bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional MRI of murine olfactory bulbs at 15.2T reveals characteristic activation patterns when stimulated by different odors
Authors: Chitrit Odélia , Bao Qingjia , Cai Aoling , Gabriela Chuartzman Silvia , Zilkha Noga , Haddad Rafi , Kimchi Tali , Frydman Lucio 
Published: August 2023

AbstractThanks to its increased sensitivity, single-shot ultrahigh field functional MRI (UHF fMRI) could lead to valuable insight about subtle brain functions such as olfaction. However, UHF fMRI experiments targeting small organs next to air voids, such as the olfactory bulb, are severely affected by field inhomogeneity problems. Spatiotemporal Encoding (SPEN) is an emerging single-shot MRI technique that could provide a route for bypassing these complications. This is here explored with single-shot fMRI studies on the olfactory bulbs of male and female mice performed at 15.2T. SPEN images collected on these organs at a 108 µm in-plane resolution yielded remarkably large and well-defined responses to olfactory cues. Under suitable T2* weightings these activation-driven changes exceeded 5% of the overall signal intensity, becoming clearly visible in the images without statistical treatment. The nature of the SPEN signal intensity changes in such experiments was unambiguously linked to olfaction, via single-nostril experiments. These experiments highlighted specific activation regions in the external plexiform region and in glomeruli in the lateral part of the bulb, when stimulated by aversive or appetitive odors, respectively. These strong signal activations were non-linear with concentration, and shed light on how chemosensory signals reaching the olfactory epithelium react in response to different cues. Second-level analyses highlighted clear differences among the appetitive, aversive and neutral odor maps; no such differences were evident upon comparing male against female olfactory activation regions.
Variational quantum and quantum-inspired clustering
Authors: Bermejo Pablo , Orús Román 
Published: August 2023

AbstractHere we present a quantum algorithm for clustering data based on a variational quantum circuit. The algorithm allows to classify data into many clusters, and can easily be implemented in few-qubit Noisy Intermediate-Scale Quantum devices. The idea of the algorithm relies on reducing the clustering problem to an optimization, and then solving it via a Variational Quantum Eigensolver combined with non-orthogonal qubit states. In practice, the method uses maximally-orthogonal states of the target Hilbert space instead of the usual computational basis, allowing for a large number of clusters to be considered even with few qubits. We benchmark the algorithm with numerical simulations using real datasets, showing excellent performance even with one single qubit. Moreover, a tensor network simulation of the algorithm implements, by construction, a quantum-inspired clustering algorithm that can run on current classical hardware.
Particle fusion of super-resolution data reveals the unit structure of Nup96 in Nuclear Pore Complex
Authors: Wang Wenxiu , Jakobi Arjen , Wu Yu-Le , Ries Jonas , Stallinga Sjoerd , Rieger Bernd 
Published: August 2023

AbstractSingle molecule localization microscopy offers resolution nearly down to the molecular level with specific molecular labelling, and is thereby a promising tool for structural biology. In practice, however, the actual value to this field is limited primarily by incomplete fluorescent labelling of the structure. This missing information can be completed by merging information from many structurally identical particles in a particle fusion approach similar to cryo-EM single-particle analysis. In this paper, we present a data analysis of particle fusion results of fluorescently labelled Nup96 nucleoporins in the Nuclear Pore Complex to show that Nup96 occurs in a spatial arrangement of two rings of 8 units with two Nup96 copies per unit giving a total of 32 Nup96 copies per pore. We use Artificial Intelligence assisted modeling in Alphafold to extend the existing cryo-EM model of Nup96 to accurately pinpoint the positions of the fluorescent labels and show the accuracy of the match between fluorescent and cryo-EM data to be better than 3 nm in-plane and 5 nm out-of-plane.
The effect of ketamine on affective modulation of the startle reflex and its resting-state brain correlates
Authors: Sen Zümrüt Duygu , Chand Tara , Danyeli Lena Vera , Kumar Vinod Jangir , Colic Lejla , Li Meng , Yemisken Merve , Javaheripour Nooshin , Refisch Alexander , Opel Nils , Macharadze Tamar , Kretzschmar Moritz , Ozkan Esra , Deliano Matthias , Walter Martin 
Published: August 2023

