bluuebunny/crossref_metadata_2025_split huggingface dataset:
Edge-enhanced infrared image super-resolution reconstruction model under transformer
Authors: Hu Lei , Hu Long , Chen MingHui 
Published: July 2024

AbstractInfrared images have important applications in military, security and surveillance fields. However, limited by technical factors, the resolution of infrared images is generally low, which seriously limits the application and development of infrared images in various fields. To address the problem of difficult recovery of edge information and easy ringing effect in the super-resolution reconstruction process of infrared images, an edge-enhanced infrared image super-resolution reconstruction model TESR under transformer is proposed. The main structure of this model is transformer. First, in view of the problem of difficult recovery of edge information of infrared images, an edge detection auxiliary network is designed, which can obtain more accurate edge information from the input low-resolution images and enhance the edge details during image reconstruction; then, the CSWin Transformer is introduced to compute the self-attention of horizontal and vertical stripes in parallel, so as to increase the receptive field of the model and enable it to utilize features with higher semantic levels. The super-resolution reconstruction model proposed in this paper can extract more comprehensive image information, and at the same time, it can obtain more accurate edge information to enhance the texture details of super-resolution images, and achieve better reconstruction results.
Children and adults produce distinct technology- and human-directed speech
Authors: Cohn Michelle , Barreda Santiago , Graf Estes Katharine , Yu Zhou , Zellou Georgia 
Published: July 2024

AbstractThis study compares how English-speaking adults and children from the United States adapt their speech when talking to a real person and a smart speaker (Amazon Alexa) in a psycholinguistic experiment. Overall, participants produced more effortful speech when talking to a device (longer duration and higher pitch). These differences also varied by age: children produced even higher pitch in device-directed speech, suggesting a stronger expectation to be misunderstood by the system. In support of this, we see that after a staged recognition error by the device, children increased pitch even more. Furthermore, both adults and children displayed the same degree of variation in their responses for whether “Alexa seems like a real person or not”, further indicating that children’s conceptualization of the system’s competence shaped their register adjustments, rather than an increased anthropomorphism response. This work speaks to models on the mechanisms underlying speech production, and human–computer interaction frameworks, providing support for routinized theories of spoken interaction with technology.
Unveiling a new oceanic anoxic event at the Norian/Rhaetian boundary (Late Triassic)
Authors: Rigo Manuel , Jin Xin , Godfrey Linda , Katz Miriam E. , Sato Honami , Tomimatsu Yuki , Zaffani Mariachiara , Maron Matteo , Satolli Sara , Concheri Giuseppe , Cardinali Alessandra , Wu Qiangwang , Du Yixing , Lei Jerry Zhen Xiao , van Wieren Connor S. , Tackett Lydia S. , Campbell Hamish , Bertinelli Angela , Onoue Tetsuji 
Published: July 2024

AbstractThe latest Triassic was characterised by protracted biotic extinctions concluding in the End-Triassic Extinction (~ 200 Ma) and a global carbon cycle perturbation. The onset of declining diversity is closely related to reducing conditions that spread globally from upper Sevatian (uppermost Norian) to across the Norian-Rhaetian boundary, likely triggered by unusually high volcanic activity. We correlate significant organic carbon cycle perturbations to an increase of CO2 in the ocean–atmosphere system, likely outgassed by the Angayucham igneous province, the onset of which is indicated by the initiation of a rapid decline in 87Sr/86Sr and 188Os/187Os seawater values. A possible causal mechanism involves elevated CO2 levels causing global warming and accelerating chemical weathering, which increased nutrient discharge to the oceans and greatly increased biological productivity. Higher export production and oxidation of organic matter led to a global O2 decrease in marine water across the Norian/Rhaetian boundary (NRB). Biotic consequences of dysoxia/anoxia include worldwide extinctions in some fossil groups, such as bivalves, ammonoids, conodonts, radiolarians.
Scanpro is a tool for robust proportion analysis of single-cell resolution data
Authors: Alayoubi Yousef , Bentsen Mette , Looso Mario 
Published: July 2024

