bluuebunny/crossref_metadata_2025_split huggingface dataset:
ETV7 reduces inflammatory responses in breast cancer cells by repressing the TNFR1/NF-κB axis
Authors: Meškytė Erna Marija , Pezzè Laura , Bartolomei Laura , Forcato Mattia , Bocci Irene Adelaide , Bertalot Giovanni , Barbareschi Mattia , Oliveira-Ferrer Leticia , Bisio Alessandra , Bicciato Silvio , Baltriukienė Daiva , Ciribilli Yari 
Published: April 2023

AbstractThe transcription factor ETV7 is an oncoprotein that is up-regulated in all breast cancer (BC) types. We have recently demonstrated that ETV7 promoted breast cancer progression by increasing cancer cell proliferation and stemness and was also involved in the development of chemo- and radio-resistance. However, the roles of ETV7 in breast cancer inflammation have yet to be studied. Gene ontology analysis previously performed on BC cells stably over-expressing ETV7 demonstrated that ETV7 was involved in the suppression of innate immune and inflammatory responses. To better decipher the involvement of ETV7 in these signaling pathways, in this study, we identified TNFRSF1A, encoding for the main receptor of TNF-α, TNFR1, as one of the genes down-regulated by ETV7. We demonstrated that ETV7 directly binds to the intron I of this gene, and we showed that the ETV7-mediated down-regulation of TNFRSF1A reduced the activation of NF-κB signaling. Furthermore, in this study, we unveiled a potential crosstalk between ETV7 and STAT3, another master regulator of inflammation. While it is known that STAT3 directly up-regulates the expression of TNFRSF1A, here we demonstrated that ETV7 reduces the ability of STAT3 to bind to the TNFRSF1A gene via a competitive mechanism, recruiting repressive chromatin remodelers, which results in the repression of its transcription. The inverse correlation between ETV7 and TNFRSF1A was confirmed also in different cohorts of BC patients. These results suggest that ETV7 can reduce the inflammatory responses in breast cancer through the down-regulation of TNFRSF1A.
The rate of orthokeratology lens use and associated factors in 33,280 children and adolescents with myopia: a cross-sectional study from Shanghai
Authors: Zhao Wenchen , Wang Jingjing , Chen Jun , Xie Hui , Yang Jinliuxing , Liu Kun , He Xiangui , Xu Xun 
Published: April 2023

Abstract
Objectives
To investigate the rate of orthokeratology lens (ortho-k lens) use and its associated factors in children and adolescents with myopia.

Methods
Cross-sectional study. Children from 104 primary and middle schools in Shanghai were enrolled by cluster sampling. Ophthalmic examinations were conducted and information was obtained using questionnaires for associated factors analysis.

Results
A total of 72,920 children and adolescents were included, among which 32,259 were the potential population for ortho-k lens use. A total of 1021 participants used ortho-k lenses, equating to a use rate of 1.4% in the total population and 3.1% in the potential population. Age (OR 0.91, 95% CI: 0.88–0.95, p < 0.001), BMI (≥95th percentile: OR 0.48, 95% CI: 0.35–0.66, p < 0.001), age at initiation of refractive correction (≤12 years: OR 1.75, 95% CI: 1.31–2.33, p < 0.001), and parental myopia (either: OR 2.09, 95% CI: 1.58–2.75, p < 0.001; both: OR 3.94, 95% CI: 3.04–5.11, p < 0.001) were independently associated with ortho-k lens use. Of the ortho-k lenses users, 12.4% had a logMAR CVA of ≥0.3. A correction target (SE) of ≤−3.0 D (OR 2.05, 95% CI: 1.38–3.05, p < 0.001) and a sleeping duration of ≤6 h (OR 4.19, 95% CI: 2.03–8.64, p < 0.001) were factors independently associated with CVA ≥ 0.3.

