bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perception of pointing gestures in 3D space
Authors: Krause Lisa-Marie , Herbort Oliver 
Published: November 2024

AbstractPointing gestures are often used to refer to distant referents by indicating in which vertical and horizontal direction the referent is located relative to the pointer. In the present manuscript, we address whether and how both dimensions interact when people spatially interpret pointing gestures, or whether both dimensions are processed independently as reflected in many current models. We found that both dimensions interact on different levels. First, cross-dimensional effects were found on a between-gestures level. That is, the perception of the vertical position implied by a pointing gesture depended on horizontal arm and finger orientation. Conversely, the horizontal interpretation depended on vertical arm and finger orientation. Second, we found cross-dimensional interactions on the level of intra-individual biases. That is, participants’ horizontal perceptual biases in interpretations (e.g., perceiving a gesture as directed more rightward than others) were related to their vertical perceptual biases. Third, we found cross-dimensional interactions on the level of intra-individual variability. That is, the vertical and horizontal interpretations of the same pointing gestures were correlated within participants and gestures. Together, these findings indicate that human spatial pointing perception is based on configural processing of a gesture on different levels of information processing.
Local and systemic humoral immune responses to Histophilus somni recombinant antigens administered intranasally and subcutaneously to dairy calves
Authors: Bazjert Joanna , Jawor Paulina , Pisarek Maciej , Baran Rafał , Jachymek Wojciech , Stefaniak Tadeusz 
Published: November 2024

AbstractBovine respiratory disease (BRD) causes significant economic losses in dairy calves. Induction of an early immune response via parenteral vaccination is complicated by the interference of colostral immunity. In this study, we investigated early immunization against selected conserved bacterial antigens. Calves were vaccinated twice intranasally and then subcutaneously with Histophilus somni recombinant proteins (rOMP40 or rHsp60) mixed with one of two adjuvants: CpG ODN2007 or MPLA. The control group (Con) was treated with PBS. The first immunization was done between 24 and 48 h of life and then twice in two weeks intervals. Blood, nasal, and saliva secretion samples were collected directly before vaccination (S1–S3) and then on 42–44 (S4) and 59–61 (S5) day of life. Antibodies (IgG1/IgG2/IgM/IgA in serum; IgG1/IgA in secretions) against both vaccine antigens were quantified in all samples. Intranasal and subcutaneous vaccinations using the described formulas did not increase antibody reactivity against the tested proteins. The reactivity of serum IgG1, IgM, and IgA anti-rOMP40 antibodies was significantly higher in S1 in all groups than that in the other samplings (p˂0.01). Significant differences in the reactivity of serum anti-rOMP40 antibodies between groups were identified in S1 (IgA reactivity was higher in the CpG vs. MPLA group; p < 0.05), S4 (IgM reactivity was higher in Con vs. CpG group; p < 0.05), and S5 (IgG1 reactivity was higher in MPLA vs. Con group; p < 0.05). The lack of consistent changes in antibodies after immunization (S4 and S5) hinders the drawing of conclusions regarding the effect of immunization on antibody reactivity. In the future, establishing a proper immunization window and adjuvants for nasal vaccines against bacterial pathogens causing BRD in calves remains to be determined.
Coherent Raman microscopy visualizes ongoing cellular senescence through amide I peak shifts originating from β sheets in disordered nucleolar proteins
Authors: Ishibashi Shigeo , Inoko Akihito , Oka Yuki , Leproux Philippe , Kano Hideaki 
Published: November 2024

