Classification of Human- and AI-Generated Texts: Investigating Features for ChatGPT

Recently, generative AIs like ChatGPT have become available to the wide public. These tools can for instance be used by students to generate essays or whole theses. But how does a teacher know whether a text is written by a student or an AI? In our work, we explore traditional and new features to (1) detect text generated by AI from scratch and (2) text rephrased by AI. Since we found that classification is more difficult when the AI has been instructed to create the text in a way that a human would not recognize that it was generated by an AI, we also investigate this more advanced case. For our experiments, we produced a new text corpus covering 10 school topics. Our best systems to classify basic and advanced human-generated/AI-generated texts have F1-scores of over 96%. Our best systems for classifying basic and advanced human-generated/AI-rephrased texts have F1-scores of more than 78%. The systems use a combination of perplexity, semantic, list lookup, error-based, readability, AI feedback, and text vector features. Our results show that the new features substantially help to improve the performance of many classifiers. Our best basic text rephrasing detection system even outperforms GPTZero by 183.8% relative in F1-score

Cardiac multiscale bioimaging: from nano- through micro- to mesoscales.

Cardiac multiscale bioimaging is an emerging field that aims to provide a comprehensive understanding of the heart and its functions at various levels, from the molecular to the entire organ. It combines both physiologically and clinically relevant dimensions: from nano- and micrometer resolution imaging based on vibrational spectroscopy and high-resolution microscopy to assess molecular processes in cardiac cells and myocardial tissue, to mesoscale structural investigations to improve the understanding of cardiac (patho)physiology. Tailored super-resolution deep microscopy with advanced proteomic methods and hands-on experience are thus strategically combined to improve the quality of cardiovascular research and support future medical decision-making by gaining additional biomolecular information for translational and diagnostic applications

EfficientBioAI: Making Bioimaging AI Models Efficient in Energy, Latency and Representation

Artificial intelligence (AI) has been widely used in bioimage image analysis nowadays, but the efficiency of AI models, like the energy consumption and latency is not ignorable due to the growing model size and complexity, as well as the fast-growing analysis needs in modern biomedical studies. Like we can compress large images for efficient storage and sharing, we can also compress the AI models for efficient applications and deployment. In this work, we present EfficientBioAI, a plug-and-play toolbox that can compress given bioimaging AI models for them to run with significantly reduced energy cost and inference time on both CPU and GPU, without compromise on accuracy. In some cases, the prediction accuracy could even increase after compression, since the compression procedure could remove redundant information in the model representation and therefore reduce over-fitting. From four different bioimage analysis applications, we observed around 2-5 times speed-up during inference and 30-80$\%$ saving in energy. Cutting the runtime of large scale bioimage analysis from days to hours or getting a two-minutes bioimaging AI model inference done in near real-time will open new doors for method development and biomedical discoveries. We hope our toolbox will facilitate resource-constrained bioimaging AI and accelerate large-scale AI-based quantitative biological studies in an eco-friendly way, as well as stimulate further research on the efficiency of bioimaging AI.Comment: 17 pages, 6 figure

Valuing Water - A Globally Sustainable Approach for the Pharmaceutical Industry

Water resources around the globe are at risk from expanding demand and decreased availability. All sectors of society rely on water for operation – agriculture, industry, power generation, and domestic users all require a constant, clean supply. As a result of population growth and environmental stress, more than one billion people do not have access to clean water, putting a strain on both people and societies, and leading to high costs to ensure supply is not diminished in any sector. As both water availability and quality are projected to decrease in the future, every sector is at risk and might want to reconsider their current relationship with this important resource. Th is analysis focuses on the water-related risks to the industrial sector, specifi cally the pharmaceutical industry. Drug discovery and processing are water-intensive processes that require large amounts of high purity water, presenting a risk to the continuation of business operations. In a changing and uncertain future, the pharmaceutical industry’s relationship with water must also necessarily change in order to continue manufacturing high-quality drugs at a low cost. Six diff erent categories for water-related business risk are outlined and include: changing business demands, stakeholder issues, supply chain, source water quality, regulatory environment, and water availability and climate change. Th is document helps companies concerned about these water-related business risks address the following questions: • Why should pharmaceutical companies consider water in the business structure? • Who are the global and local players in the movement toward enhanced water management? • What types of quantitative and qualitative steps can be taken by the pharmaceutical industry to be proactive in water management? • Where are the locations that may be additionally stressed due to our changing environment? • When can pharmaceutical companies act and at what time-scale? • How can pharmaceutical companies manage water risk and adequately value water? By taking a hands-on approach to managing water-related business risk, pharmaceutical companies can avoid costs and instead create value. Th e pharmaceutical industry has a unique opportunity to enhance its mission of sustaining human health by leading other industries in proactive and innovative water management. Pharmaceutical companies have a number of options when it comes to adapting their relationship with water to a changing future. However, navigating these options can be costly and time-consuming. In addition, the cost of water for these companies, compared to other resources, is minimal, shielding its importance from business decisions that relate to it. Th is document presents a decision-making framework designed to help companies save time and resources required to inform options analysis. It is in the form of a comprehensive and easy-to-use Water Valuation Tool consisting of six key steps: Sponsorship, Learn, Plan, Act, Share, and Re-Evaluate. Each step is designed to help a company learn new and innovative ways to value water beyond the traditional cost. Global companies are currently benefi ting from considering water use not only in everyday facility operations, but future business planning as well. Included in this document are case studies, along with an example of how this Water Valuation Tool is applied. Th is decision-making framework will assist corporate users to to design strategies most fi tting to individual situations and internal business structure.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/58622/1/merk masters project.pd