Conclusions
A certain proportion of children and adolescents in Shanghai chose to wear ortho-k lenses, related to the situation of parents and children themselves. Health education and follow-ups should be strengthened to ensure orthokeratology application quality.
Giant magnetoresistance of Dirac plasma in high-mobility graphene
Authors: Xin Na , Lourembam James , Kumaravadivel Piranavan , Kazantsev A. E. , Wu Zefei , Mullan Ciaran , Barrier Julien , Geim Alexandra A. , Grigorieva I. V. , Mishchenko A. , Principi A. , Fal’ko V. I. , Ponomarenko L. A. , Geim A. K. , Berdyugin Alexey I. 
Published: April 2023

AbstractThe most recognizable feature of graphene’s electronic spectrum is its Dirac point, around which interesting phenomena tend to cluster. At low temperatures, the intrinsic behaviour in this regime is often obscured by charge inhomogeneity1,2 but thermal excitations can overcome the disorder at elevated temperatures and create an electron–hole plasma of Dirac fermions. The Dirac plasma has been found to exhibit unusual properties, including quantum-critical scattering3–5 and hydrodynamic flow6–8. However, little is known about the plasma’s behaviour in magnetic fields. Here we report magnetotransport in this quantum-critical regime. In low fields, the plasma exhibits giant parabolic magnetoresistivity reaching more than 100 per cent in a magnetic field of 0.1 tesla at room temperature. This is orders-of-magnitude higher than magnetoresistivity found in any other system at such temperatures. We show that this behaviour is unique to monolayer graphene, being underpinned by its massless spectrum and ultrahigh mobility, despite frequent (Planckian limit) scattering3–5,9–14. With the onset of Landau quantization in a magnetic field of a few tesla, where the electron–hole plasma resides entirely on the zeroth Landau level, giant linear magnetoresistivity emerges. It is nearly independent of temperature and can be suppressed by proximity screening15, indicating a many-body origin. Clear parallels with magnetotransport in strange metals12–14 and so-called quantum linear magnetoresistance predicted for Weyl metals16 offer an interesting opportunity to further explore relevant physics using this well defined quantum-critical two-dimensional system.
Orbital-resolved observation of singlet fission
Authors: Neef Alexander , Beaulieu Samuel , Hammer Sebastian , Dong Shuo , Maklar Julian , Pincelli Tommaso , Xian R. Patrick , Wolf Martin , Rettig Laurenz , Pflaum Jens , Ernstorfer Ralph 
Published: April 2023

AbstractSinglet fission1–13 may boost photovoltaic efficiency14–16 by transforming a singlet exciton into two triplet excitons and thereby doubling the number of excited charge carriers. The primary step of singlet fission is the ultrafast creation of the correlated triplet pair17. Whereas several mechanisms have been proposed to explain this step, none has emerged as a consensus. The challenge lies in tracking the transient excitonic states. Here we use time- and angle-resolved photoemission spectroscopy to observe the primary step of singlet fission in crystalline pentacene. Our results indicate a charge-transfer mediated mechanism with a hybridization of Frenkel and charge-transfer states in the lowest bright singlet exciton. We gained intimate knowledge about the localization and the orbital character of the exciton wave functions recorded in momentum maps. This allowed us to directly compare the localization of singlet and bitriplet excitons and decompose energetically overlapping states on the basis of their orbital character. Orbital- and localization-resolved many-body dynamics promise deep insights into the mechanics governing molecular systems18–20 and topological materials21–23.
The little skate genome and the evolutionary emergence of wing-like fins
Authors: Marlétaz Ferdinand , de la Calle-Mustienes Elisa , Acemel Rafael D. , Paliou Christina , Naranjo Silvia , Martínez-García Pedro Manuel , Cases Ildefonso , Sleight Victoria A. , Hirschberger Christine , Marcet-Houben Marina , Navon Dina , Andrescavage Ali , Skvortsova Ksenia , Duckett Paul Edward , González-Rajal Álvaro , Bogdanovic Ozren , Gibcus Johan H. , Yang Liyan , Gallardo-Fuentes Lourdes , Sospedra Ismael , Lopez-Rios Javier , Darbellay Fabrice , Visel Axel , Dekker Job , Shubin Neil , Gabaldón Toni , Nakamura Tetsuya , Tena Juan J. , Lupiáñez Darío G. , Rokhsar Daniel S. , Gómez-Skarmeta José Luis 
Published: April 2023

