Big Egos in Big Science

In this paper we investigate the micro-mechanisms governing the structural evolution of a scientific collaboration. Empirical evidence indicates that we have transcended into a new paradigm with a new modus operandi where scientific discovery are not lead by so called lone ?stars?, or big egos, but instead by a group of people, from a multitude of institutions, having a diverse knowledge set and capable of operating more and more complex instrumentation Using a dataset consisting of full bibliometric coverage from a Large Scale Research Facility, we utilize a stochastic actor oriented model to estimate both the structural and performance effects of selection, as well as the behavioral of crossing organizational boundaries. Preliminary results suggest that the selection of collaborators still is skewed, and identify a large assortativity effect, as well as a tendency to interact with both authors with similar citations

Automatic Fungi Recognition: Deep Learning Meets Mycology

The article presents an AI-based fungi species recognition system for a citizen-science community. The system’s real-time identification too — FungiVision — with a mobile application front-end, led to increased public interest in fungi, quadrupling the number of citizens collecting data. FungiVision, deployed with a human-in-the-loop, reaches nearly 93% accuracy. Using the collected data, we developed a novel fine-grained classification dataset — Danish Fungi 2020 (DF20) — with several unique characteristics: species-level labels, a small number of errors, and rich observation metadata. The dataset enables the testing of the ability to improve classification using metadata, e.g., time, location, habitat and substrate, facilitates classifier calibration testing and finally allows the study of the impact of the device settings on the classification performance. The continual flow of labelled data supports improvements of the online recognition system. Finally, we present a novel method for the fungi recognition service, based on a Vision Transformer architecture. Trained on DF20 and exploiting available metadata, it achieves a recognition error that is 46.75% lower than the current system. By providing a stream of labeled data in one direction, and an accuracy increase in the other, the collaboration creates a virtuous cycle helping both communities

The endogenous preproglucagon system is not essential for gut growth homeostasis in mice

Objective: The prevalence of obesity and related co-morbidities is reaching pandemic proportions. Today, the most effective obesity treatments are glucagon-like peptide 1 (GLP-1) analogs and bariatric surgery. Interestingly, both intervention paradigms have been associated with adaptive growth responses in the gut; however, intestinotrophic mechanisms associated with or secondary to medical or surgical obesity therapies are poorly understood. Therefore, the objective of this study was to assess the local basal endogenous and pharmacological intestinotrophic effects of glucagon-like peptides and bariatric surgery in mice. Methods: We used in situ hybridization to provide a detailed and comparative anatomical map of the local distribution of GLP-1 receptor (Glp1r), GLP-2 receptor (Glp2r), and preproglucagon (Gcg) mRNA expression throughout the mouse gastrointestinal tract. Gut development in GLP-1R-, GLP-2R-, or GCG-deficient mice was compared to their corresponding wild-type controls, and intestinotrophic effects of GLP-1 and GLP-2 analogs were assessed in wild-type mice. Lastly, gut volume was determined in a mouse model of vertical sleeve gastrectomy (VSG). Results: Comparison of Glp1r, Glp2r, and Gcg mRNA expression indicated a widespread, but distinct, distribution of these three transcripts throughout all compartments of the mouse gastrointestinal tract. While mice null for Glp1r or Gcg showed normal intestinal morphology, Glp2r−/− mice exhibited a slight reduction in small intestinal mucosa volume. Pharmacological treatment with GLP-1 and GLP-2 analogs significantly increased gut volume. In contrast, VSG surgery had no effect on intestinal morphology. Conclusion: The present study indicates that the endogenous preproglucagon system, exemplified by the entire GCG gene and the receptors for GLP-1 and GLP-2, does not play a major role in normal gut development in the mouse. Furthermore, elevation in local intestinal and circulating levels of GLP-1 and GLP-2 achieved after VSG has limited impact on intestinal morphometry. Hence, although exogenous treatment with GLP-1 and GLP-2 analogs enhances gut growth, the contributions of endogenously-secreted GLP-1 and GLP-2 to gut growth may be more modest and highly context-dependent