AbstractCellular senescence occurs through the accumulation of many kinds of stresses. Senescent cells in tissues also cause various age-related disorders. Therefore, detecting them without labeling is beneficial for medical research and developing diagnostic methods. However, existing biomarkers have limitations of requiring fixation and labeling, or their molecular backgrounds are uncertain. Coherent anti-Stokes Raman scattering (CARS) spectroscopic imaging is a novel option because it can assess and visualize molecular structures based on their molecular fingerprint. Here, we present a new label-free method to visualize cellular senescence using CARS imaging in nucleoli. We found the peak of the nucleolar amide I band shifted to a higher wavenumber in binuclear senescent cells, which reflects changes in the protein secondary structure from predominant α-helices to β-sheets originating from amyloid-like aggregates. Following this, we developed a procedure that can visualize the senescent cells by providing the ratios and subtractions of these two components. We also confirmed that the procedure can visualize nucleolar aggregates due to unfolded/misfolded proteins produced by proteasome inhibition. Finally, we found that this method can help visualize the nucleolar defects in naïve cells even before binucleation. Thus, our method is beneficial to evaluate ongoing cellular senescence through label-free imaging of nucleolar defects.
A novel benign and malignant classification model for lung nodules based on multi-scale interleaved fusion integrated network
Authors: Lv Enhui , Kang Xingxing , Wen Pengbo , Tian Jiaqi , Zhang Mengying 
Published: November 2024

AbstractOne of the precursors of lung cancer is the presence of lung nodules, and accurate identification of their benign or malignant nature is important for the long-term survival of patients. With the development of artificial intelligence, deep learning has become the main method for lung nodule classification. However, successful deep learning models usually require large number of parameters and carefully annotated data. In the field of medical images, the availability of such data is usually limited, which makes deep networks often perform poorly on new test data. In addition, the model based on the linear stacked single branch structure hinders the extraction of multi-scale features and reduces the classification performance. In this paper, to address this problem, we propose a lightweight interleaved fusion integration network with multi-scale feature learning modules, called MIFNet. The MIFNet consists of a series of MIF blocks that efficiently combine multiple convolutional layers containing 1 × 1 and 3 × 3 convolutional kernels with shortcut links to extract multiscale features at different levels and preserving them throughout the block. The model has only 0.7 M parameters and requires low computational cost and memory space compared to many ImageNet pretrained CNN architectures. The proposed MIFNet conducted exhaustive experiments on the reconstructed LUNA16 dataset, achieving impressive results with 94.82% accuracy, 97.34% F1 value, 96.74% precision, 97.10% sensitivity, and 84.75% specificity. The results show that our proposed deep integrated network achieves higher performance than pre-trained deep networks and state-of-the-art methods. This provides an objective and efficient auxiliary method for accurately classifying the type of lung nodule in medical images.
Design and psychometrics of a tool for measuring social cognitive factors related to the preventive behaviors toward Covid-19 in the society
Authors: Dadashi-Tonkaboni Niloofar , Bagheri Marjan , Gholamnia-Shirvani Zeinab , Mirzaei Hamed , Mahdizadeh Mehrsadat 
Published: November 2024

AbstractWith the emergence of new strains of Covid-19, the adoption of preventive behaviors is still considered a requirement to control this disease. Therefore, considering the importance of social cognitive factors in adopting various types of preventive behaviors, the present study was conducted to design and psychometrically measure the social cognitive factors related to Covid-19 preventive behaviors. A cross-sectional study was conducted on 526 people ages 18 and over with multi-stage stratified, cluster and random sampling in Isfahan, Iran in 2022. The questionnaire was validated and formulated in three stages: designing, creating and reducing items. After collecting information and creating a bank of items, qualitative and quantitative methods were used to calculate the tool’s validity. Data analysis was done in SPSS23 software at a significance level of less than 0.05. In the present study, the average age score of the participants was 39.16 ± 11.48. The results related to the construct validity in the exploratory part show that the five factors (Outcome expectations, self-efficacy, social support, self-regulation and barrier self-efficacy) obtained have a specific value higher than one and range from 1.376 to 9.343. Correlation between factors shows that all factors have a relatively high relationship with each other (P < 0.05). According to the exploratory factor analysis, the final questionnaire contains 29 items and 5 constructs from socio-cognitive theory. The results showed that the thematically and technically designed tool has been prepared in an appropriate way for each of the structures and can accurately measure the structures of outcome expectations, self-efficacy, social support, self-regulation and barrier self-efficacy to explain the preventive behaviors of Covid-19 to evaluate.
Multicellular adaptation to electrophysiological perturbations analyzed by deterministic and stochastic bioelectrical models
Authors: Cervera Javier , Levin Michael , Mafe Salvador 
Published: November 2024