AbstractIn higher organisms, individual cells respond to signals and perturbations by epigenetic regulation and transcriptional adaptation. However, in addition to shifting the expression level of individual genes, the adaptive response of cells can also lead to shifts in the proportions of different cell types. Recent methods such as scRNA-seq allow for the interrogation of expression on the single-cell level, and can quantify individual cell type clusters within complex tissue samples. In order to identify clusters showing differential composition between different biological conditions, differential proportion analysis has recently been introduced. However, bioinformatics tools for robust proportion analysis of both replicated and unreplicated single-cell datasets are critically missing. In this manuscript, we present Scanpro, a modular tool for proportion analysis, seamlessly integrating into widely accepted frameworks in the Python environment. Scanpro is fast, accurate, supports datasets without replicates, and is intended to be used by bioinformatics experts and beginners alike.
Advanced enhancement technique for infrared images of wind turbine blades utilizing adaptive difference multi-scale top-hat transformation
Authors: He Yinchao , Kang Shuang , Li Wenwen , Xu Hongyan , Liu Sen 
Published: July 2024

AbstractEnhancing infrared images is essential for detecting wind turbine blades using infrared technology. This paper introduces an Infrared Image Enhancement Method based on Adaptive Iterative Cutoff Threshold Difference Multi-Scale Top-Hat Transformation (AICT-DMTH) to address the challenge of low image clarity in infrared detection. The method involves performing a black-white difference top-hat transformation by utilizing structural elements of varying scales for dilation and erosion. Additionally, an iterative threshold method is applied to extract more detailed image features, followed by setting a cutoff constant to determine the final scale of the structural element. The effectiveness of the proposed method is evaluated both qualitatively and quantitatively, with infrared images from laboratory and wind farm settings enhanced and compared against existing methods. The experimental results indicate that the proposed method significantly improves the clarity of infrared images, demonstrating robustness in enhancing images from various environments.
Production and stability of cultured red blood cells depends on the concentration of cholesterol in culture medium
Authors: Claessen M. J. A. G. , Yagci N. , Fu K. , Brandsma E. , Kersten M. J. , von Lindern M. , van den Akker E. 
Published: July 2024

AbstractThe production of cultured red blood cells (cRBC) for transfusion purposes requires large scale cultures and downstream processes to purify enucleated cRBC. The membrane composition, and cholesterol content in particular, are important during proliferation of (pro)erythroblasts and for cRBC quality. Therefore, we tested the requirement for cholesterol in the culture medium during expansion and differentiation of erythroid cultures with respect to proliferation, enucleation and purification by filtration. The low cholesterol level (22 µg/dl) in serum free medium was sufficient to expand (pro)erythroblast cultures. Addition of 2.0 or 5.0 mg/dL of free cholesterol at the start of differentiation induction inhibited enucleation compared to the default condition containing 3.3 mg/dl total cholesterol derived from the addition of Omniplasma to serum free medium. Addition of 5.0 mg/dl cholesterol at day 5 of differentiation did not affect the enucleation process but significantly increased recovery of enucleated cRBC following filtration over leukodepletion filters. The addition of cholesterol at day 5 increased the osmotic resistance of cRBC. In conclusion, cholesterol supplementation after the onset of enucleation improved the robustness of cRBC and increased the yield of enucleated cRBC in the purification process.
The limited role of serum neurofilament light chain in predicting pain severity of patients with diabetic polyneuropathy
Authors: Kim A-Sol , Lee Jong-Mok 
Published: July 2024

AbstractPain is one of many complaints expressed by patients with diabetic polyneuropathy. However, no objective measure for pain severity has been available. Neurofilament light chains have been widely used for assessing axonal damage in the neuronal system. Hence, we sought to investigate whether neurofilament light chains can serve as a marker reflecting pain severity in diabetic polyneuropathy. We enrolled the patients with diabetic polyneuropathy. Serum concentrations of neurofilament light chain were then measured using a single-molecule array. Pain severity was evaluated using painDETECT and the Brief Pain Inventory. Moreover, laboratory results including, serum creatinine, HbA1c, and glomerular filtration rate. A correlation test was used to analyze each variable. A total of 42 patients were enrolled. Neurofilament light chain levels were unable to reflect current neuropathic pain severity. However, high levels of neurofilament light chain were a significant predictor of poor diabetes control (r = 0.41; p = 0.02) and kidney damage (r = 0.45; p = 0.01). Serum levels of neurofilament light chain could not reflect current pain severity but was strongly associated with kidney dysfunction and poor diabetes control. Other biomarkers that could predict pain severity need to be uncovered.
LILRB4 knockdown inhibits aortic dissection development by regulating pyroptosis and the JAK2/STAT3 signaling pathway
Authors: Xiong Jianxian , Ling Jiayuan , Yan Jie , Duan Yanyu , Yu Junjian , Li Wentong , Yu Wenbo , Gao Jianfeng , Xie Dilin , Liu Ziyou , Deng Yongzhi , Liao Yongling 
Published: July 2024

