Sanz, André Schüle, Ingo Schwabe, Katarina Schwalm, Sheri Speede, Lara Southern, Jonas Steiner, Marc Stidworthy, Martin Surbeck, Claudia Szentiks, Tanguy Tanga, Reiner Ulrich, Steve Unwin, Erica van de Waal, Sue Walker, Nikolaus Weiskopf, Gudrun Wibbelt, Roman M. Wittig, Kim Wood, Klaus Zuberbühle

Sourcing high tissue quality brains from deceased wild primates with known socio‐ecology

The selection pressures that drove dramatic encephalisation processes through the mammal lineage remain elusive, as does knowledge of brain structure reorganisation through this process. In particular, considerable structural brain changes are present across the primate lineage, culminating in the complex human brain that allows for unique behaviours such as language and sophisticated tool use. To understand this evolution, a diverse sample set of humans' closest relatives with varying socio-ecologies is needed. However, current brain banks predominantly curate brains from primates that died in zoological gardens. We try to address this gap by establishing a field pipeline mitigating the challenges associated with brain extractions of wild primates in their natural habitat. The success of our approach is demonstrated by our ability to acquire a novel brain sample of deceased primates with highly variable socio-ecological exposure and a particular focus on wild chimpanzees. Methods in acquiring brain tissue from wild settings are comprehensively explained, highlighting the feasibility of conducting brain extraction procedures under strict biosafety measures by trained veterinarians in field sites. Brains are assessed at a fine-structural level via high-resolution MRI and state-of-the-art histology. Analyses confirm that excellent tissue quality of primate brains sourced in the field can be achieved with a comparable tissue quality of brains acquired from zoo-living primates. Our field methods are noninvasive, here defined as not harming living animals, and may be applied to other mammal systems than primates. In sum, the field protocol and methodological pipeline validated here pose a major advance for assessing the influence of socio-ecology on medium to large mammal brains, at both macro- and microstructural levels as well as aiding with the functional annotation of brain regions and neuronal pathways via specific behaviour assessments