AbstractKetamine is a rapid-acting antidepressant that also influences neural reactivity to affective stimuli. However, the effect of ketamine on behavioral affective reactivity is yet to be elucidated. The affect-modulated startle reflex paradigm (AMSR) allows examining the valence-specific aspects of behavioral affective reactivity. We hypothesized that ketamine alters the modulation of the startle reflex during processing of unpleasant and pleasant stimuli and weakens the resting-state functional connectivity (rsFC) within the modulatory pathway, namely between the centromedial nucleus of the amygdala and nucleus reticularis pontis caudalis. In a randomized, double-blind, placebo-controlled, cross-over study, thirty-two healthy male participants underwent ultra-high field resting-state functional magnetic resonance imaging at 7 T before and 24 h after placebo and S-ketamine infusions. Participants completed the AMSR task at baseline and one day after each infusion. In contrast to our hypothesis, ketamine infusion did not impact startle potentiation during processing of unpleasant stimuli but resulted in diminished startle attenuation during processing of pleasant stimuli. This diminishment significantly correlated with end-of-infusion plasma levels of ketamine and norketamine. Furthermore, ketamine induced a decrease in rsFC within the modulatory startle reflex pathway. The results of this first study on the effect of ketamine on the AMSR suggest that ketamine might attenuate the motivational significance of pleasant stimuli in healthy participants one day after infusion.
Educational attainment and anxiety in middle-aged and older Europeans
Authors: Chlapecka Adam , Wolfová Katrin , Fryčová Barbora , Cermakova Pavla 
Published: August 2023

AbstractWe examined the relationship between educational attainment (EA) and anxiety symptoms in a sample of 77,792 individuals (median age = 64 years, 55% female) from the Survey of Health, Ageing and Retirement in Europe. Using logistic regression, we estimated odds ratio (OR) with 95% confidence interval (CI) for the association between EA (7 educational levels based on International Standard Classification of Education) and anxiety symptoms (12 or more points from the shortened 5-item version of the Beck Anxiety Inventory), adjusting for sociodemographic and health-related factors. We further explored whether the relationship varied by region, sex and age group. Independent of sociodemographic and health-related factors, higher levels of EA were associated with lower odds of anxiety symptoms. The magnitude of this association plateaued at first stage of tertiary education (OR 0.40; 95% CI 0.35–0.47, p < 0.001). The association was stronger in females, middle-aged individuals and in Central and Eastern Europe while not apparent in Northern Europe. Our findings suggest that individuals with higher education might be protected against anxiety throughout life. The protective effect of education against anxiety symptoms is more pronounced in less egalitarian regions and in females.
Development of eco-friendly antifungal and antibacterial adhesive derived from modified cassava starch waste/polyvinyl alcohol containing green synthesized nano-silver
Authors: Jarensungnen Chaloton , Jetsrisuparb Kaewta , Phanthanawiboon Supranee , Theerakulpisut Somnuk , Hiziroglu Salim , Knijnenburg Jesper Theodorus Nicolaas , Okhawilai Manunya , Kasemsiri Pornnapa 
Published: August 2023