AbstractCells can compensate a disruptive change in one ion channel by compensatory changes in other channels. We have simulated the adaptation of a multicellular aggregate of non-excitable cells to the electrophysiological perturbation produced by the external blocking of a cation channel. In the biophysical model employed, we consider that this blocking provokes a cell depolarization that opens a voltage-gated calcium channel, thus allowing toxic Ca2+ levels. The cell adaptation to this externally-induced perturbation is ascribed to the multiplicity of channels available to keep the cell membrane potential within a physiological window. We propose that the cell depolarization provokes the upregulated expression of a compensatory channel protein that resets the cell potential to the correct polarized value, which prevents the calcium entry. To this end, we use two different simulation algorithms based on deterministic and stochastic methods. The simulations suggest that because of the local correlations coupling the cell potential to transcription, short-term bioelectrical perturbations can trigger long-term biochemical adaptations to novel stressors in multicellular aggregates. Previous experimental data on planarian flatworms’ adaptation to a barium-containing environment is also discussed.
A comprehensive scheme for power management of FC/SC/battery, and solar-roof PV source in electric vehicle systems
Authors: Valizadeh Majid , Shiri Mahyar , Sarvenoee Amirhosein Khosravi , Gowtham N. , AboRas Kareem M. 
Published: November 2024

AbstractThis paper proposes a new energy management system to combine Fuel Cells (FC) and photovoltaic (PV) panels as primary power sources. Also, battery and Super Capacitor (SC) banks are considered as secondary energy systems. The high power density and the fast dynamics of SCs combined with the high energy density and medium dynamics of batteries would be an ideal combination for FC vehicles. The high step-up DC/DC converter is used along with the implementation of the maximum power point tracking algorithm (MPPT) to adapt the low power of PV panels with the high power of DC-Link. Also, an evolutionary optimization algorithm is proposed along with the FOPI controller to improve the output of the energy management algorithm and control the sources more efficiently. The simulation results are validated for a standard urban driving cycle. It indicates for the case of the sustained presence of a PV source during a typical driving cycle, the source delivers about 55% of its maximum power.
Benchmark of screening markers for KEAP1/NFE2L2 mutations and joint analysis with the K1N2-score
Authors: Arolt Christoph , Scheel Andreas H. , Dugan Margaret , Wild Robert , Richartz Vanessa , Holz Barbara , Brägelmann Johannes , Wagener-Ryczek Svenja , Merkelbach-Bruse Sabine , Wolf Juergen , Buettner Reinhard , Catanzariti Luigi , Scheffler Matthias , Hillmer Axel M. 
Published: November 2024

AbstractOur recently published K1N2-score robustly predicts KEAP1/NFE2L2-mutations and pathway activation status, while its accessibility might be limited. We tested if the RNA expression data of six pathway-related genes and NQO1-IHC might be a reliable alternative using 348 KEAP1/NFE2L2 mutation-enriched NSCLC. While TXNRD1 RNA testing was the best-performing single-gene test, the combination of single-gene screening and validation with the K1N2-score achieved the highest performance when predicting mutation status or pathway activation.
The pro-oncogenic noncanonical activity of a RAS•GTP:RanGAP1 complex facilitates nuclear protein export
Authors: Tripathi Brajendra K. , Hirsh Nicole H. , Qian Xiaolan , Durkin Marian E. , Wang Dunrui , Papageorge Alex G. , Lake Ross , Evrard Yvonne A. , Marcus Adam I. , Ramalingam Suresh S. , Dasso Mary , Vousden Karen H. , Doroshow James H. , Walters Kylie J. , Lowy Douglas R. 
Published: November 2024

