bluuebunny/crossref_metadata_2025_split huggingface dataset:
Organ systems of a Cambrian euarthropod larva
Authors: Smith Martin R. , Long Emma J. , Dhungana Alavya , Dobson Katherine J. , Yang Jie , Zhang Xiguang 
Published: July 2024

AbstractThe Cambrian radiation of euarthropods can be attributed to an adaptable body plan. Sophisticated brains and specialized feeding appendages, which are elaborations of serially repeated organ systems and jointed appendages, underpin the dominance of Euarthropoda in a broad suite of ecological settings. The origin of the euarthropod body plan from a grade of vermiform taxa with hydrostatic lobopodous appendages (‘lobopodian worms’)1,2 is founded on data from Burgess Shale-type fossils. However, the compaction associated with such preservation obscures internal anatomy3–6. Phosphatized microfossils provide a complementary three-dimensional perspective on early crown group euarthropods7, but few lobopodians8,9. Here we describe the internal and external anatomy of a three-dimensionally preserved euarthropod larva with lobopods, midgut glands and a sophisticated head. The architecture of the nervous system informs the early configuration of the euarthropod brain and its associated appendages and sensory organs, clarifying homologies across Panarthropoda. The deep evolutionary position of Youti yuanshi gen. et sp. nov. informs the sequence of character acquisition during arthropod evolution, demonstrating a deep origin of sophisticated haemolymph circulatory systems, and illuminating the internal anatomical changes that propelled the rise and diversification of this enduringly successful group.
A dataset of synthetic art dialogues with ChatGPT
Authors: Gil-Martín Manuel , Luna-Jiménez Cristina , Esteban-Romero Sergio , Estecha-Garitagoitia Marcos , Fernández-Martínez Fernando , D’Haro Luis Fernando 
Published: July 2024

AbstractThis paper introduces Art_GenEvalGPT, a novel dataset of synthetic dialogues centered on art generated through ChatGPT. Unlike existing datasets focused on conventional art-related tasks, Art_GenEvalGPT delves into nuanced conversations about art, encompassing a wide variety of artworks, artists, and genres, and incorporating emotional interventions, integrating speakers’ subjective opinions and different roles for the conversational agents (e.g., teacher-student, expert guide, anthropic behavior or handling toxic users). Generation and evaluation stages of GenEvalGPT platform are used to create the dataset, which includes 13,870 synthetic dialogues, covering 799 distinct artworks, 378 different artists, and 26 art styles. Automatic and manual assessment proof the high quality of the synthetic dialogues generated. For the profile recovery, promising lexical and semantic metrics for objective and factual attributes are offered. For subjective attributes, the evaluation for detecting emotions or subjectivity in the interventions achieves 92% of accuracy using LLM-self assessment metrics.
A peer-and self-group competitive behavior-based socio-inspired approach for household electricity conservation
Authors: Ramnath Gaikwad Sachin , Harikrishnan R. , Muyeen S. M. , Kukker Amit , Pohekar S. D. , Kotecha Ketan 
Published: July 2024

AbstractThis paper proposes a knowledge-based decision-making system for energy bill assessment and competitive energy consumption analysis for energy savings. As humans have a tendency toward comparison between peers and self-groups, the same concept of competitive behavior is utilized to design knowledge-based decision-making systems. A total of 225 house monthly energy consumption datasets are collected for Maharashtra state, along with a questionnaire-based survey that includes socio-demographic information, household appliances, family size, and some other parameters. After data collection, the pre-processing technique is applied for data normalization, and correlation technique-based key features are extracted. These features are used to classify different house categories based on consumption. A knowledge-based system is designed based on historical datasets for future energy consumption prediction and comparison with actual usage. These comparative studies provide a path for knowledgebase system design to generate monthly energy utilization reports for significant behavior changes for energy savings. Further, Linear Programming and Genetic Algorithms are used to optimize energy consumption for different household categories based on socio-demographic constraints. This will also benefit the consumers with an electricity bill evaluation range (i.e., normal, high, or very high) and find the energy conservation potential (kWh) as well as a cost-saving solution to solve real-world complex electricity conservation problem.
Progesterone modulates the immune microenvironment to suppress ovalbumin-induced airway inflammation by inhibiting NETosis
Authors: Wang Lin , Huang Feng-Ying , Dai Shu-Zhen , Fu Yongshu , Zhou Xiangdong , Wang Cai-Chun , Tan Guang-Hong , Li Qi 
Published: July 2024