Danish Fungi 2020 - Not Just Another Image Recognition Dataset

We introduce a novel fine-grained dataset and bench-mark, the Danish Fungi 2020 (DF20). The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution, rich observation metadata, and well-defined class hierarchy. DF20 has zero overlap with ImageNet, al-lowing unbiased comparison of models fine-tuned from publicly available ImageNet checkpoints. The proposed evaluation protocol enables testing the ability to improve classification using metadata - e.g. precise geographic location, habitat, and substrate, facilitates classifier calibration testing, and finally allows to study the impact of the device settings on the classification performance. Experiments using Convolutional Neural Networks (CNN) and the recent Vision Transformers (ViT) show that DF20 presents a challenging task. Interestingly, ViT achieves results su-perior to CNN baselines with 80.45% accuracy and 0.743 macro F1 score, reducing the CNN error by 9% and 12% respectively. A simple procedure for including metadata into the decision process improves the classification accuracy by more than 2.95 percentage points, reducing the error rate by 15%. The source code for all methods and experiments is available at https://sites.google.com/view/danish-fungi-dataset

5′-AMP Activated Protein Kinase is Involved in the Regulation of Myocardial β-Oxidative Capacity in Mice

5′-adenosine monophosphate-activated protein kinase (AMPK) is considered central in regulation of energy status and substrate utilization within cells. In heart failure the energetic state is compromised and substrate metabolism is altered. We hypothesized that this could be linked to changes in AMPK activity and we therefore investigated mitochondrial oxidative phosphorylation capacity from the oxidation of long- and medium-chain fatty acids (LCFA and MCFA) in cardiomyocytes from young and old mice expressing a dominant negative AMPKα2 (AMPKα2-KD) construct and their wildtype (WT) littermates. We found a 35–45% (P < 0.05) lower mitochondrial capacity for oxidizing MCFA in AMPKα2-KD of both age-groups, compared to WT. This coincided with marked decreases in protein expression (19/29%, P < 0.05) and activity (14/21%, P < 0.05) of 3-hydroxyacyl-CoA-dehydrogenase (HAD), in young and old AMPKα2-KD mice, respectively, compared to WT. Maximal LCFA oxidation capacity was similar in AMPKα2-KD and WT mice independently of age implying that LCFA-transport into the mitochondria was unaffected by loss of AMPK activity or progressing age. Expression of regulatory proteins of glycolysis and glycogen breakdown showed equivocal effects of age and genotype. These results illustrate that AMPK is necessary for normal mitochondrial function in the heart and that decreased AMPK activity may lead to an altered energetic state as a consequence of reduced capacity to oxidize MCFA. We did not identify any clear aging effects on mitochondrial function

mTORC2 and AMPK differentially regulate muscle triglyceride content via Perilipin 3.

OBJECTIVE: We have recently shown that acute inhibition of both mTOR complexes (mTORC1 and mTORC2) increases whole-body lipid utilization, while mTORC1 inhibition had no effect. Therefore, we tested the hypothesis that mTORC2 regulates lipid metabolism in skeletal muscle. METHODS: Body composition, substrate utilization and muscle lipid storage were measured in mice lacking mTORC2 activity in skeletal muscle (specific knockout of RICTOR (Ric mKO)). We further examined the RICTOR/mTORC2-controlled muscle metabolome and proteome; and performed follow-up studies in other genetic mouse models and in cell culture. RESULTS: Ric mKO mice exhibited a greater reliance on fat as an energy substrate, a re-partitioning of lean to fat mass and an increase in intramyocellular triglyceride (IMTG) content, along with increases in several lipid metabolites in muscle. Unbiased proteomics revealed an increase in the expression of the lipid droplet binding protein Perilipin 3 (PLIN3) in muscle from Ric mKO mice. This was associated with increased AMPK activity in Ric mKO muscle. Reducing AMPK kinase activity decreased muscle PLIN3 expression and IMTG content. AMPK agonism, in turn, increased PLIN3 expression in a FoxO1 dependent manner. PLIN3 overexpression was sufficient to increase triglyceride content in muscle cells. CONCLUSIONS: We identified a novel link between mTORC2 and PLIN3, which regulates lipid storage in muscle. While mTORC2 is a negative regulator, we further identified AMPK as a positive regulator of PLIN3, which impacts whole-body substrate utilization and nutrient partitioning