AbstractCanonical RAS signaling, including PI3K/AKT- and RAF/MEK-dependent activities, results mainly from RAS•GTP interaction with its effectors at the plasma membrane. Here, we identified a fundamental, oncogenic, noncanonical RAS•GTP activity that increases XPO1-dependent export of nuclear protein cargo into the cytoplasm and is independent of PI3K/AKT and RAF/MEK signaling. This RAS-dependent step acts downstream from XPO1 binding to nuclear protein cargo and is mediated by a perinuclear protein complex between RAS•GTP and RanGAP1 that facilitates hydrolysis of Ran•GTP to Ran•GDP, which promotes release of nuclear protein cargo into the cytoplasm. The export of nuclear EZH2, which promotes cytoplasmic degradation of the DLC1 tumor suppressor protein, is a biologically important component of this pro-oncogenic activity. Conversely, preventing nuclear protein export contributes to the antitumor activity of KRAS inhibition, which can be further augmented by reactivating the tumor suppressor activity of DLC1 or potentially combining RAS inhibitors with other cancer treatments.
Rural land systems both support and hinder the Sustainable Development Goals across Europe
Authors: Nicholas Kimberly A. , Scown Murray 
Published: November 2024

AbstractAchieving sustainable rural land systems, including farms and forestry, is essential to achieve the European Union’s goal of fair and healthy food systems while becoming climate-neutral and halting biodiversity loss. Here we quantitatively assess the environmental and socioeconomic sustainability of rural land systems in Europe using spatial hotspot analyses based on 15 environmental and 9 social sustainability indicators from the European Sustainable Development Goals and the Common Agricultural Policy. We find high subsidy support for under-performing sustainability areas and low sustainability performance in areas producing the most calories. However, we identified two brightspots with good environmental and socioeconomic performance (Nordics and Central Europe), and five dragspots hindering sustainability: the Balkans, the Lowlands, Northern Italy, Southern Italy and Malta, and Southern Spain. Redirecting support to reward social and environmental benefits from land use can help achieve sustainability goals.
Annual grass invasions and wildfire deplete ecosystem carbon storage by >50% to resistant base levels
Authors: Maxwell Toby M. , Quicke Harold E. , Price Samuel J. , Germino Matthew J. 
Published: November 2024

AbstractEcological disturbance can affect carbon storage and stability and is a key consideration for managing lands to preserve or increase ecosystem carbon to ameliorate the global greenhouse gas problem. Dryland soils are massive carbon reservoirs that are increasingly impacted by species invasions and altered fire regimes, including the exotic-grass-fire cycle in the extensive sagebrush steppe of North America. Direct measurement of total carbon in 1174 samples from landscapes of this region that differed in invasion and wildfire history revealed that their impacts depleted soil carbon by 42–49%, primarily in deep horizons, which could amount to 17.1–20.0 Tg carbon lost across the ~400,000 ha affected annually. Disturbance effects on soil carbon stocks were not synergistic, suggesting that soil carbon was lowered to a floor—i.e. a resistant base-level—beneath which further loss was unlikely. Restoration and maintenance of resilient dryland shrublands/rangelands could stabilize soil carbon at magnitudes relevant to the global carbon cycle.
Reef site and habitat influence effectiveness of Acropora palmata restoration and its microbiome in the Florida Keys
Authors: Rosales Stephanie M. , Young Benjamin D. , Bright Allan J. , Montes Enrique , Zhang Jia-Zhong , Traylor-Knowles Nikki , Williams Dana E. 
Published: November 2024

AbstractThe success of coral restoration for the critically endangered Acropora palmata is understudied. Here, we examined how habitat and coral microbiomes influenced survivorship in four genets of A. palmata outplanted in three reefs. A. palmata microbiomes were correlated to reef and habitat and minimally to coral genet. Carysfort Reef exhibited the lowest survivorship which correlated to lower current velocity and a higher relative abundance of Rhodobacterales in A. palmata. Higher survivorship was present at Pickles Reef which correlated to the highest current velocity, and at North Dry Rocks with the shallowest outplant depth. Habitat factors driven by time of year such as higher levels of nitrate, nitrite, and temperature also correlated with a relative increase in a putative pathogen, Alteromonadales, and a decrease in an uncharacterized core bacteria. We suggest outplanting at sites with high currents, lower depths, and at lower concentrations of nitrate/nitrite to increase A. palmata survivorship.
Enhanced vasoconstriction in sickle cell disease is dependent on ETA receptor activation
Authors: Allan John Miller , Fox Brandon M. , Kasztan Malgorzata , Kelly Gillian C. , Molina Patrick A. , King McKenzi A. , Colson Jackson , Wells Leigh , Bowman Latanya , Blackburn Marsha , Kutlar Abdullah , Harris Ryan A. , Pollock David M. , Pollock Jennifer S. 
Published: November 2024