AbstractSkates are cartilaginous fish whose body plan features enlarged wing-like pectoral fins, enabling them to thrive in benthic environments1,2. However, the molecular underpinnings of this unique trait remain unclear. Here we investigate the origin of this phenotypic innovation by developing the little skateLeucoraja erinaceaas a genomically enabled model. Analysis of a high-quality chromosome-scale genome sequence for the little skate shows that it preserves many ancestral jawed vertebrate features compared with other sequenced genomes, including numerous ancient microchromosomes. Combining genome comparisons with extensive regulatory datasets in developing fins—including gene expression, chromatin occupancy and three-dimensional conformation—we find skate-specific genomic rearrangements that alter the three-dimensional regulatory landscape of genes that are involved in the planar cell polarity pathway. Functional inhibition of planar cell polarity signalling resulted in a reduction in anterior fin size, confirming that this pathway is a major contributor to batoid fin morphology. We also identified a fin-specific enhancer that interacts with severalhoxagenes, consistent with the redeployment ofhoxgene expression in anterior pectoral fins, and confirmed its potential to activate transcription in the anterior fin using zebrafish reporter assays. Our findings underscore the central role of genome reorganization and regulatory variation in the evolution of phenotypes, shedding light on the molecular origin of an enigmatic trait.
A generalized reinforcement learning based deep neural network agent model for diverse cognitive constructs
Authors: Nair Sandeep Sathyanandan , Muddapu Vignayanandam Ravindernath , Vigneswaran C. , Balasubramani Pragathi P. , Ramanathan Dhakshin S. , Mishra Jyoti , Chakravarthy V. Srinivasa 
Published: April 2023

AbstractHuman cognition is characterized by a wide range of capabilities including goal-oriented selective attention, distractor suppression, decision making, response inhibition, and working memory. Much research has focused on studying these individual components of cognition in isolation, whereas in several translational applications for cognitive impairment, multiple cognitive functions are altered in a given individual. Hence it is important to study multiple cognitive abilities in the same subject or, in computational terms, model them using a single model. To this end, we propose a unified, reinforcement learning-based agent model comprising of systems for representation, memory, value computation and exploration. We successfully modeled the aforementioned cognitive tasks and show how individual performance can be mapped to model meta-parameters. This model has the potential to serve as a proxy for cognitively impaired conditions, and can be used as a clinical testbench on which therapeutic interventions can be simulated first before delivering to human subjects.
AI4SeaIce: selecting loss functions for automated SAR sea ice concentration charting
Authors: Kucik Andrzej , Stokholm Andreas 
Published: April 2023

AbstractFor maritime navigation in the Arctic, sea ice charts are an essential tool, which still to this day is drawn manually by professional ice analysts. The total Sea Ice Concentration (SIC) is the primary descriptor of the charts and indicates the fraction of ice in an ocean surface area. Naturally, automating the SIC chart creation is desired. However, the optimal representation of the corresponding machine-learning task is ambivalent and discussed in the community. In this study, we explore the representation with either regressional or classification objectives, each with two different (weighted) loss functions: Mean Square Error and Binary Cross-Entropy, and Categorical Cross-Entropy and the Earth Mover’s Distance, respectively. While all models achieve good results they differ as the regression-based models obtain the highest numerical similarity to the reference charts, whereas the classification-optimised models generate results more visually pleasing and consistent. Rescaling the loss functions with inverse class weights improves the performance for intermediate classes at the expense of open water and fully-covered sea ice areas.
Trends in management and outcomes of COVID patients admitted to a Swiss tertiary care hospital
Authors: Marti Christophe , Gaudet-Blavignac Christophe , Martin Jeremy , Lovis Christian , Stirnemann Jérôme , Grosgurin Olivier , Novotny Fiona , Iten Anne , Mendes Aline , Prendki Virginie , Serratrice Christine , Farhoumand Pauline Darbellay , Abidi Nour , Vetter Pauline , Carballo Sebastian , Reny Jean-Luc , Berner Amandine , Gayet-Ageron Angèle 
Published: April 2023

