bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting adverse events after thoracic endovascular aortic repair for patients with type B aortic dissection
Authors: Kang Mengyang , Li You , Zhang Yiman , Zhao Yang , Meng Yan , Zhang Junbo , Tian Hongyan 
Published: April 2024

AbstractThe potential of adverse events (AEs) after thoracic endovascular aortic repair (TEVAR) in patients with type B aortic dissection (TBAD) has been reported. To avoid the occurrence of AEs, it is important to recognize high-risk population for prevention in advance. The data of 261 patients with TBAD who received TEVAR between June 2017 and June 2021 at our medical center were retrospectively reviewed. After the implementation of exclusion criteria, 172 patients were finally included, and after 2.8 years (range from 1 day to 5.8 years) of follow up, they were divided into AEs (n = 41) and non-AEs (n = 131) groups. We identified the predictors of AEs, and a prediction model was constructed to calculate the specific risk of postoperative AEs at 1, 2, and 3 years, and to stratify patients into high-risk (n = 78) and low-risk (n = 94) group. The prediction model included seven predictors: Age > 75 years, Lower extremity malperfusion (LEM), NT-proBNP > 330 pg/ml, None distal tear, the ratio between the diameter of the ascending aorta and descending aorta (A/D ratio) > 1.2, the ratio of the area of the false lumen to the total aorta (FL ratio) > 64%, and acute TEVAR, which exhibited excellent predictive accuracy performance and discriminatory ability with C statistic of 82.3% (95% CI 77.3–89.2%). The prediction model was contributed to identify high-risk patients of postoperative AEs, which may serve to achievement of personalized treatment and follow-up plans for patients.
Depletion of proteasome subunit PSMD1 induces cancer cell death via protein ubiquitination and DNA damage, irrespective of p53 status
Authors: Kim Mi-Yeun , Park Eun-Ran , Cho Eung-Ho , Park Sun-Hoo , Han Chul Ju , Kim Sang-Bum , Gu Man Bock , Shin Hyun-Jin , Lee Kee-Ho 
Published: April 2024

AbstractHepatocellular carcinoma (HCC) is characterized by high incidence and fatality rates worldwide. In our exploration of prognostic factors in HCC, the 26s proteasome subunit, non-ATPase 1 (PSMD1) protein emerged as a significant contributor, demonstrating its potential as a therapeutic target in this aggressive cancer. PSMD1 is a subunit of the 19S regulatory particle in the 26S proteasome complex; the 19S particle controls the deubiquitination of ubiquitinated proteins, which are then degraded by the proteolytic activity of the complex. Proteasome-targeting in cancer therapy has received significant attention because of its practical application as an established anticancer agent. We investigated whether PSMD1 plays a critical role in cancer owing to its prognostic significance. PSMD1 depletion induced cell cycle arrest in G2/M phase, DNA damage and apoptosis of cancer cells, irrespective of the p53 status. PSMD1 depletion-mediated cell death was accompanied by an increase in overall protein ubiquitination. These phenotypes occurred exclusively in cancer cells, with no effects observed in normal cells. These findings indicate that PSMD1 depletion-mediated ubiquitination of cellular proteins induces cell cycle arrest and eventual death in cancer cells, emphasizing PSMD1 as a potential therapeutic target in HCC.
Automated imaging coupled with AI-powered analysis accelerates the assessment of plant resistance to Tetranychus urticae
Authors: Złotkowska Ewelina , Wlazło Anna , Kiełkiewicz Małgorzata , Misztal Krzysztof , Dziosa Paulina , Soja Krzysztof , Barczak-Brzyżek Anna , Filipecki Marcin 
Published: April 2024

AbstractThe two-spotted spider mite (TSSM), Tetranychus urticae, is among the most destructive piercing-sucking herbivores, infesting more than 1100 plant species, including numerous greenhouse and open-field crops of significant economic importance. Its prolific fecundity and short life cycle contribute to the development of resistance to pesticides. However, effective resistance loci in plants are still unknown. To advance research on plant-mite interactions and identify genes contributing to plant immunity against TSSM, efficient methods are required to screen large, genetically diverse populations. In this study, we propose an analytical pipeline utilizing high-resolution imaging of infested leaves and an artificial intelligence-based computer program, MITESPOTTER, for the precise analysis of plant susceptibility. Our system accurately identifies and quantifies eggs, feces and damaged areas on leaves without expert intervention. Evaluation of 14 TSSM-infested Arabidopsis thaliana ecotypes originating from diverse global locations revealed significant variations in symptom quantity and distribution across leaf surfaces. This analytical pipeline can be adapted to various pest and host species, facilitating diverse experiments with large specimen numbers, including screening mutagenized plant populations or phenotyping polymorphic plant populations for genetic association studies. We anticipate that such methods will expedite the identification of loci crucial for breeding TSSM-resistant plants.
Fingerprinting Mediterranean hurricanes using pre-event thermal drops in seawater temperature
Authors: Scardino Giovanni , Miglietta Mario Marcello , Kushabaha Alok , Casella Elisa , Rovere Alessio , Besio Giovanni , Borzì Alfio Marco , Cannata Andrea , Mazza Gianfranco , Sabato Gaetano , Scicchitano Giovanni 
Published: April 2024

