bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative ultrasound image assessment of the optic nerve subarachnoid space during 90-day head-down tilt bed rest
Authors: Xie Yuan , Fu Yingdi , Shao Yaqi , Qu Lina , Yang Jiangang , Yang Chengjia , Zhou Kun , Li Kai , Xu Zi , Xu Dong , Cao Kai , Tian Ning , Lv Ke , Wang Linjie , Wang Yaping , Wang Ningli , Li Yinghui 
Published: January 2024

AbstractThe elevation in the optic nerve sheath (ONS) pressure (ONSP) due to microgravity-induced headward fluid shift is the primary hypothesized contributor to SANS. This longitudinal study aims to quantify the axial plane of the optic nerve subarachnoid space area (ONSSA), which is filled with cerebrospinal fluid (CSF) and expands with elevated ONSP during and after head-down tilt (HDT) bed rest (BR). 36 healthy male volunteers (72 eyes) underwent a 90-day strict 6° HDT BR. Without obtaining the pre-HDT data, measurements were performed on days 30, 60, and 90 during HDT and at 6 recovery time points extended to 180-days (R + 180) in a supine position. Portable B-scan ultrasound was performed using the 12 MHz linear array probe binocularly. The measurements of the ONS and the calculation of the ONSSA were performed with ImageJ 1.51 analysis software by two experienced observers in a masked manner. Compared to R + 180, the ONSSA on HDT30, HDT60, and HDT90 exhibited a consistently significant distention of 0.44 mm2 (95% CI: 0.13 to 0.76 mm2, P = 0.001), 0.45 mm2 (95% CI: 0.15 to 0.75 mm2, P = 0.001), and 0.46 mm2 (95% CI: 0.15 to 0.76 mm2, P < 0.001), respectively, and recovered immediately after HDT on R + 2. Such small changes in the ONSSA were below the lateral resolution limit of ultrasound (0.4 mm) and may not be clinically relevant, possibly due to ONS hysteresis causing persistent ONS distension. Future research can explore advanced quantitative portable ultrasound-based techniques and establish comparisons containing the pre-HDT measurements to deepen our understanding of SANS.
Genetic susceptibility modifies the association of long-term air pollution exposure on Parkinson’s disease
Authors: Huang Yi-Ming , Ma Ya-Hui , Gao Pei-Yang , Cui Xi-Han , Hou Jia-Hui , Chi Hao-Chen , Fu Yan , Wang Zhi-Bo , Feng Jian-Feng , Cheng Wei , Tan Lan , Yu Jin-Tai 
Published: January 2024

AbstractInconsistent findings exist regarding the potential association between polluted air and Parkinson’s disease (PD), with unclear insights into the role of inherited sensitivity. This study sought to explore the potential link between various air pollutants and PD risk, investigating whether genetic susceptibility modulates these associations. The population-based study involved 312,009 initially PD-free participants with complete genotyping data. Annual mean concentrations of PM2.5, PM10, NO2, and NOx were estimated, and a polygenic risk score (PRS) was computed to assess individual genetic risks for PD. Cox proportional risk models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between ambient air pollutants, genetic risk, and incident PD. Over a median 12.07-year follow-up, 2356 PD cases (0.76%) were observed. Compared to the lowest quartile of air pollution, the highest quartiles of NO2 and PM10 pollution showed HRs and 95% CIs of 1.247 (1.089–1.427) and 1.201 (1.052–1.373) for PD incidence, respectively. Each 10 μg/m3 increase in NO2 and PM10 yielded elevated HRs and 95% CIs for PD of 1.089 (1.026–1.155) and 1.363 (1.043–1.782), respectively. Individuals with significant genetic and PM10 exposure risks had the highest PD development risk (HR: 2.748, 95% CI: 2.145–3.520). Similarly, those with substantial genetic and NO2 exposure risks were over twice as likely to develop PD compared to minimal-risk counterparts (HR: 2.414, 95% CI: 1.912–3.048). Findings suggest that exposure to air contaminants heightens PD risk, particularly in individuals genetically predisposed to high susceptibility.
Second-scale rotational coherence and dipolar interactions in a gas of ultracold polar molecules
Authors: Gregory Philip D. , Fernley Luke M. , Tao Albert Li , Bromley Sarah L. , Stepp Jonathan , Zhang Zewen , Kotochigova Svetlana , Hazzard Kaden R. A. , Cornish Simon L. 
Published: January 2024