AbstractStudies have demonstrated that prior to puberty, girls have a lower incidence and severity of asthma symptoms compared to boys. This study aimed to explore the role of progesterone (P4), a sex hormone, in reducing inflammation and altering the immune microenvironment in a mouse model of allergic asthma induced by OVA. Female BALB/c mice with or without ovariectomy to remove the influence of sex hormones were used for the investigations. Serum, bronchoalveolar lavage fluid (BALF), and lung tissue samples were collected for analysis. The results indicated that P4 treatment was effective in decreasing inflammation and mucus secretion in the lungs of OVA-induced allergic asthma mice. P4 treatment also reduced the influx of inflammatory cells into the BALF and increased the levels of Th1 and Th17 cytokines while decreasing the levels of Th2 and Treg cytokines in both BALF and lung microenvironment CD45+ T cells. Furthermore, P4 inhibited the infiltration of inflammatory cells into the lungs, suppressed NETosis, and reduced the number of pulmonary CD4+ T cells while increasing the number of regulatory T cells. The neutrophil elastase inhibitor GW311616A also suppressed airway inflammation and mucus production and modified the secretion of immune Th1, Th2, Th17, and Treg cytokines in lung CD45+ immune cells. These changes led to an alteration of the immunological milieu with increased Th1 and Th17 cells, accompanied by decreased Th2, Treg, and CD44+ T cells, similar to the effects of P4 treatment. Treatment with P4 inhibited NETosis by suppressing the p38 pathway activation, leading to reduced reactive oxygen species production. Moreover, P4 treatment hindered the release of double-stranded DNA during NETosis, thereby influencing the immune microenvironment in the lungs. These findings suggest that P4 treatment may be beneficial in reducing inflammation associated with allergic asthma by modulating the immune microenvironment. In conclusion, this research indicates the potential of P4 as a therapeutic agent for ameliorating inflammation in OVA-induced allergic asthma mice.
Identification and optimization of the key growth parameters involved in carotenoids production of the marine microalga Pavlova gyrans
Authors: Maciel Filipe , Berni Paulo , Geada Pedro , Teixeira José , Silva Joana , Vicente António 
Published: July 2024

AbstractIn this work, a multivariate analysis was carried out, using a Plackett–Burman (PB) design involving seventeen growth parameters, on carotenoids production of Pavlova gyrans (p < 0.10). Each assay was analysed regarding its content (mg g−1) of fucoxanthin (Fx), diatoxanthin, diadinoxanthin, β-carotene (βCar), α-carotene, and the sum of all carotenoids analysed individually (TCar). According to the statistical analysis, modified medium formulations were developed for the particular cases of Fx, βCar, and TCar. The study showed that Fx content was positively affected by nitrogen supplementation and lower light intensities. Higher concentrations of nitrogen and iron increased the final content of βCar as well. Similarly, salinity, light intensity, nitrogen, iron, and cobalt were identified as key factors in TCar production. The PB-based formulations showed significant improvements (p < 0.05) for TCar (11.794 mg g−1) and Fx (6.153 mg g−1) when compared to the control conditions (Walne’s medium—2.010 mg g−1). Furthermore, effective control of key variables (e.g., light intensity) throughout P. gyrans growth proved successful (p < 0.05), increasing the productivity of Fx (0.759 mg L−1 d−1) and TCar (1.615 mg L−1 d−1).
Readability analysis of ChatGPT's responses on lung cancer
Authors: Gencer Adem 
Published: July 2024