AbstractEnvironmentally friendly biopolymer-based wood adhesives are an inevitable trend of wood product development to replace the use of harmful formaldehyde-based adhesives. In this research, a new eco-friendly modified cassava starch waste-based adhesive via carboxymethylation (CMS), and blending with polyvinyl alcohol (PVA), tannic acid (TA) and green synthesized silver nanoparticles (AgNPs) was prepared. The effects of TA content on green synthesis of AgNPs (Ag-TA) and bio-adhesive nanocomposite properties were investigated. The use of 5 wt% TA for AgNPs synthesis (Ag-TA-5) resulted in a uniform particle size distribution. The plywood prepared with Ag-TA-5 provided the highest dry and wet shear strength at 1.95 ± 0.11 MPa and 1.38 ± 0.3 MPa, respectively. The water absorption and thickness swelling of this plywood remarkably decreased up to 10.99% and 6.79%, respectively. More importantly, the presence of Ag-TA in CMS/PVA adhesive successfully inhibited the invasion of mold and bacteria. Based on the cyclic delamination test, the adhesive bond durability of bio-adhesive containing Ag-TA-5 could meet the requirement of the AITC Test T110-2007 and was comparable to commercial adhesives. The added advantage of the prepared bio-adhesive was its synthesis from agro-waste products and possible economically viable production at industrial level.
A novel disulfidptosis and glycolysis related risk score signature for prediction of prognosis and ICI therapeutic responsiveness in colorectal cancer
Authors: Li Jiazheng , Yang Chao , Zheng Yongbin 
Published: August 2023

AbstractDisulfidptosis is a newly-identified non-programmed cell death mode with tight associations with glucose metabolism. Elevated glycolysis is an important metabolic feature of tumor cells, which fulfills the energy requirement for their rapid growth and progression. Our present study determined to develop a disulfidptosis and glycolysis related gene (DGRG) risk score signature to predict the prognosis and ICI therapeutic responsiveness for CRC patients. First, the gene expression and clinical profiles for CRC patients were obtained from TCGA and GEO database. Using weighted gene co-expression network analysis, we identified hub genes showing the strongest correlations with both disulfidptosis and glycolysis activities. Next, a DGRG risk score signature was successfully developed through univariate and least absolute shrinkage and selection operator method Cox regression method. A DGRG risk score-based nomogram could further enhance the predictive performance. In addition, an array of systemic analysis was performed to unravel the correlation of DGRG risk score with tumor microenvironment. The results showed that CRC patients with low DGRG risk level had up-regulated immune cell infiltrations, enhanced metabolic activities and heightened gene mutation frequencies, while high risk patients was the opposite. Moreover, our present study identified low risk CRC patients as potential beneficiaries from immune checkpoint inhibitor (ICI) therapies. Our present work highlighted the potential utility of DGRG risk score signature in prognosis prediction and ICI responsiveness determination for CRC patients, which demonstrated promising clinical application value.
Tetraspanins predict the prognosis and characterize the tumor immune microenvironment of glioblastoma
Authors: Li Yu-Chao , Wu Yue , Chen Gang , Zhu Li-Zhi , Luo Xiu , Nie Qian-Qian , Zhang Lu , Zuo Chang-Jing 
Published: August 2023

AbstractGlioblastoma (GBM) is the most aggressive and lethal primary brain tumor. Conventional treatments have not achieved breakthroughs in improving survival. Therefore, novel molecular targets and biomarkers need to be identified. As signal transduction docks on the cell membrane, tetraspanins (TSPANs) are associated with various tumors; however, research on their role in GBM remains extremely scarce. Gene expression and clinicopathological characteristic data were obtained from GEPIA, CGGA, HPA, cBioPortal, and GSCA databases to analyze the mRNA and protein expression levels, prognostic value, clinical relevance, mutation status, and targeted drug sensitivity of TSPANs in GBM. Gene set enrichment analysis (GSEA), Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used for biological process enrichment. Data from TCGA and TCIA were used to construct the tumor immune microenvironment landscape of TSPANs. Different R software algorithms were used to analyze the immune score, immune cell infiltration, and immune checkpoint correlation. Univariate and multivariate analyses were performed for TSPAN4, which had the most significant predictive prognostic value, and a nomogram model was constructed to predict individual outcomes. The expression and function of TSPAN4 were verified in vitro. TSPAN3/4/6/11/12/18/23/24/25/26/27/28/29/30/31expressions were significantly upregulated in GBM, and TSPAN3/4/6/11/18/24/25/26/29/30 were strongly correlated with prognosis. The expression of multiple TSPANs significantly correlated with 1p/19q co-deletion status, IDH mutation status, recurrence, age, and tumor grade. GSEA and GO analyses revealed the potential contribution of TSPANs in cell adhesion and migration. Immune correlation analysis revealed that TSPANs are related to the formation of the GBM tumor microenvironment (TME) and may influence immunotherapy outcomes. TSPAN4 is an independent prognostic factor and TSPAN4 knockdown has been demonstrated to strongly inhibit glioma cell proliferation, invasion, and migration in vitro. We comprehensively elaborated the prognostic value and potential role of differentially expressed TSPANs in GBM, including molecules that scientists have previously overlooked. This study provides a novel and comprehensive perspective on the pathological mechanisms of GBM and the future direction of individualized tumor immunotherapy, which may be a critical link between GBM malignant progression and TME remodeling.
Tidal transports from satellite observations of earth’s magnetic field
Authors: Saynisch-Wagner Jan , Baerenzung Julien , Hornschild Aaron , Thomas Maik 
Published: August 2023