AbstractUltracold polar molecules combine a rich structure of long-lived internal states with access to controllable long-range anisotropic dipole–dipole interactions. In particular, the rotational states of polar molecules confined in optical tweezers or optical lattices may be used to encode interacting qubits for quantum computation or pseudo-spins for simulating quantum magnetism. As with all quantum platforms, the engineering of robust coherent superpositions of states is vital. However, for optically trapped molecules, the coherence time between rotational states is typically limited by inhomogeneous differential light shifts. Here we demonstrate a rotationally magic optical trap for 87Rb133Cs molecules that supports a Ramsey coherence time of 0.78(4) s in the absence of dipole–dipole interactions. This is estimated to extend to >1.4 s at the 95% confidence level using a single spin-echo pulse. In our trap, dipolar interactions become the dominant mechanism by which Ramsey contrast is lost for superpositions that generate oscillating dipoles. By changing the states forming the superposition, we tune the effective dipole moment and show that the coherence time is inversely proportional to the strength of the dipolar interaction. Our work unlocks the full potential of the rotational degree of freedom in molecules for quantum computation and quantum simulation.
Long-lived valley states in bilayer graphene quantum dots
Authors: Garreis Rebekka , Tong Chuyao , Terle Jocelyn , Ruckriegel Max Josef , Gerber Jonas Daniel , Gächter Lisa Maria , Watanabe Kenji , Taniguchi Takashi , Ihn Thomas , Ensslin Klaus , Huang Wei Wister 
Published: January 2024

AbstractBilayer graphene is a promising platform for electrically controllable qubits in a two-dimensional material. Of particular interest is the ability to encode quantum information in the valley degree of freedom, a two-fold orbital degeneracy that arises from the symmetry of the hexagonal crystal structure. The use of valleys could be advantageous, as known spin- and orbital-mixing mechanisms are unlikely to be at work for valleys, promising more robust qubits. The Berry curvature associated with valley states allows for electrical control of their energies, suggesting routes for coherent qubit manipulation. However, the relaxation time of valley states—which ultimately limits these qubits’ coherence properties and therefore their suitability as practical qubits—is not yet known. Here we measure the characteristic relaxation times of these spin and valley states in gate-defined bilayer graphene quantum dot devices. Different valley states can be distinguished from each other with a fidelity of over 99%. The relaxation time between valley triplets and singlets exceeds 500 ms and is more than one order of magnitude longer than for spin states. This work facilitates future measurements on valley-qubit coherence, demonstrating bilayer graphene as a practical platform hosting electrically controlled, long-lived valley qubits.
Regressive vision transformer for dog cardiomegaly assessment
Authors: Li Jialu , Zhang Youshan 
Published: January 2024

AbstractCardiac disease is one of the leading causes of death in dogs. Automatic cardiomegaly detection has great significance in helping clinicians improve the accuracy of the diagnosis process. Deep learning methods show promising results in improving cardiomegaly classification accuracy, while they are still not widely applied in clinical trials due to the difficulty in mapping predicted results with input radiographs. To overcome these challenges, we first collect large-scale dog heart X-ray images. We then develop a dog heart labeling tool and apply a few-shot generalization strategy to accelerate the label speed. We also develop a regressive vision transformer model with an orthogonal layer to bridge traditional clinically used VHS metric with deep learning models. Extensive experimental results demonstrate that the proposed model achieves state-of-the-art performance.
Deep reinforcement learning for microstructural optimisation of silica aerogels
Authors: Pandit Prakul , Abdusalamov Rasul , Itskov Mikhail , Rege Ameya 
Published: January 2024