AbstractTwo successive COVID-19 flares occurred in Switzerland in spring and autumn 2020. During these periods, therapeutic strategies have been constantly adapted based on emerging evidence. We aimed to describe these adaptations and evaluate their association with patient outcomes in a cohort of COVID-19 patients admitted to the hospital. Consecutive patients admitted to the Geneva Hospitals during two successive COVID-19 flares were included. Characteristics of patients admitted during these two periods were compared as well as therapeutic management including medications, respiratory support strategies and admission to the ICU and intermediate care unit (IMCU). A mutivariable model was computed to compare outcomes across the two successive waves adjusted for demographic characteristics, co-morbidities and severity at baseline. The main outcome was in-hospital mortality. Secondary outcomes included ICU admission, Intermediate care (IMCU) admission, and length of hospital stay. A total of 2′983 patients were included. Of these, 165 patients (16.3%, n = 1014) died during the first wave and 314 (16.0%, n = 1969) during the second (p = 0.819). The proportion of patients admitted to the ICU was lower in second wave compared to first (7.4 vs. 13.9%, p < 0.001) but their mortality was increased (33.6% vs. 25.5%, p < 0.001). Conversely, a greater proportion of patients was admitted to the IMCU in second wave compared to first (26.6% vs. 22.3%, p = 0.011). A third of patients received lopinavir (30.7%) or hydroxychloroquine (33.1%) during the first wave and none during second wave, while corticosteroids were mainly prescribed during second wave (58.1% vs. 9.1%, p < 0.001). In the multivariable analysis, a 25% reduction of mortality was observed during the second wave (HR 0.75; 95% confidence interval 0.59 to 0.96). Among deceased patients, 82.3% (78.2% during first wave and 84.4% during second wave) died without beeing admitted to the ICU. The proportion of patients with therapeutic limitations regarding ICU admission increased during the second wave (48.6% vs. 38.7%, p < 0.001). Adaptation of therapeutic strategies including corticosteroids therapy and higher admission to the IMCU to receive non-invasive respiratory support was associated with a reduction of hospital mortality in multivariable analysis, ICU admission and LOS during the second wave of COVID-19 despite an increased number of admitted patients. More patients had medical decisions restraining ICU admission during the second wave which may reflect better patient selection or implicit triaging.
Using the future wheel methodology to assess the impact of open science in the transport sector
Authors: Nielsen Anja Fleten , Michelmann Jakob , Akac Attila , Palts Kristel , Zilles Anne , Anagnostopoulou Afroditi , Langeland Ove 
Published: April 2023

AbstractOpen Science enhances information sharing and makes scientific results of transport research more transparent and accessible at all levels and to everyone allowing integrity and reproducibility. However, what future impacts will Open Science have on the societal, environmental and economic development within the transport sector? Using the Future Wheel methodology, we conducted a workshop with transport experts from both industry and academia to answer this question. The main findings of this study point in the direction of previous studies in other fields, in terms of increased innovation, increased efficiency, economic savings, more equality, and increased participation of citizens. In addition, we found several potential transport specific impacts: lower emission, faster travel times, improved traffic safety, increased awareness for transport policies, artificial intelligence improving mobility services. Several potential negative outcomes of Open Science were also identified by the expert group: job loss, new types of risks, increased cost, increased conflicts, time delays, increased inequality and increased energy consumption. If we know the negative outcomes it is much easier to put in place strategies that are sustainable for a broader stakeholder group, which also increase the probability of taking advantage of all the positive impacts of Open Science.
Machine learning-based analytics of the impact of the Covid-19 pandemic on alcohol consumption habit changes among United States healthcare workers
Authors: Rezapour Mostafa , Niazi Muhammad Khalid Khan , Gurcan Metin Nafi 
Published: April 2023

AbstractThe COVID-19 pandemic is a global health concern that has spread around the globe. Machine Learning is promising in the fight against the COVID-19 pandemic. Machine learning and artificial intelligence have been employed by various healthcare providers, scientists, and clinicians in medical industries in the fight against COVID-19 disease. In this paper, we discuss the impact of the Covid-19 pandemic on alcohol consumption habit changes among healthcare workers in the United States during the first wave of the Covid-19 pandemic. We utilize multiple supervised and unsupervised machine learning methods and models such as decision trees, logistic regression, support vector machines, multilayer perceptron, XGBoost, CatBoost, LightGBM, AdaBoost, Chi-Squared Test, mutual information, KModes clustering and the synthetic minority oversampling technique on a mental health survey data obtained from the University of Michigan Inter-University Consortium for Political and Social Research to investigate the links between COVID-19-related deleterious effects and changes in alcohol consumption habits among healthcare workers. Through the interpretation of the supervised and unsupervised methods, we have concluded that healthcare workers whose children stayed home during the first wave in the US consumed more alcohol. We also found that the work schedule changes due to the Covid-19 pandemic led to a change in alcohol use habits. Changes in food consumption, age, gender, geographical characteristics, changes in sleep habits, the amount of news consumption, and screen time are also important predictors of an increase in alcohol use among healthcare workers in the United States.
Imaging the innermost gaseous layers of the Mira star R Car with GRAVITY-VLTI
Authors: Rosales-Guzmán A. , Sanchez-Bermudez J. , Paladini C. , Alberdi A. , Brandner W. , Cannon E. , González-Torá G. , Haubois X. , Henning Th. , Kervella P. , Montarges M. , Perrin G. , Schödel R. , Wittkowski M. 
Published: April 2023