AbstractAortic dissection (AD) is a life-threatening condition with a high mortality rate and without effective pharmacological therapies. Our previous study illustrated that leukocyte immunoglobulin-like receptor B4 (LILRB4) knockdown promoted the contractile phenotypic switch and apoptosis of AD cells. This study aimed to further investigate the role of LILRB4 in animal models of AD and elucidate its underlying molecular mechanisms. Animal models of AD were established using 0.1% beta-aminopropionitrile and angiotensin II and an in vitro model was developed using platelet-derived growth factor BB (PDGF-BB). The effects of LILRB4 knockdown on histopathological changes, pyroptosis, phenotype transition, extracellular matrix (ECM), and Janus kinase 2 (JAK2)/signal transducers and activators of transcription 3 (STAT3) pathways were assessed using a series of in vivo and in vitro assays. The effects of the JAK2 inhibitor AG490 on AD cell function, phenotypic transition, and ECM were explored. LILRB4 was highly expressed in AD and its knockdown increased survival rate, reduced AD incidence, and alleviated histopathological changes in the AD mouse model. Furthermore, LILRB4 knockdown promoted contractile phenotype switch, stabilized the ECM, and inhibited pyroptosis. Mechanistically, LILRB4 knockdown inhibited the JAK2/STAT3 signaling pathway. JAK2 inhibitor AG490 inhibited cell viability and migration, enhanced apoptosis, induced G0/G1 cell cycle arrest, and suppressed S-phase progression in PDGF-BB-stimulated human aortic smooth muscle cells. LILRB4 knockdown suppresses AD development by inhibiting pyroptosis and the JAK2/STAT3 signaling pathway.
Investigation on the molecular mechanism of SPA interference with osteogenic differentiation of bone marrow mesenchymal stem cells
Authors: Wen Hong-jie , Zhu Shou-yan , Yang Hua-gang , Guo Feng-yong 
Published: July 2024

AbstractBinding of Staphylococcus aureus protein A (SPA) to osteoblasts induces apoptosis and inhibits bone formation. Bone marrow-derived mesenchymal stem cells (BMSCs) have the ability to differentiate into bone, fat and cartilage. Therefore, it was important to analyze the molecular mechanism of SPA on osteogenic differentiation. We introduced transcript sequence data to screen out differentially expressed genes (DEGs) related to SPA-interfered BMSC. Protein–protein interaction (PPI) network of DEGs was established to screen biomarkers associated with SPA-interfered BMSC. Receiver operating characteristic (ROC) curve was plotted to evaluate the ability of biomarkers to discriminate between two groups of samples. Finally, we performed GSEA and regulatory analysis based on biomarkers. We identified 321 DEGs. Subsequently, 6 biomarkers (Cenpf, Kntc1, Nek2, Asf1b, Troap and Kif14) were identified by hubba algorithm in PPI. ROC analysis showed that six biomarkers could clearly discriminate between normal differentiated and SPA-interfered BMSC. Moreover, we found that these biomarkers were mainly enriched in the pyrimidine metabolism pathway. We also constructed '71 circRNAs-14 miRNAs-5 mRNAs' and '10 lncRNAs-5 miRNAs-2 mRNAs' networks. Kntc1 and Asf1b genes were associated with rno-miR-3571. Nek2 and Asf1b genes were associated with rno-miR-497-5p. Finally, we found significantly lower expression of six biomarkers in the SPA-interfered group compared to the normal group by RT-qPCR. Overall, we obtained 6 biomarkers (Cenpf, Kntc1, Nek2, Asf1b, Troap, and Kif14) related to SPA-interfered BMSC, which provided a theoretical basis to explore the key factors of SPA affecting osteogenic differentiation.
Tumor biomechanics as a novel imaging biomarker to assess response to immunotherapy in a murine glioma model
Authors: Streibel Yannik , Breckwoldt Michael O. , Hunger Jessica , Pan Chenchen , Fischer Manuel , Turco Verena , Boztepe Berin , Fels-Palesandro Hannah , Scheck Jonas G. , Sturm Volker , Karimian-Jazi Kianush , Agardy Dennis A. , Annio Giacomo , Mustapha Rami , Soni Shreya S. , Alasa Abdulrahman , Weidenfeld Ina , Rodell Christopher B. , Wick Wolfgang , Heiland Sabine , Winkler Frank , Platten Michael , Bendszus Martin , Sinkus Ralph , Schregel Katharina 
Published: July 2024