AbstractSilica aerogels are being extensively studied for aerospace and transportation applications due to their diverse multifunctional properties. While their microstructural features dictate their thermal, mechanical, and acoustic properties, their accurate characterisation remains challenging due to their nanoporous morphology and the stochastic nature of gelation. In this work, a deep reinforcement learning (DRL) framework is presented to optimise silica aerogel microstructures modelled with the diffusion-limited cluster–cluster aggregation (DLCA) algorithm. For faster computations, two environments consisting of DLCA surrogate models are tested with the DRL framework for inverse microstructure design. The DRL framework is shown to effectively optimise the microstructure morphology, wherein the error of the material properties achieved is dependent upon the complexity of the environment. However, in all cases, with adequate training of the DRL agent, material microstructures with desired properties can be achieved by the framework. Thus, the methodology provides a resource-efficient means to design aerogels, offering computational advantages over experimental iterations or direct numerical solutions.
Association of sleep quality with duty hours, mental health, and medical errors among Japanese postgraduate residents: a cross-sectional study
Authors: Nagasaki Kazuya , Kobayashi Hiroyuki , Nishizaki Yuji , Kurihara Masaru , Watari Takashi , Shimizu Taro , Yamamoto Yu , Shikino Kiyoshi , Fukui Sho , Nishiguchi Sho , Katayama Kohta , Tokuda Yasuharu 
Published: January 2024

AbstractLong duty hours (DH) impair sleep and negatively affect residents’ health and medical safety. This cross-sectional study investigated the association among residents’ DH, sleep duration, insomnia, sleep impairment, depressive symptoms, and self-reported medical errors among 5579 residents in Japan who completed the General Medicine In-Training Examination (2021) and participated in the training-environment survey. Weekly DH was classified under seven categories. Sleep duration and insomnia symptoms, from the Athens Insomnia Scale, were analysed to determine sleep impairment; depressive symptoms and medical errors were self-reported. Among 5095 residents, 15.5% slept < 5 h/day, and 26.7% had insomnia. In multivariable analysis, compared with ≥ 60 and < 70, DH ≥ 90 h/week associated with shorter sleep duration and worsen insomnia symptoms. Shorter durations of sleep and more intense symptoms of insomnia were associated with increased depressive symptoms. Medical errors increased only among residents with insomnia, but were not associated with sleep duration. DH > 90 h/week could lead to shorter sleep duration, worsen insomnia symptoms, and negatively impact well-being and medical safety. There was no significant association between sleep duration and medical errors; however, insomnia conferred an increased risk of medical errors. Limiting DH for residents to avoid excessive workload can help improve resident sleep, enhance resident well-being, and potentially reduce insomnia-associated medical errors.
Exploring the impact of intensified multiple session tDCS over the left DLPFC on brain function in MCI: a randomized control trial
Authors: Šimko P. , Pupíková M. , Gajdoš M. , Klobušiaková P. , Vávra V. , Šimo A. , Rektorová I. 
Published: January 2024

AbstractTranscranial direct current stimulation combined with cognitive training (tDCS-cog) represents a promising approach to combat cognitive decline among healthy older adults and patients with mild cognitive impairment (MCI). In this 5-day-long double-blinded randomized trial, we investigated the impact of intensified tDCS-cog protocol involving two trains of stimulation per day on working memory (WM) enhancement in 35 amnestic and multidomain amnestic MCI patients. Specifically, we focused to improve WM tasks relying on top-down attentional control and hypothesized that intensified tDCS would enhance performance of visual object matching task (VOMT) immediately after the stimulation regimen and at a 1-month follow-up. Secondarily, we explored whether the stimulation would augment online visual working memory training. Using fMRI, we aimed to elucidate the neural mechanisms underlying the intervention effects by analyzing BOLD activations during VOMT. Our main finding revealed no superior after-effects of tDCS-cog over the sham on VOMT among individuals with MCI as indicated by insignificant immediate and long-lasting after-effects. Additionally, the tDCS-cog did not enhance online training as predicted. The fMRI analysis revealed brain activity alterations in right insula that may be linked to tDCS-cog intervention. In the study we discuss the insignificant behavioral results in the context of the current evidence in tDCS parameter space and opening the discussion of possible interference between trained cognitive tasks.
Isolation and characterization of novel Bacillus strains with superior probiotic potential: comparative analysis and safety evaluation
Authors: Golnari Mohsen , Bahrami Nastaran , Milanian Zahra , Rabbani Khorasgani Mohammad , Asadollahi Mohammad Ali , Shafiei Rasoul , Fatemi Seyed Safa-Ali 
Published: January 2024

