bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of hearing loss, tinnitus, vertigo and sudden deafness among patients with polymyositis and dermatomyositis
Authors: Hung Shih-Han , Xirasagar Sudha , Dang Luong Huu , Viet-Nhi Nguyen-Kieu , Cheng Yen-Fu , Chen Chin-Shyan , Lin Herng-Ching 
Published: March 2024

AbstractLittle is known about a possible association of autoimmune inner ear disease among patients diagnosed with polymyositis (PM)/dermatomyositis (DM). This study aimed to explore differences in the prevalence of inner ear symptoms among patients with and without PM/DM using a nationwide population-based dataset. Data for this study were retrieved from the Taiwan National Health Insurance Research Database. The study sample included 1622 patients diagnosed with PM/DM and 8109 propensity-score matched comparison patients without PM/DM. We performed multivariate logistic regressions to calculate odds ratios (ORs) and 95% confidence interval (CI) for tinnitus, hearing loss, sudden deafness, and vertigo among patients with PM/DM versus comparison patients. Chi-square tests showed statistically significant differences between patients with PM/DM and comparison patients in the prevalence of tinnitus (16.1% vs. 12.7%, p < 0.001), non-conductive hearing loss (9.2% vs. 6.8%, p < 0.001), and vertigo (14.4% vs. 11.1%, p < 0.001). The adjusted ORs for tinnitus, non-conductive hearing loss, and vertigo, respectively, were 1.332 (95% CI = 1.147–1.547), 1.399 (95% CI = 1.154–1.696), and 1.374 (95% CI = 1.173–1.611) for patients with PM/DM when compared to comparison patients. Our study finds that patients with PM/DM have higher prevalence rates of tinnitus, non-conductive hearing loss, and vertigo than comparison patients.
Prenatal delta-9-tetrahydrocannabinol exposure alters fetal neurodevelopment in rhesus macaques
Authors: Ryan Kimberly S. , Karpf Joshua A. , Chan Chi Ngai , Hagen Olivia L. , McFarland Trevor J. , Urian J. Wes , Wang Xiaojie , Boniface Emily R. , Hakar Melanie H. , Terrobias Jose Juanito D. , Graham Jason A. , Passmore Scarlet , Grant Kathleen A. , Sullivan Elinor L. , Grafe Marjorie R. , Saugstad Julie A. , Kroenke Christopher D. , Lo Jamie O. 
Published: March 2024

AbstractPrenatal cannabis use is associated with adverse offspring neurodevelopmental outcomes, however the underlying mechanisms are relatively unknown. We sought to determine the impact of chronic delta-9-tetrahydrocannabinol (THC) exposure on fetal neurodevelopment in a rhesus macaque model using advanced imaging combined with molecular and tissue studies. Animals were divided into two groups, control (n = 5) and THC-exposed (n = 5), which received a daily THC edible pre-conception and throughout pregnancy. Fetal T2-weighted MRI was performed at gestational days 85 (G85), G110, G135 and G155 to assess volumetric brain development. At G155, animals underwent cesarean delivery with collection of fetal cerebrospinal fluid (CSF) for microRNA (miRNA) studies and fetal tissue for histologic analysis. THC exposure was associated with significant age by sex interactions in brain growth, and differences in fetal brain histology suggestive of brain dysregulation. Two extracellular vesicle associated-miRNAs were identified in THC-exposed fetal CSF; pathway analysis suggests that these miRNAs are associated with dysregulated axonal guidance and netrin signaling. This data is indicative of subtle molecular changes consistent with the observed histological data, suggesting a potential role for fetal miRNA regulation by THC. Further studies are needed to determine whether these adverse findings correlate with long-term offspring neurodevelopmental health.
A graph convolutional network with dynamic weight fusion of multi-scale local features for diabetic retinopathy grading
Authors: Wang Yipeng , Wang Liejun , Guo Zhiqing , Song Shiji , Li Yanhong 
Published: March 2024