AbstractGlioblastoma is the most common and aggressive primary malignant brain tumor with poor prognosis. Novel immunotherapeutic approaches are currently under investigation. Even though magnetic resonance imaging (MRI) is the most important imaging tool for treatment monitoring, response assessment is often hampered by therapy-related tissue changes. As tumor and therapy-associated tissue reactions differ structurally, we hypothesize that biomechanics could be a pertinent imaging proxy for differentiation. Longitudinal MRI and magnetic resonance elastography (MRE) were performed to monitor response to immunotherapy with a toll-like receptor 7/8 agonist in orthotopic syngeneic experimental glioma. Imaging results were correlated to histology and light sheet microscopy data. Here, we identify MRE as a promising non-invasive imaging method for immunotherapy-monitoring by quantifying changes in response-related tumor mechanics. Specifically, we show that a relative softening of treated compared to untreated tumors is linked to the inflammatory processes following therapy-induced re-education of tumor-associated myeloid cells. Mechanistically, combined effects of myeloid influx and inflammation including extracellular matrix degradation following immunotherapy form the basis of treated tumors being softer than untreated glioma. This is a very early indicator of therapy response outperforming established imaging metrics such as tumor volume. The overall anti-tumor inflammatory processes likely have similar effects on human brain tissue biomechanics, making MRE a promising tool for gauging response to immunotherapy in glioma patients early, thereby strongly impacting patient pathway.
Clinical efficacy of pre-trained large language models through the lens of aphasia
Authors: Cong Yan , LaCroix Arianna N. , Lee Jiyeon 
Published: July 2024

AbstractThe rapid development of large language models (LLMs) motivates us to explore how such state-of-the-art natural language processing systems can inform aphasia research. What kind of language indices can we derive from a pre-trained LLM? How do they differ from or relate to the existing language features in aphasia? To what extent can LLMs serve as an interpretable and effective diagnostic and measurement tool in a clinical context? To investigate these questions, we constructed predictive and correlational models, which utilize mean surprisals from LLMs as predictor variables. Using AphasiaBank archived data, we validated our models’ efficacy in aphasia diagnosis, measurement, and prediction. Our finding is that LLMs-surprisals can effectively detect the presence of aphasia and different natures of the disorder, LLMs in conjunction with the existing language indices improve models’ efficacy in subtyping aphasia, and LLMs-surprisals can capture common agrammatic deficits at both word and sentence level. Overall, LLMs have potential to advance automatic and precise aphasia prediction. A natural language processing pipeline can be greatly benefitted from integrating LLMs, enabling us to refine models of existing language disorders, such as aphasia.
Presurgical management of ulnar nerve entrapment in patients with and without diabetes mellitus
Authors: Andersson Stina , Zimmerman Malin , Perez Raquel , Rydberg Mattias , Dahlin Lars B. 
Published: July 2024