AbstractFor common diseases such as lung cancer, patients often use the internet to obtain medical information. As a result of advances in artificial intelligence and large language models such as ChatGPT, patients and health professionals use these tools to obtain medical information. The aim of this study was to evaluate the readability of ChatGPT-generated responses with different readability scales in the context of lung cancer. The most common questions in the lung cancer section of Medscape® were reviewed, and questions on the definition, etiology, risk factors, diagnosis, treatment, and prognosis of lung cancer (both NSCLC and SCLC) were selected. A set of 80 questions were asked 10 times to ChatGPT via the OpenAI API. ChatGPT's responses were tested using various readability formulas. The mean Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning FOG Scale, SMOG Index, Automated Readability Index, Coleman-Liau Index, Linsear Write Formula, Dale-Chall Readability Score, and Spache Readability Formula scores are at a moderate level (mean and standard deviation: 40.52 ± 9.81, 12.56 ± 1.66, 13.63 ± 1.54, 14.61 ± 1.45, 15.04 ± 1.97, 14.24 ± 1.90, 11.96 ± 2.55, 10.03 ± 0.63 and 5.93 ± 0.50, respectively). The readability levels of the answers generated by ChatGPT are "collage" and above and are difficult to read. Perhaps in the near future, the ChatGPT can be programmed to produce responses that are appropriate for people of different educational and age groups.
A novel translational model of atherosclerosis, the ex vivo pump-perfused amputated human limb model
Authors: Hartley Adam , Afoke Jonathan , Liu Guiqing , Owen Samuel , Hajhosseiny Reza , Hassen Kimberly , Punjabi Prakash , Haskard Dorian , Shalhoub Joseph , Khamis Ramzi 
Published: July 2024

AbstractThe preclinical study of atherosclerosis has traditionally centred around the use of small animal models, translating to large animal models, prior to first-in-man studies. We propose to disrupt this paradigm by designing an ex vivo pump perfused human limb model. The novel model consists of taking a freshly amputated limb and incorporating it into an ex situ pump-perfused bypass system (akin to extracorporeal membrane oxygenation), circulating warmed, oxygenated blood. The circuit incorporates an introducer sheath and guiding catheter for intravascular imaging and X-ray angiography. Regular monitoring is performed using blood gas analysis, aiming for physiological parameters. The model maintains oxygen saturations > 99% for the length of perfusion (up to 6-h). Clinical grade X-ray angiography, intravascular ultrasound and optical coherence tomography have been successfully performed. Indocyanine green, a near-infrared fluorescent dye that localises to atherosclerotic plaque, has been injected into the system and left to circulate for 90-min. Fluorescence reflectance imaging of the dissected arterial bed confirmed uptake in areas of calcific atherosclerotic plaque on intravascular imaging. This is the first demonstration of an ex vivo pump-perfused “living” limb experimental model of atherosclerosis, which shows promise for future studies in translational interventional imaging and molecular targeting.
Cross-architecture tuning of silicon and SiGe-based quantum devices using machine learning
Authors: Severin B. , Lennon D. T. , Camenzind L. C. , Vigneau F. , Fedele F. , Jirovec D. , Ballabio A. , Chrastina D. , Isella G. , de Kruijf M. , Carballido M. J. , Svab S. , Kuhlmann A. V. , Geyer S. , Froning F. N. M. , Moon H. , Osborne M. A. , Sejdinovic D. , Katsaros G. , Zumbühl D. M. , Briggs G. A. D. , Ares N. 
Published: July 2024

AbstractThe potential of Si and SiGe-based devices for the scaling of quantum circuits is tainted by device variability. Each device needs to be tuned to operation conditions and each device realisation requires a different tuning protocol. We demonstrate that it is possible to automate the tuning of a 4-gate Si FinFET, a 5-gate GeSi nanowire and a 7-gate Ge/SiGe heterostructure double quantum dot device from scratch with the same algorithm. We achieve tuning times of 30, 10, and 92 min, respectively. The algorithm also provides insight into the parameter space landscape for each of these devices, allowing for the characterization of the regions where double quantum dot regimes are found. These results show that overarching solutions for the tuning of quantum devices are enabled by machine learning.
The effect of aggressive group norms on young adults’ conformity behavior in WhatsApp chats: a vignette-based experiment
Authors: Kreuder Annika , Frick Ulrich , Klütsch Jennifer , Haehn Luise , Schlittmeier Sabine J. 
Published: July 2024