AbstractDiabetic retinopathy (DR) is a serious ocular complication that can pose a serious risk to a patient’s vision and overall health. Currently, the automatic grading of DR is mainly using deep learning techniques. However, the lesion information in DR images is complex, variable in shape and size, and randomly distributed in the images, which leads to some shortcomings of the current research methods, i.e., it is difficult to effectively extract the information of these various features, and it is difficult to establish the connection between the lesion information in different regions. To address these shortcomings, we design a multi-scale dynamic fusion (MSDF) module and combine it with graph convolution operations to propose a multi-scale dynamic graph convolutional network (MDGNet) in this paper. MDGNet firstly uses convolution kernels with different sizes to extract features with different shapes and sizes in the lesion regions, and then automatically learns the corresponding weights for feature fusion according to the contribution of different features to model grading. Finally, the graph convolution operation is used to link the lesion features in different regions. As a result, our proposed method can effectively combine local and global features, which is beneficial for the correct DR grading. We evaluate the effectiveness of method on two publicly available datasets, namely APTOS and DDR. Extensive experiments demonstrate that our proposed MDGNet achieves the best grading results on APTOS and DDR, and is more accurate and diverse for the extraction of lesion information.
Sleep- and sleep deprivation-related changes of vertex auditory evoked potentials during the estrus cycle in female rats
Authors: Tóth Attila , Traub Máté , Bencsik Norbert , Détári László , Hajnik Tünde , Dobolyi Arpád 
Published: March 2024

AbstractThe estrus cycle in female rodents has been shown to affect a variety of physiological functions. However, little is known about its presumably thorough effect on auditory processing during the sleep–wake cycle and sleep deprivation. Vertex auditory evoked potentials (vAEPs) were evoked by single click tone stimulation and recorded during different stages of the estrus cycle and sleep deprivation performed in metestrus and proestrus in female rats. vAEPs showed a strong sleep-dependency, with the largest amplitudes present during slow wave sleep while the smallest ones during wakefulness. Higher amplitudes and longer latencies were seen in the light phase during all vigilance stages. The largest amplitudes were found during proestrus (light phase) while the shortest latencies were seen during estrus (dark phase) compared to the 2nd day diestrus baseline. High-amplitude responses without latency changes were also seen during metestrus with increased homeostatic sleep drive. More intense and faster processing of auditory information during proestrus and estrus suggesting a more effective perception of relevant environmental cues presumably in preparation for sexual receptivity. A 4-h sleep deprivation resulted in more pronounced sleep recovery in metestrus compared to proestrus without difference in delta power replacement suggesting a better tolerance of sleep deprivation in proestrus. Sleep deprivation decreased neuronal excitability and responsiveness in a similar manner both during metestrus and proestrus, suggesting that the negative consequences of sleep deprivation on auditory processing may have a limited correlation with the estrus cycle stage.
Generation of a galactic chronology with impact ages and spiral arm tangents
Authors: Gillman Michael , Zhang Rui 
Published: March 2024

AbstractResolving the role of galactic processes in Solar System/Earth events necessitates a robust temporal model. However, astrophysical theory diverges with models varying from long-lasting spiral density waves with uniform pattern speeds and arm structures to others with fleeting and unpredictable features. Here, we address those issues with (1) an analysis of patterns of impact periodicity over periods of 10 to 250 million years (Myr) using circular statistics and (2), an independent logarithmic spiral arm model fitted to arm tangents of 870 micron dust. Comparison of the impact periodicity results with the best-fit spiral arm model suggests a galactic period of 660 Myr, i.e. 165 Myr to pass from one arm to the next in a four spiral arm model, with the most recent arm passage around 52 million years ago (Ma). The oldest impact ages imply that the emerging galactic chronology model is robust for at least the last 2 Gyr. The arm-passing time is consistent with spectral analyses of zircons across 3 Gyrs. Overall, the model provides a temporal framework against which to test hypotheses of galactic mechanisms for global events such as mass extinctions and superchrons.
In vivo phenotypic vascular dysfunction extends beyond the aorta in a mouse model for fibrillin-1 (Fbn1) mutation
Authors: Curry T. , Barrameda M. E. , Thomas T. Currier , Esfandiarei M. 
Published: March 2024

