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The rise of generative AI tools has sparked debates about the labeling of AI-generated content. Yet, the impact of such labels remains uncertain. In two preregistered online experiments among US and UK participants ( N = 4,976), we show that while participants did not equate "AI-generated" with "False," labeling headlines as AI-generated lowered their perceived accuracy and participants' willingness to share them, regardless of whether the headlines were true or false, and created by humans or AI. The impact of labeling headlines as AI-generated was three times smaller than labeling them as false. This AI aversion is due to expectations that headlines labeled as AI-generated have been entirely written by AI with no human supervision. These findings suggest that the labeling of AI-generated content should be approached cautiously to avoid unintended negative effects on harmless or even beneficial AI-generated content and that effective deployment of labels requires transparency regarding their meaning., (© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences.)

Background: In obesity, adipose tissue undergoes a remodeling process characterized by increased adipocyte size (hypertrophia) and number (hyperplasia). The ability to tip the balance toward the hyperplastic growth, with recruitment of new fat cells through adipogenesis, seems to be critical for a healthy adipose tissue expansion, as opposed to a hypertrophic growth that is accompanied by the development of inflammation and metabolic dysfunction. However, the molecular mechanisms underlying the fine-tuned regulation of adipose tissue expansion are far from being understood., Methods: We analyzed by mass spectrometry-based proteomics visceral white adipose tissue (vWAT) samples collected from C57BL6 mice fed with a HFD for 8 weeks. A subset of these mice, called low inflammation (Low-INFL), showed reduced adipose tissue inflammation, as opposed to those developing the expected inflammatory response (Hi-INFL). We identified the discriminants between Low-INFL and Hi-INFL vWAT samples and explored their function in Adipose-Derived human Mesenchymal Stem Cells (AD-hMSCs) differentiated to adipocytes., Results: vWAT proteomics allowed us to quantify 6051 proteins. Among the candidates that most differentiate Low-INFL from Hi-INFL vWAT, we found proteins involved in adipocyte function, including adiponectin and hormone sensitive lipase, suggesting that adipocyte differentiation is enhanced in Low-INFL, as compared to Hi-INFL. The chromatin modifier SET and MYND Domain Containing 3 (SMYD3), whose function in adipose tissue was so far unknown, was another top-scored hit. SMYD3 expression was significantly higher in Low-INFL vWAT, as confirmed by western blot analysis. Using AD-hMSCs in culture, we found that SMYD3 mRNA and protein levels decrease rapidly during the adipocyte differentiation. Moreover, SMYD3 knock-down before adipocyte differentiation resulted in reduced H3K4me3 and decreased cell proliferation, thus limiting the number of cells available for adipogenesis., Conclusions: Our study describes an important role of SMYD3 as a newly discovered regulator of adipocyte precursor proliferation during the early steps of adipogenesis., (© 2023. The Author(s).)

Human lifetime exposure to arsenic through drinking water, food supply or industrial pollution leads to its accumulation in many organs such as liver, kidneys, lungs or pancreas but also adipose tissue. Recently, population-based studies revealed the association between arsenic exposure and the development of metabolic diseases such as obesity and type 2 diabetes. To shed light on the molecular bases of such association, we determined the concentration that inhibited 17% of cell viability and investigated the effects of arsenic acute exposure on adipose-derived human mesenchymal stem cells differentiated in vitro into mature adipocytes and treated with sodium arsenite (NaAsO 2 , 10 nM to 10 µM). Untargeted metabolomics and gene expression analyses revealed a strong dose-dependent inhibition of lipogenesis and lipolysis induction, reducing the cellular ability to store lipids. These dysregulations were emphasized by the inhibition of the cellular response to insulin, as shown by the perturbation of several genes and metabolites involved in the mentioned biological pathways. Our study highlighted the activation of an adaptive oxidative stress response with the strong induction of metallothioneins and increased glutathione levels in response to arsenic accumulation that could exacerbate the decreased insulin sensitivity of the adipocytes. Arsenic exposure strongly affected the expression of arsenic transporters, responsible for arsenic influx and efflux, and induced a pro-inflammatory state in adipocytes by enhancing the expression of the inflammatory interleukin 6 (IL6). Collectively, our data showed that an acute exposure to low levels of arsenic concentrations alters key adipocyte functions, highlighting its contribution to the development of insulin resistance and the pathogenesis of metabolic disorders., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Some major social media companies are announcing plans to tokenize user engagements, derived from blockchain-based decentralized social media. This would bring financial and reputational incentives for engagement, which might lead users to post more objectionable content. Previous research showed that financial or reputational incentives for accuracy decrease the willingness to share misinformation. However, it is unclear to what extent such outcome would change if engagements instead of accuracy were incentivized, which is a more realistic scenario. To address this question, we conducted a survey experiment to examine the effects of hypothetical token incentives. We find that a simple nudge about the possibility of earning token-based points for the achieved user engagements increases the willingness to share different kinds of news, including misinformation. The presence of penalties for objectionable posts diminishes the positive effect of tokenization rewards on misinformation sharing, but it does not eliminate it. These results have policy implications for content moderation practices if platforms embrace decentralization and engagement tokenization., (© 2023. Springer Nature Limited.)