AbstractSocial networking and messaging applications, such as WhatsApp, have become an essential social environment for adolescents and young adults (AYA). While facilitating connectivity, they also bear hazards, including cyber-aggression. This study investigates the impact of (aggressive) group norms on AYA's propensity to expect cyberaggressive behaviors within different group chats. Based on a vignette scenario, realistically simulated WhatsApp group chats enabled scrutinizing, if and how exemplary reactions (funny, aggressive, friendly) of group members influence AYA's conformity to cyber-aggression (N = 500, aged 16 to 29). Additionally, we examined the effect of chat group type—close friends versus fellow students—on the anticipation of aggressive reactions. Sociodemographic, social, and developmental-psychological factors were evaluated for potential effects. Multilevel logistic regression analyses indicated that aggressive group norms significantly predict cyber-aggression anticipation, while no effect of chat group type was observed. Controlling for the size and vivacity of participant’s friend group, gender, age, and educational status were significant predictors: males, younger participants, and non-university students expected higher levels of cyber-aggression conformity. This study underlines the importance of group dynamics on perceptions of cyber-aggression and hints at individual risk factors for AYA's digital communication behavior.
Post-mortem recrystallization of biogenic amorphous calcium carbonate guided by the inherited macromolecular framework
Authors: Stolarski Jarosław , Coronado Ismael , Potocka Marta , Janiszewska Katarzyna , Mazur Maciej , Baronnet Alain , Cruz Juncal A. , Grauby Olivier , Meibom Anders 
Published: July 2024

AbstractIn contrast to abiotically formed carbonates, biogenetic carbonates have been observed to be nanocomposite, organo-mineral structures, the basic build-blocks of which are particles of quasi-uniform size (10–100 nm) organized into complex higher-order hierarchical structures, typically with highly controlled crystal-axis alignments. Some of these characteristics serve as criteria for inferring a biological origin and the state of preservation of fossil carbonate materials, and to determine whether the biomineralization process was biologically induced or controlled. Here we show that a calcium storage structure formed by the American lobster, a gastrolith initially consisting of amorphous calcium carbonate (ACC) and amorphous calcium phosphate (ACP), post-mortem can crystallize into (thus secondary) calcite with structural properties strongly influenced by the inherited organic matrix. This secondary calcite meets many structural criteria for biominerals (thus called the biomorphic calcite), but differs in trace element distributions (e.g., P and Mg). Such observations refine the capability to determine whether a fossil carbonates can be attributed to biogenic processes, with implications for the record of life on Earth and other terrestrial planets.
Examining bi-directional links between loneliness, social connectedness and sleep from a trait and state perspective
Authors: Dworschak Christine , Mäder Thomas , Rühlmann Charlotta , Maercker Andreas , Kleim Birgit 
Published: July 2024

AbstractGreater loneliness as well as a lack of social connectedness have often been associated with poorer sleep. However, the temporal dynamics and direction of these associations remain unclear. Aim of the current study was to examine bi-directional associations between loneliness/social connectedness and sleep in 48 stress-exposed medical students during their first medical internship, considered a period of heightened stress. We obtained trait-level questionnaire data on loneliness and global sleep completed before and during the internship as well as state-level diary- and wearable-based data on daily changes in social connectedness and sleep collected twice over the period of seven consecutive days, once before and once during the internship. Bi-directional associations among greater loneliness and higher daytime dysfunction on trait-level were identified. In addition, several uni-directional associations between loneliness/social connectedness and sleep were found on trait- and state-level. In sum, findings of this study point at a bi-directional relation among loneliness/social connectedness and sleep, in which variables seem to reciprocally influence each other across longer-term periods as well as on a day-to-day basis.
Diagnostics of unmanned aerial vehicle with recurrence based approach of piezo-element voltage signals
Authors: Ambrożkiewicz Bartłomiej , Dzienis Paweł , Ambroziak Leszek , Koszewnik Andrzej , Syta Arkadiusz , Ołdziej Daniel , Pakrashi Vikram 
Published: July 2024

AbstractThis work experimentally addresses damage calibration of an unmanned aerial vehicle in operational condition. A wide range of damage level and types are simulated and controlled by an electric motor via pulse width modulation in this regard. The measurement is carried out via established protocols of using a piezo-patch on one of the 8 arms, utilising the vibration sensitivity and flexibility of the arms, demonstrating repeatability of such protocol. Subsequently, recurrence analysis on the voltage time series data is performed for detection of damage. Quantifiers of damage extent are then created for the full range of damage conditions, including the extreme case of complete loss of power. Experimental baseline condition for no damage condition is also established in this regard. Both diagonal-line and vertical-line based indicators from recurrence analysis are sensitive to the quantitative estimates of damage levels and a statistical test of significance analysis confirms that it is possible to automate distinguishing the levels of damage. The damage quantifiers proposed in this paper are useful for rapid monitoring of unmanned aerial vehicle operations of connection.
Large-scale proteomics reveals precise biomarkers for detection of ovarian cancer in symptomatic women
Authors: Ivansson Emma , Hedlund Lindberg Julia , Stålberg Karin , Sundfeldt Karin , Gyllensten Ulf , Enroth Stefan 
Published: July 2024