AbstractIn individuals with Marfan Syndrome (MFS), fibrillin-1 gene (FBN1) mutations can lead to vascular wall weakening and dysfunction. The experimental mouse model of MFS (Fbn1C1041G/+) has been advantageous in investigating MFS-associated life-threatening aortic aneurysms. It is well established that the MFS mouse model exhibits an accelerated-aging phenotype in elastic organs like the aorta, lung, and skin. However, the impact of Fbn1 mutations on the in vivo function and structure of various artery types with the consideration of sex and age, has not been adequately explored in real-time and a clinically relevant context. In this study, we investigate if Fbn1 mutation contributes to sex-dependent alterations in central and cerebral vascular function similar to phenotypic changes associated with normal aging in healthy control mice. In vivo ultrasound imaging of central and cerebral vasculature was performed in 6-month-old male and female MFS and C57BL/6 mice and sex-matched 12-month-old (middle-aged) healthy control mice. Our findings confirm aortic enlargement (aneurysm) and wall stiffness in MFS mice, but with exacerbation in male diameters. Coronary artery blood flow velocity (BFV) in diastole was not different but left pulmonary artery BFV was decreased in MFS and 12-month-old control mice regardless of sex. At 6 months of age, MFS male mice show decreased posterior cerebral artery BFV as compared to age-matched control males, with no difference observed between female cohorts. Reduced mitral valve early-filling velocities were indicated in MFS mice regardless of sex. Male MFS mice also demonstrated left ventricular hypertrophy. Overall, these results underscore the significance of biological sex in vascular function and structure in MFS mice, while highlighting a trend of pre-mature vascular aging phenotype in MFS mice that is comparable to phenotypes observed in older healthy controls. Furthermore, this research is a vital step in understanding MFS's broader implications and sets the stage for more in-depth future analyses, while providing data-driven preclinical justification for re-evaluating diagnostic approaches and therapeutic efficacy.
Numerical simulation study on distinguishing nonlinear propagation regimes of femtosecond pulses in fused silica
Authors: Liu Faqian , Xi Tingting , Zhang Lanzhi , Li Dongwei , Hao Zuoqiang 
Published: March 2024

AbstractWe perform numerical simulations to investigate the nonlinear propagation dynamics of femtosecond Gaussian and vortex beams in fused silica. By analyzing the extent of spectral broadening, we are able to distinguish between the linear, self-focusing, and filamentation regimes. Additionally, the maximum intensity and fluence distribution within the cross-section of the vortex beams are analyzed for different incident laser energies. The results demonstrate a direct correlation between the spectral broadening and the peak intensity of the femtosecond laser pulse. As a result, this provides a theoretical foundation for distinguishing different propagation regimes, and determining critical powers for self-focusing and filamentation of both femtosecond Gaussian and structured beams.
AI supported fetal echocardiography with quality assessment
Authors: Taksoee-Vester Caroline A. , Mikolaj Kamil , Bashir Zahra , Christensen Anders N. , Petersen Olav B. , Sundberg Karin , Feragen Aasa , Svendsen Morten B. S. , Nielsen Mads , Tolsgaard Martin G. 
Published: March 2024

AbstractThis study aimed to develop a deep learning model to assess the quality of fetal echocardiography and to perform prospective clinical validation. The model was trained on data from the 18–22-week anomaly scan conducted in seven hospitals from 2008 to 2018. Prospective validation involved 100 patients from two hospitals. A total of 5363 images from 2551 pregnancies were used for training and validation. The model's segmentation accuracy depended on image quality measured by a quality score (QS). It achieved an overall average accuracy of 0.91 (SD 0.09) across the test set, with images having above-average QS scoring 0.97 (SD 0.03). During prospective validation of 192 images, clinicians rated 44.8% (SD 9.8) of images as equal in quality, 18.69% (SD 5.7) favoring auto-captured images and 36.51% (SD 9.0) preferring manually captured ones. Images with above average QS showed better agreement on segmentations (p < 0.001) and QS (p < 0.001) with fetal medicine experts. Auto-capture saved additional planes beyond protocol requirements, resulting in more comprehensive echocardiographies. Low QS had adverse effect on both model performance and clinician’s agreement with model feedback. The findings highlight the importance of developing and evaluating AI models based on ‘noisy’ real-life data rather than pursuing the highest accuracy possible with retrospective academic-grade data.
LY2444296, a κ-opioid receptor antagonist, selectively reduces alcohol drinking in male and female Wistar rats with a history of alcohol dependence
Authors: Flores-Ramirez Francisco J. , Illenberger Jessica M. , Pascasio Glenn , Terenius Lars , Martin-Fardon Rémi 
Published: March 2024