Many NLP applications require manual text annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of complexity, the tasks may be conducted by crowd workers on platforms such as MTurk as well as trained annotators, such as research assistants. Using four samples of tweets and news articles ( n = 6,183), we show that ChatGPT outperforms crowd workers for several annotation tasks, including relevance, stance, topics, and frame detection. Across the four datasets, the zero-shot accuracy of ChatGPT exceeds that of crowd workers by about 25 percentage points on average, while ChatGPT's intercoder agreement exceeds that of both crowd workers and trained annotators for all tasks. Moreover, the per-annotation cost of ChatGPT is less than $0.003-about thirty times cheaper than MTurk. These results demonstrate the potential of large language models to drastically increase the efficiency of text classification.

Abusive head trauma (AHT) is a leading cause of mortality and morbidity in infants. While the reported incidence is close to 40 cases per 100'000 births/year, misdiagnoses are commonly observed in cases with atypical, subacute, or chronic presentation. Currently, standard clinical evaluation of inflicted intracranial hemorrhagic injury (ICH) in infants urgently requires a screening test able to identify infants who need additional investigations. Blood biomarkers characteristic of AHT may assist in detecting these infants, improving prognosis through early medical care. To date, the application of innovative omics technologies in retrospective studies of AHT in infants is rare, due also to the blood serum and cerebrospinal fluid of AHT cases being scarce and not systematically accessible. Here, we explored the circulating blood proteomes of infants with severe AHT and their atraumatic controls. We discovered 165 circulating serum proteins that display differential changes in AHT cases compared with atraumatic controls. The peripheral blood proteomes of pediatric AHT commonly reflect: (i) potentially secreted proteome from injured brain, and (ii) proteome dysregulated in the system's circulation by successive biological events following acute ICH. This study opens up a novel opportunity for research efforts in clinical screening of AHT cases., (© 2023 The Authors. Proteomics published by Wiley-VCH GmbH.)

Background: According to the World Health Organization, road traffic injuries lead to 1.3 million deaths each year and represent the leading cause of death for young adults under 30 years old. The use of psychoactive substances, including alcohol, drugs and pharmaceuticals, is a well-known risk factor for road traffic injuries. Our study aims to assess the prevalence of substances consumed by drivers in western Switzerland. Such studies are pivotal to improving prevention and developing public awareness campaigns., Methods: To assess the prevalence of psychoactive substances among drivers, roadside controls were performed in collaboration with local police, using their classical sampling procedures to detect drivers under the influence of drugs or alcohol over two time periods (P1: 2006-2008, P2: 2017-2020). When impaired driving was not suspected by the police, minimally invasive sampling strategies (i.e., oral fluids during P1 and dried blood spots during P2) were performed on volunteer drivers after a road safety survey. A posteriori analyses and statistical interpretation were then performed., Results: Among the 1605 drivers included in the study, 1048 volunteers provided an oral fluid sample, while 299 provided a dried blood spot sample. The percentage of drivers testing positive for at least one substance that can impact driving abilities was stable over time, with a rate of 10.5% positivity measured over both periods. Considering the different categories of substances, a slight variation was observed between both periods, with 7.6 and 6.3% of pharmaceuticals and 3.6 and 4.9% of illicit drugs for P1 and P2, respectively. Regarding the consumption of illicit drugs, the highest percentage of positivity was measured in biological fluids of drivers under the age of 35, during nights and week-ends, periods which are considered particularly prone to fatal accidents for this age group. Disturbingly, the road safety survey highlighted that drivers' perception of the risk of getting positively controlled while driving after drug consumption is low (3.3 on a 1-to-10 scale, N = 299)., Conclusion: The number of positive cases measured in voluntary drivers who passed the preliminary police check demonstrates the importance of systematic biofluid sampling strategies regarding driving under the influence of psychoactive substances. Although the number of fatal road accidents globally has decreased over time, the results of this study reveal the need for both better prevention and deterrent processes that could potentially reduce the risk of fatal road accidents associated with drug consumption., (© 2022. The Author(s).)