Abstract
Sickle cell disease (SCD) carries a significant risk for poor vascular health and vascular dysfunction. High levels of vascular reactive oxygen species (ROS) as well as elevated plasma endothelin-1 (ET-1), a potent vasoconstrictor with actions via the ETA receptor, are both common phenotypes in SCD. Alpha-1 adrenergic receptor activation is a major mediator of stress-induced vasoconstriction. However, the mechanism of the SCD enhanced vasoconstrictive response is unknown. We hypothesized that SCD induces enhanced alpha-1 adrenergic mediated vasoconstriction through the ET-1/ETA receptor pathway in arterial tissues. Utilizing humanized SCD (HbSS) and genetic control (HbAA) mice, alpha-1a, but not alpha-1b or alpha-1d, receptor expression was significantly greater in aortic tissue from HbSS mice compared to HbAA mice. Significantly enhanced vasoconstriction in aortic and carotid arterial segments were observed from HbSS mice compared with HbAA mice. Treatment with ambrisentan, a selective ETA receptor antagonist, and a ROS scavenger normalized the aortic vasoconstrictive response in HbSS mice. In a randomized translational study, patients with SCD were treated with placebo or ambrisentan for 3 months, with the treatment group showing an increase in the percent brachial arterial diameter. Taken together, these data suggest that the ETA receptor pathway interaction with the adrenergic receptor pathway contributes to enhanced aortic vasoconstriction in SCD. Findings indicate the potential of ETA antagonism as a therapeutic avenue for improving vascular health in SCD.
Joint image dehazing and denoising for single haze image enhancement
Authors: Yu Yuting , Bosheng Ding , Huang Shizhao , Cheng Ming , Wang Enliang , Tu Defeng , Tan Linglong 
Published: November 2024

AbstractOutdoor haze images are typically degraded by noise due to the external environment and imaging equipment. The existing haze image enhancement methods ignore the interrelation between haze and noise, which cannot suppress the noise and remove the haze simultaneously. To address these intractable problems, a dual‐branch architecture that combines dehazing and denoising is proposed here to restore clear images. First, dark channel prior and unsupervised networks in the image dehazing branch to remove the image blur are adopted. Then, the image denoising branch removes the image noise in parallel by constructing a mean/extreme sampler and a self‐supervised network. Finally, a convolutional neural network fusion strategy is presented to fuse output images from the aforementioned two branches to generate the final qualified results. Extensive experiments reveal that the proposed haze image enhancement method outperforms other state‐of‐the‐art methods in terms of peak signal‐to‐noise ratio (PSNR) and structural similarity index measure (SSIM).
Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning
Authors: Erüst Ali Can , Taşcıkaraoğlu Fatma Yıldız 
Published: November 2024

AbstractThis paper considers the real‐time spatio‐temporal electric vehicle charging navigation problem in a dynamic environment by utilizing a shortest path‐based reinforcement learning approach. In a data sharing system including transportation network, an electric vehicle (EV) and EV charging stations (EVCSs), it is aimed to determine the most convenient EVCS and the optimal path for reducing the travel, charging and waiting costs. To estimate the waiting times at EVCSs, Gaussian process regression algorithm is integrated using a real‐time dataset comprising of state‐of‐charge and arrival‐departure times of EVs. The optimization problem is modelled as a Markov decision process with unknown transition probability to overcome the uncertainties arising from time‐varying variables. A recently proposed on‐policy actor–critic method, phasic policy gradient (PPG) which extends the proximal policy optimization algorithm with an auxiliary optimization phase to improve training by distilling features from the critic to the actor network, is used to make EVCS decisions on the network where EV travels through the optimal path from origin node to EVCS by considering dynamic traffic conditions, unit value of EV owner and time‐of‐use charging price. Three case studies are carried out for 24 nodes Sioux‐Falls benchmark network. It is shown that phasic policy gradient achieves an average of 9% better reward compared to proximal policy optimization and the total time decreases by 7–10% when EV owner cost is considered.