AbstractExtreme atmospheric-marine events, known as medicanes (short for “Mediterranean hurricanes”), have affected the Mediterranean basin in recent years, resulting in extensive coastal flooding and storm surges, and have occasionally been responsible for several casualties. Considering that the development mechanism of these events is similar to tropical cyclones, it is plausible that these phenomena are strongly affected by sea surface temperatures (SSTs) during their development period (winter and autumn seasons). In this study, we compared satellite data and the numerical reanalysis of SSTs from 1969 to 2023 with in situ data from dataloggers installed at different depths off the coast of southeastern Sicily as well as from data available on Argo floats on the Mediterranean basin. A spectral analysis was performed using a continuous wavelet transform (CWT) for each SST time series to highlight the changes in SSTs prior to the occurrence of Mediterranean Hurricanes as well as the energy content of the various frequencies of the SST signal. The results revealed that decreases in SST occurred prior to the formation of each Mediterranean hurricane, and that this thermal drop phenomenon was not observed in intense extra-tropical systems. The spectral analyses revealed that high CWT coefficients representing high SST energy contents were observed before the occurrence of a Mediterranean hurricane. This information may provide a useful fingerprint for distinguishing Mediterranean hurricanes from common seasonal storms at the onset of these events.
Artificial light at night bans Chaoborus from vital epilimnetic waters
Authors: Ślusarczyk Mirosław , Bednarska Anna , Zebrowski Marcin Lukasz , Tałanda Joanna 
Published: April 2024

AbstractArtificial light at night (ALAN) is known to affect organisms in terrestrial ecosystems and adjacent litoral habitats. In the present study, we tested the effect of ALAN on the spatial distribution of organisms in open waters, using the insect larvae ofChaoborus flavicansas an example. During the dayC. flavicanstypically hide from visually hunting fish in deep, dark, anoxic waters. On safer nights, they forage in rich subsurface waters. Nighttime field tests revealed that light from an HPS street lamp mounted on a boat anchored in open water attracted planktivorous fish, but deterred planktonicChaoborusfrom rich but risky surface waters.Chaoborusdid not descend to the safest, anoxic hypolimnion, but remained in hypoxic mid-depth metalimnion, which does not appear to be a perfect refuge. Neither light gradient nor food distribution fully explained their mid-depth residence under ALAN conditions. A further laboratory test revealed a limited tolerance ofC. flavicansto anoxia. Half of the test larvae died after 38 h at 9 °C in anoxic conditions. The trade-off between predation risk and oxygen demand may explain whyChaoborusdid not hide in deep anoxic waters, but remained in the riskier metalimnion with residual oxygen under ALAN conditions.
Asthma prevalence among United States population insights from NHANES data analysis
Authors: Swed Sarya , Sawaf Bisher , Al-Obeidat Feras , Hafez Wael , Rakab Amine , Alibrahim Hidar , Nasif Mohamad Nour , Alghalyini Baraa , Zia Zaidi Abdul Rehman , Alshareef Lamees , Alqatati Fadel , Zamrath Zahir Fathima , Ahmed Ashraf I. , Alom Mulham , Sultan Anas , AlMahmoud Abdullah , Bakkour Agyad , Cherrez-Ojeda Ivan 
Published: April 2024

AbstractAsthma is a prevalent respiratory condition that poses a substantial burden on public health in the United States. Understanding its prevalence and associated risk factors is vital for informed policymaking and public health interventions. This study aims to examine asthma prevalence and identify major risk factors in the U.S. population. Our study utilized NHANES data between 1999 and 2020 to investigate asthma prevalence and associated risk factors within the U.S. population. We analyzed a dataset of 64,222 participants, excluding those under 20 years old. We performed binary regression analysis to examine the relationship of demographic and health related covariates with the prevalence of asthma. The study found that asthma affected 8.7% of the U.S. population. Gender emerged as a significant factor, with 36.0% of asthma patients being male and 64.0% female (p < 0.001). Individuals aged 60 and older having the highest asthma prevalence at 34.0%. Non-Hispanic whites had the highest prevalence at 46.4%, followed by non-hispanic blacks at 26.0%. In contrast, Mexican Americans and other hispanic individuals had lower rates, at 9.6% and 9.0%, respectively. Females were 1.76 times more likely to have asthma than males (p < 0.001). Obese individuals had a 1.74 times higher likelihood of current asthma compared to underweight individuals (p < 0.001). Notably, both Non-Hispanic Whites and Non-Hispanic Blacks showed higher odds of current asthma compared to Mexican Americans (with adjusted odds ratios of 2.084 and 2.096, respectively, p < 0.001). The research findings indicate that asthma is prevalent in 8.7% of the U.S. population. Our study highlights that individuals who are female, have low income, are obese, and smoke have the highest likelihood of being affected by asthma. Therefore, public health policies should prioritize addressing these risk factors in their preventive strategies.
Refining outcome prediction after traumatic brain injury with machine learning algorithms
Authors: Bark D. , Boman M. , Depreitere B. , Wright D. W. , Lewén A. , Enblad P. , Hånell A. , Rostami E. 
Published: April 2024