Cobalt, chromium, and nickel are used in orthopedic prostheses. They can be released, accumulate in many organs, and be toxic. The aim of this study is to evaluate the cytotoxicity of these metals on human hepatocytes and to improve our knowledge of their cellular toxicity mechanisms by metabolomic analysis. HepaRG cells were incubated for 48 h with increasing concentrations of metals to determine their IC 50 . Then, a nontargeted metabolomic study using liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was done at IC 50 and at a lower concentration (100 nM), near to those found in the blood and liver of patients with prostheses. IC 50 were defined at 940, 2, and 1380 μM for Co, Cr, and Ni, respectively. In vitro , Cr appears to be much more toxic than Co and Ni. Metabolomic analysis revealed the disruption of metabolic pathways from the low concentration of 100 nM, in particular tryptophan metabolism and lipid metabolism illustrated by an increase in phenylacetylglycine, a marker of phospholipidosis, for all three metals. They also appear to be responsible for oxidative stress. Dysregulation of these pathways impacts hepatocyte metabolism and may result in hepatotoxicity. Further investigations on accessible biological matrices should be conducted to correlate our in vitro results with the clinical data of prostheses-bearing patients.

The peroxisome proliferator-activated receptors (PPARs) are nuclear receptors involved in the regulation of the metabolic homeostasis and therefore represent valuable therapeutic targets for the treatment of metabolic diseases. The development of more balanced drugs interacting with PPARs, devoid of the side-effects showed by the currently marketed PPARγ full agonists, is considered the major challenge for the pharmaceutical companies. Here we present a chemoinformatics search approach for new ligands that let us identify a novel PPAR pan-agonist with a very attractive activity profile being able to reduce lipid accumulation and improve insulin sensitivity. This compound represents, therefore, the potential lead of a new class of drugs for treatment of dyslipidemic type 2 diabetes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Masson SAS. All rights reserved.)

Obesity is considered as a major public health concern with strong economic and social burdens. Exposure to pollutants such as heavy metals can contribute to the development of obesity and its associated metabolic disorders, including type 2 diabetes and cardiovascular diseases. Adipose tissue is an endocrine and paracrine organ that plays a key role in the development of these diseases and is one of the main target of heavy metal accumulation. In this study, we determined by inductively coupled plasma mass spectrometry cadmium concentrations in human subcutaneous and visceral adipose tissues, ranging between 2.5 nM and 2.5 µM. We found a positive correlation between cadmium levels and age, sex and smoking status and a negative correlation between cadmium and body mass index. Based on cadmium adipose tissue concentrations found in humans, we investigated the effects of cadmium exposure, at concentrations between 1 nM and 10 µM, on adipose-derived human mesenchymal stem cells differentiated into mature adipocytes in vitro. Transcriptomic analysis highlighted that such exposure altered the expression of genes involved in trace element homeostasis and heavy metal detoxification, such as Solute Carrier Family transporters and metallothioneins. This effect correlated with zinc level alteration in cells and cellular media. Interestingly, dysregulation of zinc homeostasis and transporters has been particularly associated with the development of obesity and type 2 diabetes. Moreover, we found that cadmium exposure induces the pro-inflammatory state of the adipocytes by enhancing the expression of genes such as IL-6, IL-1B and CCL2, cytokines also induced in obesity. Finally, cadmium modulates various adipocyte functions such as the insulin response signaling pathway and lipid homeostasis. Collectively, our data identified some of the cellular mechanisms by which cadmium alters adipocyte functions, thus highlighting new facets of its potential contribution to the progression of metabolic disorders., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Despite heightened awareness of the detrimental impact of hate speech on social media platforms on affected communities and public discourse, there is little consensus on approaches to mitigate it. While content moderation-either by governments or social media companies-can curb online hostility, such policies may suppress valuable as well as illicit speech and might disperse rather than reduce hate speech. As an alternative strategy, an increasing number of international and nongovernmental organizations (I/NGOs) are employing counterspeech to confront and reduce online hate speech. Despite their growing popularity, there is scant experimental evidence on the effectiveness and design of counterspeech strategies (in the public domain). Modeling our interventions on current I/NGO practice, we randomly assign English-speaking Twitter users who have sent messages containing xenophobic (or racist) hate speech to one of three counterspeech strategies-empathy, warning of consequences, and humor-or a control group. Our intention-to-treat analysis of 1,350 Twitter users shows that empathy-based counterspeech messages can increase the retrospective deletion of xenophobic hate speech by 0.2 SD and reduce the prospective creation of xenophobic hate speech over a 4-wk follow-up period by 0.1 SD. We find, however, no consistent effects for strategies using humor or warning of consequences. Together, these results advance our understanding of the central role of empathy in reducing exclusionary behavior and inform the design of future counterspeech interventions., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)