AbstractAlcohol use disorder (AUD) remains a major public health concern. The dynorphin (DYN)/κ-opioid receptor (KOP) system is involved in actions of alcohol, particularly its withdrawal-associated negative affective states. This study tested the ability of LY2444296, a selective, short-acting, KOP antagonist, to decrease alcohol self-administration in dependent male and female Wistar rats at 8 h abstinence. Animals were trained to orally self-administer 10% alcohol (30 min/day for 21 sessions) and were made dependent via chronic intermittent alcohol vapor exposure for 6 weeks or exposed to air (nondependent). After 6 weeks, the effect of LY2444296 (0, 3, and 10 mg/kg, p.o.) was tested on alcohol self-administration at 8 h of abstinence. A separate cohort of rats was prepared in parallel, and their somatic withdrawal signs and alcohol self-administration were measured after LY2444296 administration at 8 h, 2 weeks, and 4 weeks abstinence. LY2444296 at 3 and 10 mg/kg significantly reduced physical signs of withdrawal in dependent rats at 8 h abstinence, only. Furthermore, 3 and 10 mg/kg selectively decreased alcohol self-administration in dependent rats at only 8 h abstinence. These results highlight the DYN/KOP system in actions of alcohol during acute abstinence, suggesting KOP antagonism could be beneficial for mitigating acute withdrawal signs and, in turn, significantly reduce excessive alcohol consumption associated with AUD.
Kinetic properties of glucose 6-phosphate dehydrogenase and inhibition effects of several metal ions on enzymatic activity in vitro and cells
Authors: Sun Lindan , Sun Binbin , Zhang Yulei , Chen Keping 
Published: March 2024

AbstractDue to the non-degradable and persistent nature of metal ions in the environment, they are released into water bodies, where they accumulate in fish. In order to assess pollution in fish, the enzyme, glucose 6-phosphate dehydrogenase (G6PD), has been employed as a biomarker due to sensitivity to various ions. This study investigates the kinetic properties of the G6PD enzyme in yellow catfish (Pelteobagrus fulvidraco), and analyzes the effects of these metal ions on the G6PD enzyme activity in the ovarian cell line (CCO) of channel catfish (Ictalurus punctatus). IC50 values and inhibition types of G6PD were determined in the metal ions Cu2+, Al3+, Zn2+, and Cd2+. While, the inhibition types of Cu2+ and Al3+ were the competitive inhibition, Zn2+ and Cd2+ were the linear mixed noncompetitive and linear mixed competitive, respectively. In vitro experiments revealed an inverse correlation between G6PD activity and metal ion concentration, mRNA levels and enzyme activity of G6PD increased at the lower metal ion concentration and decreased at the higher concentration. Our findings suggest that metal ions pose a significant threat to G6PD activity even at low concentrations, potentially playing a crucial role in the toxicity mechanism of metal ion pollution. This information contributes to the development of a biomonitoring tool for assessing metal ion contamination in aquatic species.
Sentiment analysis of video danmakus based on MIBE-RoBERTa-FF-BiLSTM
Authors: Zhao Jianbo , Liu Huailiang , Wang Yakai , Zhang Weili , Zhang Xiaojin , Li Bowei , Sun Tong , Qi Yanwei , Zhang Shanzhuang 
Published: March 2024

AbstractDanmakus are user-generated comments that overlay on videos, enabling real-time interactions between viewers and video content. The emotional orientation of danmakus can reflect the attitudes and opinions of viewers on video segments, which can help video platforms optimize video content recommendation and evaluate users’ abnormal emotion levels. Aiming at the problems of low transferability of traditional sentiment analysis methods in the danmaku domain, low accuracy of danmaku text segmentation, poor consistency of sentiment annotation, and insufficient semantic feature extraction, this paper proposes a video danmaku sentiment analysis method based on MIBE-RoBERTa-FF-BiLSTM. This paper constructs a “Bilibili Must-Watch List and Top Video Danmaku Sentiment Dataset” by ourselves, covering 10,000 positive and negative sentiment danmaku texts of 18 themes. A new word recognition algorithm based on mutual information (MI) and branch entropy (BE) is used to discover 2610 irregular network popular new words from trigrams to heptagrams in the dataset, forming a domain lexicon. The Maslow’s hierarchy of needs theory is applied to guide the consistent sentiment annotation. The domain lexicon is integrated into the feature fusion layer of the RoBERTa-FF-BiLSTM model to fully learn the semantic features of word information, character information, and context information of danmaku texts and perform sentiment classification. Comparative experiments on the dataset show that the model proposed in this paper has the best comprehensive performance among the mainstream models for video danmaku text sentiment classification, with an F1 value of 94.06%, and its accuracy and robustness are also better than other models. The limitations of this paper are that the construction of the domain lexicon still requires manual participation and review, the semantic information of danmaku video content and the positive case preference are ignored.
A deep learning method for empirical spectral prediction and inverse design of all-optical nonlinear plasmonic ring resonator switches
Authors: Adibnia Ehsan , Mansouri-Birjandi Mohammad Ali , Ghadrdan Majid , Jafari Pouria 
Published: March 2024