AbstractDespite the current use of some Bacillus spp. as probiotics, looking for and introducing new efficient and safe potential probiotic strains is one of the most important topics in both microbiology and food industry. This study aimed to isolate, identify, and evaluate the probiotic characteristics and safety of some Bacillus spp. from natural sources. Thirty-six spore-forming, Gram-positive, and catalase-positive Bacillus isolates were identified in 54 samples of soil, feces and dairy products. Bacterial identification was performed using 16S rDNA sequencing. To evaluate the probiotic potential of isolates, the resistance of bacterial cells to simulated gastrointestinal tract (GIT) conditions, the presence of enterotoxin genes, their susceptibility to antibiotics, antimicrobial and hemolytic activities and biochemical profiles were investigated. The results revealed that eight sporulating Bacillus spp. isolates fulfilled all tested probiotic criteria. They showed a high growth rate, non-hemolytic and lecithinase activity, and resistance to simulated GIT conditions. These strains exhibited broad-spectrum antibacterial activity against pathogenic bacteria. In addition, they did not exhibit antibacterial resistance to the 12 tested antibiotics. The results of this study suggest that these isolates can be considered as candidates for functional foods and as safe additives to improve diet quality.
NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data
Authors: Haque Rezuana , Hassan Md. Mehedi , Bairagi Anupam Kumar , Shariful Islam Sheikh Mohammed 
Published: January 2024

AbstractBrain tumors (BTs) are one of the deadliest diseases that can significantly shorten a person’s life. In recent years, deep learning has become increasingly popular for detecting and classifying BTs. In this paper, we propose a deep neural network architecture called NeuroNet19. It utilizes VGG19 as its backbone and incorporates a novel module named the Inverted Pyramid Pooling Module (iPPM). The iPPM captures multi-scale feature maps, ensuring the extraction of both local and global image contexts. This enhances the feature maps produced by the backbone, regardless of the spatial positioning or size of the tumors. To ensure the model’s transparency and accountability, we employ Explainable AI. Specifically, we use Local Interpretable Model-Agnostic Explanations (LIME), which highlights the features or areas focused on while predicting individual images. NeuroNet19 is trained on four classes of BTs: glioma, meningioma, no tumor, and pituitary tumors. It is tested on a public dataset containing 7023 images. Our research demonstrates that NeuroNet19 achieves the highest accuracy at 99.3%, with precision, recall, and F1 scores at 99.2% and a Cohen Kappa coefficient (CKC) of 99%.
A CNN-based model to count the leaves of rosette plants (LC-Net)
Authors: Deb Mainak , Dhal Krishna Gopal , Das Arunita , Hussien Abdelazim G. , Abualigah Laith , Garai Arpan 
Published: January 2024

AbstractPlant image analysis is a significant tool for plant phenotyping. Image analysis has been used to assess plant trails, forecast plant growth, and offer geographical information about images. The area segmentation and counting of the leaf is a major component of plant phenotyping, which can be used to measure the growth of the plant. Therefore, this paper developed a convolutional neural network-based leaf counting model called LC-Net. The original plant image and segmented leaf parts are fed as input because the segmented leaf part provides additional information to the proposed LC-Net. The well-known SegNet model has been utilised to obtain segmented leaf parts because it outperforms four other popular Convolutional Neural Network (CNN) models, namely DeepLab V3+, Fast FCN with Pyramid Scene Parsing (PSP), U-Net, and Refine Net. The proposed LC-Net is compared to the other recent CNN-based leaf counting models over the combined Computer Vision Problems in Plant Phenotyping (CVPPP) and KOMATSUNA datasets. The subjective and numerical evaluations of the experimental results demonstrate the superiority of the LC-Net to other tested models.
Nonlinear relationship between gonadotropin total dose applied and live birth rates in non-PCOS patients: a retrospective cohort study
Authors: Xu Xiaoyuan , Yang Aimin , Han Yan , Li Siran , Wang Wei , Hao Guimin , Cui Na 
Published: January 2024