AbstractThe tides are a major driver of global oceanic mixing. While global tidal elevations are very well observed by satellite altimetry, the global tidal transports are much less well known. For twenty years, magnetic signals induced by the ocean tides have been detectable in satellite magnetometer observations, such as Swarm or CHAMP. Here, we demonstrate how satellite magnetometer observations can be used to directly derive global ocean tidal transports. As an advantage over other tidal transport estimates, our tidal estimates base on very few and very loose constraints from numerical forward models.
Improving speech perception for hearing-impaired listeners using audio-to-tactile sensory substitution with multiple frequency channels
Authors: Fletcher Mark D. , Verschuur Carl A. , Perry Samuel W. 
Published: August 2023

AbstractCochlear implants (CIs) have revolutionised treatment of hearing loss, but large populations globally cannot access them either because of disorders that prevent implantation or because they are expensive and require specialist surgery. Recent technology developments mean that haptic aids, which transmit speech through vibration, could offer a viable low-cost, non-invasive alternative. One important development is that compact haptic actuators can now deliver intense stimulation across multiple frequencies. We explored whether these multiple frequency channels can transfer spectral information to improve tactile phoneme discrimination. To convert audio to vibration, the speech amplitude envelope was extracted from one or more audio frequency bands and used to amplitude modulate one or more vibro-tactile tones delivered to a single-site on the wrist. In 26 participants with normal touch sensitivity, tactile-only phoneme discrimination was assessed with one, four, or eight frequency bands. Compared to one frequency band, performance improved by 5.9% with four frequency bands and by 8.4% with eight frequency bands. The multi-band signal-processing approach can be implemented in real-time on a compact device, and the vibro-tactile tones can be reproduced by the latest compact, low-powered actuators. This approach could therefore readily be implemented in a low-cost haptic hearing aid to deliver real-world benefits.
Exceptional multi-year prediction skill of the Kuroshio Extension in the CESM high-resolution decadal prediction system
Authors: Kim Who M. , Yeager Stephen G. , Danabasoglu Gokhan , Chang Ping 
Published: August 2023

AbstractThe Kuroshio Extension (KE) has far-reaching influences on climate as well as on local marine ecosystems. Thus, skillful multi-year to decadal prediction of the KE state and understanding sources of skill are valuable. Retrospective forecasts using the high-resolution Community Earth System Model (CESM) show exceptional skill in predicting KE variability up to lead year 4, substantially higher than the skill found in a similarly configured low-resolution CESM. The higher skill is attained because the high-resolution system can more realistically simulate the westward Rossby wave propagation of initialized ocean anomalies in the central North Pacific and their expression within the sharp KE front, and does not suffer from spurious variability near Japan present in the low-resolution CESM that interferes with the incoming wave propagation. These results argue for the use of high-resolution models for future studies that aim to predict changes in western boundary current systems and associated biological fields.
Diastereoisomeric enrichment of 1,4-enediols and H2-splitting inhibition on Pd-supported catalysts
Authors: Ballesteros-Soberanas Jordi , Mon Marta , Leyva-Pérez Antonio 
Published: August 2023