AbstractAll-optical plasmonic switches (AOPSs) utilizing surface plasmon polaritons are well-suited for integration into photonic integrated circuits (PICs) and play a crucial role in advancing all-optical signal processing. The current AOPS design methods still rely on trial-and-error or empirical approaches. In contrast, recent deep learning (DL) advances have proven highly effective as computational tools, offering an alternative means to accelerate nanophotonics simulations. This paper proposes an innovative approach utilizing DL for spectrum prediction and inverse design of AOPS. The switches employ circular nonlinear plasmonic ring resonators (NPRRs) composed of interconnected metal–insulator–metal waveguides with a ring resonator. The NPRR switching performance is shown using the nonlinear Kerr effect. The forward model presented in this study demonstrates superior computational efficiency when compared to the finite-difference time-domain method. The model analyzes various structural parameters to predict transmission spectra with a distinctive dip. Inverse modeling enables the prediction of design parameters for desired transmission spectra. This model provides a rapid estimation of design parameters, offering a clear advantage over time-intensive conventional optimization approaches. The loss of prediction for both the forward and inverse models, when compared to simulations, is exceedingly low and on the order of 10−4. The results confirm the suitability of employing DL for forward and inverse design of AOPSs in PICs.
Channel-forming discharge based on the extreme value identification of sediment-carrying capacity index
Authors: Ge Hua , Zhu Lingling 
Published: March 2024

AbstractChannel-forming discharge (Dcf) is an important parameter in river management and reservoir flood regulation. Applying the methods for calculating Dcf to reaches downstream reservoirs characterized by drastic changes in water and sediment conditions and long-term scouring status is difficult. Based on the riverbed-shaping principle of sediment-laden water flow, while simultaneously considering the active action of water flow and response of the riverbed, this study proposes a new method for calculating Dcf by identifying the extreme value of the suspended sediment-carrying capacity index. The application of this method to the middle and lower reaches of the Yangtze River showed that after the impoundment of the Three Gorges Reservoir, Dcf in this section was reduced by an amplitude between 2500 and 4700 m3/s. The results can be used to guide the operation of the Three Gorges Reservoir and the management of the middle and lower reaches of the Yangtze River, thus providing reference for other river channels downstream of the reservoir.
Oxidation state of Cu in silicate melts at upper mantle conditions
Authors: Liu Xingcheng , Zhang Lei , Zhu Sanyuan , Li Li , Xiong Xiaolin 
Published: March 2024

AbstractBeyond its economic value, copper (Cu) serves as a valuable tracer of deep magmatic processes due to its close relationship with magmatic sulfide evolution and sensitivity to oxygen fugacity (fO2). However, determining Cu’s oxidation state (+ 1 or + 2) in silicate melts, crucial for interpreting its behavior and reconstructing fO2 in the Earth’s interior, has long been a challenge. This study utilizes X-ray Absorption Near Edge Structure spectroscopy to investigate the Cu oxidation state in hydrous mafic silicate melts equilibrated under diverse fO2 (− 1.8 to 3.1 log units relative to the Fayalite–Magnetite–Quartz buffer), temperature (1150–1300 °C), and pressure (1.0–2.5 GPa) conditions. Our results reveal that Cu predominantly exists as Cu+ across all fO2 conditions, with a minor Cu2+ component. This dominance of Cu+ persists even in relatively oxidized melts, highlighting its limited sensitivity to fO2 under upper mantle conditions. This significantly constrains the utility of Cu as an oxybarometer in hydrous silicate melts in the deep Earth. However, our findings suggest that Cu isotopes primarily reflect the interplay of sulfide segregation/accumulation during magmatic differentiation, shedding light on these fundamental processes in Earth’s interior.