Visible-Light Photoswitchable Benzimidazole Azo-Arenes as beta-Arrestin2-Biased Selective Cannabinoid 2 Receptor Agonists

Acknowledgements The authors would like to acknowledge Dr. Andrea Holme for excellent technical support and the Iain Fraser Cytometry Centre (University of Aberdeen) for providing access to their equipment. The authors would like to thank Dr. Matthias Scheiner for his contributions towards the development of the calcium mobilization assay and Dr. Valérie Jahns for her efforts towards faster automated analysis of the obtained results. Nick Verhavert is acknowledged for his assistance with the NanoBiT® assay. Diego Rodriguez-Soacha is acknowledged for establishing the rCB1R radioligand binding assay in our laboratory. Special thanks to Dr. Rangan Maitra and RTI International for providing the G16 coupled hCB1 and hCB2 CHO-K1 cell lines. The authors thank Nadine Yurdagül-Hemmrich and Annette Hannawacker for excellent technical support. This project was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft under DFG DE1546/10-1). J. N. Hislop’s financing support was given by NHS Grampian. The research visit of S. A. M. Steinmüller in Dr. Hislop’s laboratory was funded by the Elite Network of Bavaria (grant N° K-BM-2013-247). J. Fender and A. Tutov were supported by the International Doctoral Program “Receptor Dynamics” funded within the framework of the Elite Network of Bavaria (grant N° K-BM-2013- 247). M. H. Deventer was funded by the Research FoundationFlanders (FWO; grant 1S54521N).Peer reviewe

Cardiac recovery from pressure overload is not altered by thyroid hormone status in old mice

IntroductionThyroid hormones (THs) are known to have various effects on the cardiovascular system. However, the impact of TH levels on preexisting cardiac diseases is still unclear. Pressure overload due to arterial hypertension or aortic stenosis and aging are major risk factors for the development of structural and functional abnormalities and subsequent heart failure. Here, we assessed the sensitivity to altered TH levels in aged mice with maladaptive cardiac hypertrophy and cardiac dysfunction induced by transverse aortic constriction (TAC).MethodsMice at the age of 12 months underwent TAC and received T4 or anti-thyroid medication in drinking water over the course of 4 weeks after induction of left ventricular pressure overload.ResultsT4 excess or deprivation in older mice had no or only very little impact on cardiac function (fractional shortening), cardiac remodeling (cardiac wall thickness, heart weight, cardiomyocyte size, apoptosis, and interstitial fibrosis), and mortality. This is surprising because T4 excess or deprivation had significantly changed the outcome after TAC in young 8-week-old mice. Comparing the gene expression of deiodinases (Dio) 2 and 3 and TH receptor alpha (TRα) 1 and the dominant-negative acting isoform TRα2 between young and aged mice revealed that aged mice exhibited a higher expression of TRα2 and Dio3, while expression of Dio2 was reduced compared with young mice. These changes in Dio2 and 3 expressions might lead to reduced TH availability in the hearts of 12-month-old mice accompanied by reduced TRα action due to higher TRα2.DiscussionIn summary, our study shows that low and high TH availability have little impact on cardiac function and remodeling in older mice with preexisting pressure-induced cardiac damage. This observation seems to be the result of an altered expression of deiodinases and TRα isoforms, thus suggesting that even though cardiovascular risk is increasing with age, the response to TH stress may be dampened in certain conditions

Frühe mathematische Bildung - Ziele und Gelingensbedingungen für den Elementar- und Primarbereich