The semi-hydrogenation reaction of gemini alkynes proceeds with palladium-supported catalysts in a diastereoisomerically-enriched way to give mainly meso 1,4-enediols, which inhibit the dissociation of H2 on the palladium catalyst.
Microstrip antenna modelling based on image‐based convolutional neural network
Authors: Fu Hao , Tian Yubo , Meng Fei , Li Qing , Ren Xuefeng 
Published: August 2023

AbstractConvolutional neural networks (CNN) have a strong feature extraction ability for images and present a high level of efficiency and accuracy in object detection and image recognition. When CNN is used to model microwave devices, the existing literature generally uses its size parameters as one‐dimensional (1‐D) input, which does not give full play to the image‐processing ability of CNN. In order to make full use of the characteristics of CNN, this letter converts the 1‐D input of microwave devices into the form of an image model, that is, the 1‐D input is transformed into a two‐dimensional (2‐D) matrix composed of 0 and 1 as the input. The image model is combined with CNN, called image‐based CNN (ICNN), which establishes a deep learning surrogate model between the physical parameters and electrical properties of microwave devices and improves the accuracy and generalization ability of the model. Taking the resonant frequency of the microstrip antenna as a simulation example, modelling was carried out by the proposed ICNN and compared with the mainstream machine learning methods. The results show that the proposed method has high convergence and fitting accuracy.
A double T‐type H‐bridge reduced switch multilevel inverter for a wide range of DC voltage variations
Authors: Zolfagharian Omid , Mirzaei Mehrdad , Dastfan Ali 
Published: August 2023

AbstractRenewable energy sources are subject to input source uncertainties, which can negatively impact output voltage THD. Having a high number of voltage levels in multilevel inverters (MLIs) with minimum components is cost‐effective. This paper proposes a new structure, Double T‐type H‐bridge (DTH) module, that can produce 9, 13, 17, 19, 21, and 25 levels using reduced components. Switching patterns in MLIs refer to the way in which the power switches are controlled to generate the desired output voltage waveform. As a result, having more switching patterns make the converter flexible to produce voltage levels in the face of input source uncertainties. The DTH structure provides new switching patterns, making it possible to produce levels when the difference of capacitor voltage is negative in a positive cycle or vice versa. This paper presents a new algorithm based on nearest level control to order voltage levels in ascending order, which improves output THD significantly. This topology brings a lower switching state that is linked to switching losses directly compared to the topologies with the same number of power switches. The DTH module's performance is evaluated through graphical analysis, simulations, and experimental results in symmetrical, asymmetrical, and load change conditions.
Benchmarking Gaia DR3 Apsis with the Hyades and Pleiades open clusters
Authors: Brandner Wolfgang , Calissendorff Per , Kopytova Taisiya 
Published: August 2023

Context. The Gaia astrophysical parameters inference system (Apsis) provides astrophysical parameter estimates for several to hundreds of millions of stars.
Aims. We aim to benchmark Gaia DR3 Apsis.
Methods. We compiled approximately 1500 bona fide single stars in the Hyades and Pleiades open clusters for validation of PARSEC isochrones, and for comparison with Apsis estimates. PARSEC stellar isochrones in the Gaia photometric system enable us to assign average ages and metallicities to the clusters, and mass, effective temperature, luminosity, and surface gravity to the individual stars.
Results. Apsis does not recover the single-age, single-metallicity characteristic of the cluster populations. Ages assigned to cluster members seemingly follow the input template for Galactic populations, with earlier-type stars being systematically assigned younger ages than later-type stars. Cluster metallicities are underestimated by 0.10–0.2 dex. Effective temperature estimates are in general reliable. Surface gravity estimates reveal strong systematic errors for specific ranges of the Gaia BP − RP colours.
Conclusions. We caution that Gaia DR3 Apsis estimates can be subject to significant systematic uncertainties. Some of the Apsis estimates, such as metallicity, might only be meaningful for statistical studies of the time-averaged Galactic stellar population, but are not recommended to be used for individual stars.