Context.The mass-loss mechanisms in M-type asymptotic giant branch (AGB) stars are still not well understood; these include, in particular, the formation of dust-driven winds from the innermost gaseous layers around these stars. One way to understand the gas-dust interaction in these regions and its impact on the mass-loss mechanisms is through the analysis of high-resolution observations of the stellar surface and its closest environment.Aims.We aim to characterize the inner circumstellar environment (~3R*) of the M-type Mira star R Car in the near-infrared at different phases of a pulsation period.Methods.We used GRAVITY interferometric observations in the K band obtained during two different epochs over 2018. Those data were analyzed using parametric models and image reconstruction of both the pseudo-continuum and the CO band heads observed. The reported data are the highest angular resolution observations on the source in theKband.Results.We determined sizes of R Car’s stellar disk of 16.67 ± 0.05 mas (3.03 au) in January 2018 and 14.84 ± 0.06 mas (2.70 au) in February, 2018, respectively. From our physical model, we determined temperatures and size ranges for the innermost CO layer detected around R Car. The derived column density of the CO is in the ~9.18×1018–1×1019cm−2range, which is sufficient to permit dust nucleation and the formation of stable dust-driven winds. We find that magnesium composites, Mg2SiO4and MgSiO3, have temperatures and condensation distances consistent with the ones obtained for the CO layer model and pure-line reconstructed images, which are the dust types most likely to be responsible for wind formation. Our reconstructed images show evidence of asymmetrical and inhomogeneous structures, which might trace a complex and perhaps clumpy structure of the CO molecule distribution.Conclusions.Our work demonstrates that the conditions for dust nucleation and thus for initialising dust-driven winds in M-type AGB stars are met in R Car, and we identify magnesium composites as the most probable candidates. We find structural changes between two observing epochs (which are separated by ~10% of the full pulsation period of the star) and evidence of the effects of asymmetries and clumpiness. This observational evidence is crucial to constraining the role of convection and pulsation in M-type stars.
A low-metallicity massive contact binary undergoing slow Case A mass transfer: A detailed spectroscopic and orbital analysis of SSN 7 in NGC 346 in the SMC
Authors: Rickard M. J. , Pauli D. 
Published: April 2023

Context. Most massive stars are believed to be born in close binary systems where they can exchange mass, which impacts the evolution of both binary components. Their evolution is of great interest in the search for the progenitors of gravitational waves. However, there are unknowns in the physics of mass transfer as observational examples are rare, especially at low metallicity. Nearby low-metallicity environments are particularly interesting hunting grounds for interacting systems as they act as the closest proxy for the early universe where we can resolve individual stars.
Aims. Using multi-epoch spectroscopic data, we complete a consistent spectral and orbital analysis of the early-type massive binary SSN 7 hosting a ON3 If*+O5.5 V((f)) star. Using these detailed results, we constrain an evolutionary scenario that can help us to understand binary evolution in low metallicity.
Methods. We were able to derive reliable radial velocities of the two components from the multi-epoch data, which were used to constrain the orbital parameters. The spectroscopic data covers the UV, optical, and near-IR, allowing a consistent analysis with the stellar atmosphere code, PoWR. Given the stellar and orbital parameters, we interpreted the results using binary evolutionary models.
Results. The two stars in the system have comparable luminosities of log(L1/L⊙) = 5.75 and log(L2/L⊙) = 5.78 for the primary and secondary, respectively, but have different temperatures (T1 = 43.6 kK and T2 = 38.7 kK). The primary (32 M⊙) is less massive than the secondary (55 M⊙), suggesting mass exchange. The mass estimates are confirmed by the orbital analysis. The revisited orbital period is 3 d. Our evolutionary models also predict mass exchange. Currently, the system is a contact binary undergoing a slow Case A phase, making it the most massive Algol-like system yet discovered.
Conclusions. Following the initial mass function, massive stars are rare, and to find them in an Algol-like configuration is even more unlikely. To date, no comparable system to SSN 7 has been found, making it a unique object to study the efficiency of mass transfer in massive star binaries. This example increases our understanding of massive star binary evolution and the formation of gravitational wave progenitors.