Im Rahmen der Schriftenreihe "Wissenschaftliche Untersuchungen zur Arbeit der Stiftung 'Haus der kleinen Forscher'" werden regelmäßig wissenschaftliche Beiträge von renommierten Expertinnen und Experten aus dem Bereich der frühen Bildung veröffentlicht. Diese Schriftenreihe dient einem fachlichen Dialog zwischen Stiftung, Wissenschaft und Praxis, mit dem Ziel, allen Kitas, Horten und Grundschulen in Deutschland fundierte Unterstützung für ihren frühkindlichen Bildungsauftrag zu geben. Der vorliegende achte Band der Reihe mit einem Geleitwort von Kristina Reiss stellt die Ziele und Gelingensbedingungen mathematischer Bildung im Elementar- und Primarbereich in den Fokus. Christiane Benz, Meike Grüßing, Jens Holger Lorenz, Christoph Selter und Bernd Wollring spezifizieren in ihrer Expertise pädagogisch-inhaltliche Zieldimensionen mathematischer Bildung im Kita- und Grundschulalter. Neben einer theoretischen Fundierung verschiedener Zielbereiche werden Instrumente für deren Messung aufgeführt. Des Weiteren erörtern die Autorinnen und Autoren Gelingensbedingungen für eine effektive und wirkungsvolle frühe mathematische Bildung in der Praxis. Sie geben zudem Empfehlungen für die Weiterentwicklung der Stiftungsangebote und die wissenschaftliche Begleitung der Stiftungsarbeit im Bereich Mathematik. Das Schlusskapitel des Bandes beschreibt die Umsetzung dieser fachlichen Empfehlungen in den inhaltlichen Angeboten der Stiftung "Haus der kleinen Forscher"

PKA catalytic subunit mutations in adrenocortical Cushing's adenoma impair association with the regulatory subunit

We recently identified a high prevalence of mutations affecting the catalytic (C alpha) subunit of protein kinase A (PKA) in cortisol-secreting adrenocortical adenomas. The two identified mutations (Leu206Arg and Leu199_Cys200insTrp) are associated with increased PKA catalytic activity, but the underlying mechanisms are highly controversial. Here we utilize a combination of biochemical and optical assays, including fluorescence resonance energy transfer in living cells, to analyze the consequences of the two mutations with respect to the formation of the PKA holoenzyme and its regulation by cAMP. Our results indicate that neither mutant can form a stable PKA complex, due to the location of the mutations at the interface between the catalytic and the regulatory subunits. We conclude that the two mutations cause high basal catalytic activity and lack of regulation by cAMP through interference of complex formation between the regulatory and the catalytic subunits of PKA

Eukaryotic elongation factor 2 is a prognostic marker and its kinase a potential therapeutic target in HCC

Hepatocellular carcinoma is a cancer with increasing incidence and largely refractory to current anticancer drugs. Since Sorafenib, a multikinase inhibitor has shown modest efficacy in advanced hepatocellular carcinoma additional treatments are highly needed. Protein phosphorylation via kinases is an important post-translational modification to regulate cell homeostasis including proliferation and apoptosis. Therefore kinases are valuable targets in cancer therapy. To this end we performed 2D differential gel electrophoresis and mass spectrometry analysis of phosphoprotein-enriched lysates of tumor and corresponding non-tumorous liver samples to detect differentially abundant phosphoproteins to screen for novel kinases as potential drug targets. We identified 34 differentially abundant proteins in phosphoprotein enriched lysates. Expression and distribution of the candidate protein eEF2 and its phosphorylated isoform was validated immunohistochemically on 78 hepatocellular carcinoma and non-tumorous tissue samples. Validation showed that total eEF2 and phosphorylated eEF2 at threonine 56 are prognostic markers for overall survival of HCC-patients. The activity of the regulating eEF2 kinase, compared between tumor and non-tumorous tissue lysates by in vitro kinase assays, is more than four times higher in tumor tissues. Functional analyzes regarding eEF2 kinase were performed in JHH5 cells with CRISPR/Cas9 mediated eEF2 kinase knock out. Proliferation and growth is decreased in eEF2 kinase knock out cells

Smoking cessation and depression after acute coronary syndrome.

Smoking and depression are risk factors for acute coronary syndrome (ACS) that often co-exist. We investigated the evolution of depression according to smoking cessation one-year after ACS. Data from 1822 ACS patients of the Swiss multicenter SPUM-ACS cohort study were analyzed over a one-year follow-up. Participants were classified in three groups based on smoking status one-year post-ACS - continuous smokers, smokers who quit within the year, and non-smokers. Depression status at baseline and one-year was assessed with the Center for Epidemiologic Studies Depression scale (CES-D) and antidepressant drug use. A CES-D score ≥ 16 defined depression. A multivariate-adjusted logistic regression model was used to calculate odds ratios (OR) between groups. The study sample mean age was 62.4 years and females represented 20.8%. At baseline, 22.6% were depressed, 40.9% were smokers, and 47.5% of these quit smoking over the year post-ACS. In comparison to depressed continuous smokers, depressed smokers who quit had an adjusted OR 2.59 (95% confidence interval (CI) 1.27-5.25) of going below a CES-D score of 16 or not using antidepressants. New depression at one-year was found in 24.4% of non-depressed smokers who quit, and in 27.1% of non-depressed continuous smokers, with an adjusted OR 0.85 (95% CI 0.55-1.29) of moving to a CES-D score of ≥16 or using antidepressants. In conclusion, smokers with depression at time of ACS who quit smoking improved their depression more frequently compared to continuous smokers. The incidence of new depression among smokers who quit after ACS was similar compared to continuous smokers