AbstractDiabetes mellitus (DM) is a risk factor for the development of ulnar nerve entrapment (UNE). Differences in surgical outcomes for UNE between patients with and without DM have been reported, but studies on presurgical management are scarce. This study aimed to evaluate the presurgical management of UNE in patients with (DM diagnosis < 2 years of UNE diagnosis) and without DM regarding the level of care for diagnosis and the proportion that proceeds to surgery. Data from 6600 patients with UNE between 2004 and 2019 were included from the Skåne Health Care Register (SHR) and cross-linked with data from the Swedish National Diabetes Register (NDR). The group with UNE and DM was compared to the group with UNE without DM and prevalence ratios were calculated using Cox regression analysis. Patients with DM more often got their first UNE diagnosis in secondary care than in primary care (643/667, 96% vs. 5361/5786; 93%). Patients with and without DM, regardless of the type of DM, presence of retinopathy, or HbA1c levels, were surgically treated for UNE to the same extent (258/667, 39% of patients with DM vs. 2131/5786, 37% of patients without DM). The proportion of surgically treated was significantly lower among patients diagnosed with UNE in primary care compared to secondary care (59/449, 13% vs. 2330/5786, 38%). Men were more often surgically treated than women (1228/3191, 38% vs.1161/3262 36%). Patients with UNE and DM are surgically treated to the same extent as patients with UNE but without DM and are more likely to be diagnosed in specialized care.
A privacy-preserving platform oriented medical healthcare and its application in identifying patients with candidemia
Authors: Yuan Siyi , Xu Song , Lu Xiao , Chen Xiangyu , Wang Yao , Bao Renyi , Sun Yunbo , Xiao Xiongjian , Su Longxiang , Long Yun , Li Linfeng , He Huaiwu 
Published: July 2024

AbstractFederated learning (FL) has emerged as a significant method for developing machine learning models across multiple devices without centralized data collection. Candidemia, a critical but rare disease in ICUs, poses challenges in early detection and treatment. The goal of this study is to develop a privacy-preserving federated learning framework for predicting candidemia in ICU patients. This approach aims to enhance the accuracy of antifungal drug prescriptions and patient outcomes. This study involved the creation of four predictive FL models for candidemia using data from ICU patients across three hospitals in China. The models were designed to prioritize patient privacy while aggregating learnings across different sites. A unique ensemble feature selection strategy was implemented, combining the strengths of XGBoost’s feature importance and statistical test p values. This strategy aimed to optimize the selection of relevant features for accurate predictions. The federated learning models demonstrated significant improvements over locally trained models, with a 9% increase in the area under the curve (AUC) and a 24% rise in true positive ratio (TPR). Notably, the FL models excelled in the combined TPR + TNR metric, which is critical for feature selection in candidemia prediction. The ensemble feature selection method proved more efficient than previous approaches, achieving comparable performance. The study successfully developed a set of federated learning models that significantly enhance the prediction of candidemia in ICU patients. By leveraging a novel feature selection method and maintaining patient privacy, the models provide a robust framework for improved clinical decision-making in the treatment of candidemia.
Hemodynamics of short-duration light-intensity physical exercise in the prefrontal cortex of children: a functional near-infrared spectroscopy study
Authors: Naito Takashi , Oka Koichiro , Ishii Kaori 
Published: July 2024

AbstractIdentifying the types of exercise that enhance cerebral blood flow is crucial for developing exercise programs that enhance cognitive function. Nevertheless, few studies have explored the amount of light-intensity, short-duration exercises that individuals can easily perform on cerebral blood flow, particularly in children. We examined the effects of these exercises on the hemodynamics of the prefrontal cortex (PFC) using functional near-infrared spectroscopy. Participants comprised 41 children (aged 12.1 ± 1.5 years, 37% female) who engaged in seven light-intensity exercises, with each movement performed in two patterns lasting 10 or 20 s. Changes in oxygenated hemoglobin (oxy-Hb) levels at rest and during exercise were compared using analysis of covariance, with sex and age as covariates. Significant increases in oxy-Hb were observed in multiple regions of the PFC during all forms of exercise (including dynamic and twist stretching [66.6%, 8/12 regions, η2 = 0.07–0.27], hand and finger movements [75.0%, 9/12 regions, η2 = 0.07–0.16], and balance exercises (100.0%, 6/6 regions, η2 = 0.13–0.25]), except for static stretching with monotonic movements. This study implies that short-duration, light-intensity exercises, provided that they entail a certain degree of cognitive and/or physical demands, can activate the PFC and increase blood flow.