AbstractThe purpose of this article is to explore the relationship between the total dose of follicle-stimulating hormone (FSH) applied during controlled ovulation stimulation and the live birth rates (LBRs) in non-PCOS population. Many studies have found no difference between the dose of FSH application and pregnancy outcomes such as clinical pregnancy rates after fresh embryo transfer. However, a recent large retrospective analysis found a negative correlation between live birth rates and increasing dose of FSH. It is still controversial about the association between FSH dose and LBRs. In addition, no studies have yet explored the nonlinear relationship between FSH and LBRs. This cohort study included a total of 11,645 patients who had accepted IVF/intracytoplasmic sperm injection (ICSI) at the second hospital of Hebei medical university between December 2014 to December 2019. PCOS was identified by Rotterdam PCOS criteria. We researched the association between FSH total dose and live birth rates (LBRs) using multivariate regression analysis. In addition, a model for nonlinear relationships based on a two-part linear regression was applied. The analysis of threshold effects indicated that LBR increased with every 1000 IU FSH when the concentration of FSH was lower than 1410 IU (OR 1.55, 95% CI [1.05, 2.28]); however, a negative association between FSH dose and LBR (OR 0.94, 95% CI [0.89, 0.99]) was found when the FSH total dose was higher than 1410 IU. It is worth noting that the relationship between LBR and FSH dose varied among patients of different ages (OR 0.92 vs 1.06, P for interaction < 0.05).
Ant backbone phylogeny resolved by modelling compositional heterogeneity among sites in genomic data
Authors: Cai Chenyang 
Published: January 2024

AbstractAnts are the most ubiquitous and ecologically dominant arthropods on Earth, and understanding their phylogeny is crucial for deciphering their character evolution, species diversification, and biogeography. Although recent genomic data have shown promise in clarifying intrafamilial relationships across the tree of ants, inconsistencies between molecular datasets have also emerged. Here I re-examine the most comprehensive published Sanger-sequencing and genome-scale datasets of ants using model comparison methods that model among-site compositional heterogeneity to understand the sources of conflict in phylogenetic studies. My results under the best-fitting model, selected on the basis of Bayesian cross-validation and posterior predictive model checking, identify contentious nodes in ant phylogeny whose resolution is modelling-dependent. I show that the Bayesian infinite mixture CAT model outperforms empirical finite mixture models (C20, C40 and C60) and that, under the best-fitting CAT-GTR + G4 model, the enigmatic Martialis heureka is sister to all ants except Leptanillinae, rejecting the more popular hypothesis supported under worse-fitting models, that place it as sister to Leptanillinae. These analyses resolve a lasting controversy in ant phylogeny and highlight the significance of model comparison and adequate modelling of among-site compositional heterogeneity in reconstructing the deep phylogeny of insects.
Cysteine-rich with EGF-like domains 2 (CRELD2) is an endoplasmic reticulum stress-inducible angiogenic growth factor promoting ischemic heart repair
Authors: Wu Xuekun , Zheng Linqun , Reboll Marc R. , Hyde Lillian F. , Mass Elvira , Niessen Hans W. , Kosanke Maike , Pich Andreas , Giannitsis Evangelos , Tillmanns Jochen , Bauersachs Johann , Heineke Joerg , Wang Yong , Korf-Klingebiel Mortimer , Polten Felix , Wollert Kai C. 
Published: January 2024

AbstractTissue repair after myocardial infarction (MI) is guided by autocrine and paracrine-acting proteins. Deciphering these signals and their upstream triggers is essential when considering infarct healing as a therapeutic target. Here we perform a bioinformatic secretome analysis in mouse cardiac endothelial cells and identify cysteine-rich with EGF-like domains 2 (CRELD2), an endoplasmic reticulum stress-inducible protein with poorly characterized function. CRELD2 was abundantly expressed and secreted in the heart after MI in mice and patients. Creld2-deficient mice and wild-type mice treated with a CRELD2-neutralizing antibody showed impaired de novo microvessel formation in the infarct border zone and developed severe postinfarction heart failure. CRELD2 protein therapy, conversely, improved heart function after MI. Exposing human coronary artery endothelial cells to recombinant CRELD2 induced angiogenesis, associated with a distinct phosphoproteome signature. These findings identify CRELD2 as an angiogenic growth factor and unravel a link between endoplasmic reticulum stress and ischemic tissue repair.