AbstractOutcome after traumatic brain injury (TBI) is typically assessed using the Glasgow outcome scale extended (GOSE) with levels from 1 (death) to 8 (upper good recovery). Outcome prediction has classically been dichotomized into either dead/alive or favorable/unfavorable outcome. Binary outcome prediction models limit the possibility of detecting subtle yet significant improvements. We set out to explore different machine learning methods with the purpose of mapping their predictions to the full 8 grade scale GOSE following TBI. The models were set up using the variables: age, GCS-motor score, pupillary reaction, and Marshall CT score. For model setup and internal validation, a total of 866 patients could be included. For external validation, a cohort of 369 patients were included from Leuven, Belgium, and a cohort of 573 patients from the US multi-center ProTECT III study. Our findings indicate that proportional odds logistic regression (POLR), random forest regression, and a neural network model achieved accuracy values of 0.3–0.35 when applied to internal data, compared to the random baseline which is 0.125 for eight categories. The models demonstrated satisfactory performance during external validation in the data from Leuven, however, their performance were not satisfactory when applied to the ProTECT III dataset.
Centella asiatica mitigates the detrimental effects of Bisphenol-A (BPA) on pancreatic islets
Authors: Banerjee Oly , Singh Siddhartha , Paul Tiyesh , Maji Bithin Kumar , Mukherjee Sandip 
Published: April 2024

AbstractBisphenol-A (BPA) is widely used in food packaging and household products, leading to daily human exposure and potential health risks including metabolic diseases like type 2 diabetes mellitus (T2DM). Understanding BPA's mechanisms and developing intervention strategies is urgent. Centella asiatica, a traditional herbal medicine containing pentacyclic triterpenoids, shows promise due to its antioxidant and anti-inflammatory properties, utilized for centuries in Ayurvedic therapy. We investigated the effect of Centella asiatica (CA) ethanol extract on BPA-induced pancreatic islet toxicity in male Swiss albino mice. BPA administration (10 and 100 μg/kg body weight, twice daily) for 21 days caused glucose homeostasis disturbances, insulin resistance, and islet dysfunction, which were partially mitigated by CA supplementation (200 and 400 mg/kg body weight). Additionally, heightened oxidative stress, elevated levels of proinflammatory cytokines, loss of mitochondrial membrane potential (MMP), abnormal cell cycle, and increased apoptosis were implicated in the detrimental impact of BPA on the endocrine pancreas which were effectively counteracted by CA supplementation. In summary, CA demonstrated a significant ability to mitigate BPA-induced apoptosis, modulate redox homeostasis, alleviate inflammation, preserve MMP, and regulate the cell cycle. As a result, CA emerged as a potent agent in neutralizing the diabetogenic effects of BPA to a considerable extent.
Factors affecting motivation for receiving a booster dose of the COVID-19 vaccine among Japanese university students and staff: a cross-sectional questionnaire survey
Authors: Uchida Sho , Uno Shunsuke , Kondo Masahiro , Uwamino Yoshifumi , Namkoong Ho , Nishimura Tomoyasu , Misawa Kana , Kashimura Shoko , Yamato Kei , Ishizaka Tamami , Nagashima Kengo , Kitagawa Yuko , Hasegawa Naoki 
Published: April 2024