AbstractOvarian cancer is the 8th most common cancer among women and has a 5-year survival of only 30–50%. While the survival is close to 90% for stage I tumours it is only 20% for stage IV. Current biomarkers are not sensitive nor specific enough, and novel biomarkers are urgently needed. We used the Explore PEA technology for large-scale analysis of 2943 plasma proteins to search for new biomarkers using two independent clinical cohorts. The discovery analysis using the first cohort identified 296 proteins that had significantly different levels in malign tumours as compared to benign and for 269 (91%) of these, the association was replicated in the second cohort. Multivariate modelling, including all proteins independent of their association in the univariate analysis, identified a model for separating benign conditions from malign tumours (stage I–IV) consisting of three proteins; WFDC2, KRT19 and RBFOX3. This model achieved an AUC of 0.92 in the replication cohort and a sensitivity and specificity of 0.93 and 0.77 at a cut-off developed in the discovery cohort. There was no statistical difference of the performance in the replication cohort compared to the discovery cohort. WFDC2 and KRT19 have previously been associated with ovarian cancer but RBFOX3 has not previously been identified as a potential biomarker. Our results demonstrate the ability of using high-throughput precision proteomics for identification of novel plasma protein biomarker for ovarian cancer detection.
Improving consumer understanding of pesticide toxicity labels: experimental evidence
Authors: Hosni Hanin , Segovia Michelle , Zhao Shuoli , Palma Marco A. , Skevas Theodoros 
Published: July 2024

AbstractConsumers often inadvertently misperceive the health hazards associated with over-the-counter pesticides under the current textual labeling policy, potentially leading to improper use. We conducted an incentivized framed field experiment with eye tracking to evaluate the effectiveness of the current pesticide labels that convey risk using signal words (Caution, Warning, Danger) compared to two visually focused label alternatives: traffic light colors and skull intensity symbols. A total of 166 participants were randomly assigned to one of three label formats and asked to rank toxicity levels and make purchasing decisions within multiple price lists. Results show that signal words fail to adequately communicate toxicity levels. Specifically, participants’ correct assessment of toxicity level dramatically improves from 54% under the existing signal word label to 95% under the traffic light and 83% under the skull intensity symbol labels. We also find that participants are more likely to choose the less toxic alternatives under the new labels, suggesting the current labeling system may affect choice and have unintended adverse effects on human health.
Differential circulating cytokine profiles in acute coronary syndrome versus stable coronary artery disease
Authors: Maaniitty Eveliina , Jalkanen Juho , Sinisilta Sami , Gunn Jarmo , Vasankari Tuija , Biancari Fausto , Jalkanen Sirpa , Airaksinen K. E. Juhani , Hollmen Maija , Kiviniemi Tuomas 
Published: July 2024

AbstractChronic inflammation plays a crucial role in coronary artery disease (CAD), but differences in specific cytokine profiles between acute coronary syndrome (ACS) and stable CAD remain unknown. We investigated cytokine differences between these two manifestations of CAD. The study included 308 patients with angiographically detected, hemodynamically significant CAD: 150 patients undergone angiography for ACS, 158 patients undergone angiography for stable CAD. To assess dynamic changes, 116 patients had index angiogram at least 3 months earlier. We measured the serum concentrations of 48 circulating cytokines. The ACS group had decreased interleukin (IL) 4 (p = 0.005), and increased IL-8 (p = 0.008), hepatocyte growth factor (HGF) (p < 0.001) and macrophage colony-stimulating factor (M-CSF) (p = 0.002) levels compared with the stable CAD group. Multivariable logistic regression revealed increased levels of HGF (OR 18.050 [95% CI 4.372–74.517], p < 0.001), M-CSF (OR 2.257 [1.375–3.705], p = 0.001) and IL-6 (OR 1.586 [1.131–2.224], p = 0.007), independently associated with ACS. In the post-angiography group, only diminished platelet-derived growth factor-BB levels in ACS-manifested patients were observed (OR 0.478, [0.279–0.818], p = 0.007). Cytokine profiles differ between ACS and stable CAD. Such differences seem to be mainly reversible within 3 months after ACS. Thus, targeting one or two cytokines only might not offer one-size fits all-therapeutic approach for CAD-associated inflammation.Trial registration: NCT03444259.