AbstractUnderstanding the factors that influence people’s decisions regarding vaccination is essential to promote vaccination. We aimed to clarify the motivations for receiving booster vaccines. We conducted a paper-based questionnaire distributed during January–February 2022 involving students and faculty staff who received the first COVID-19 vaccination at the mass vaccination program during June–September 2021 at Keio University. A total of 1725 participants were enrolled, and all completed the survey. Among these, 64.9% reported a significant adverse event (AEs) affecting daily life after the second vaccine. “Fear of severe COVID-19 illness” (72.6%) was the most common reason for getting vaccinated, followed by “concern of infecting others” (68.4%) and “fear of COVID-19 infection itself” (68.3%). Television emerged as the most influential source of information (80%), followed by university information (50.2%) and social networking sites (42.8%). Multivariate analysis revealed “fear of severe COVID-19 illness”, “fear of COVID-19 infection itself”, and “trust in the efficacy and safety of the vaccines in general” were significantly correlated with willingness to receive paid vaccinations. The severity of AEs and source of information were not related to participants’ willingness to receive booster vaccinations. Participants with positive reasons for vaccination were more likely to accept a third dose.
Optimizing industrial transport with a connected automated vehicle demonstrator for assembly systems and end-of-line production
Authors: Curiel-Ramirez Luis A. , Adlon Tobias , Burggräf Peter , Ramirez-Mendoza Ricardo A. , Beyer Moritz , Gert Denny 
Published: April 2024

AbstractIn recent years, the automotive industry has witnessed significant progress in the development of automated driving technologies. The integration of advanced sensors and systems in vehicles has led to the emergence of various functionalities, such as driving assistance and autonomous driving. Applying these technologies on the assembly line can enhance the efficiency, safety, and speed of transportation, especially at end-of-line production. This work presents a connected automated vehicle (CAV) demonstrator for generating autonomous driving systems and services for the automotive industry. Our prototype electric vehicle is equipped with state-of-the-art sensors and systems for perception, localization, navigation, and control. We tested various algorithms and tools for transforming the vehicle into a self-driving platform, and the prototype was simulated and tested in an industrial environment as proof of concept for integration into assembly systems and end-of-line transport. Our results show the successful integration of self-driving vehicle platforms in the automotive industry, particularly in factory halls. We demonstrate the localization, navigation, and communication capabilities of our prototype in a demo area. This work anticipates a significant increase in efficiency and operating cost reduction in vehicle manufacturing, despite challenges such as current low traveling speeds and high equipment costs. Ongoing research aims to enhance safety for higher vehicle speeds, making it a more viable business case for manufacturers, considering the increasing standardization of automated driving equipment in cars. The main contribution of this paper lies in introducing the general concept architecture of the integration of automated driving functionalities in end-of-line assembly and production systems. Showing a case study of the effective development and implementation of such functionalities with a CAV demonstrator in a more standardized industrial operational design domain.
Spontaneous perspective-taking in real-time language comprehension: evidence from eye-movements and grain of coordination
Authors: Wei Yipu , Wan Yingjia , Tanenhaus Michael K. 
Published: April 2024

AbstractLinguistic communication requires interlocutors to consider differences in each other’s knowledge (perspective-taking). However, perspective-taking might either be spontaneous or strategic. We monitored listeners’ eye movements in a referential communication task. A virtual speaker gave temporally ambiguous instructions with scalar adjectives (“big” in “big cubic block”). Scalar adjectives assume a contrasting object (a small cubic block). We manipulated whether the contrasting object (a small triangle) for a competitor object (a big triangle) was in common ground (visible to both speaker and listener) or was occluded so it was in the listener’s privileged ground, in which case perspective-taking would allow earlier reference-resolution. We used a complex visual context with multiple objects, making strategic perspective-taking unlikely when all objects are in the listener’s referential domain. A turn-taking, puzzle-solving task manipulated whether participants could anticipate a more restricted referential domain. Pieces were either confined to a small area (requiring fine-grained coordination) or distributed across spatially distinct regions (requiring only coarse-grained coordination). Results strongly supported spontaneous perspective-taking: Although comprehension was less time-locked in the coarse-grained condition, participants in both conditions used perspective information to identify the target referent earlier when the competitor contrast was in privileged ground, even when participants believed instructions were computer-generated.
Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism
Authors: Erdős Balázs , O’Donovan Shauna D. , Adriaens Michiel E. , Gijbels Anouk , Trouwborst Inez , Jardon Kelly M. , Goossens Gijs H. , Afman Lydia A. , Blaak Ellen E. , van Riel Natal A. W. , Arts Ilja C. W. 
Published: April 2024

AbstractContinuous glucose monitoring (CGM) is a promising, minimally invasive alternative to plasma glucose measurements for calibrating physiology-based mathematical models of insulin-regulated glucose metabolism, reducing the reliance on in-clinic measurements. However, the use of CGM glucose, particularly in combination with insulin measurements, to develop personalized models of glucose regulation remains unexplored. Here, we simultaneously measured interstitial glucose concentrations using CGM as well as plasma glucose and insulin concentrations during an oral glucose tolerance test (OGTT) in individuals with overweight or obesity to calibrate personalized models of glucose-insulin dynamics. We compared the use of interstitial glucose with plasma glucose in model calibration, and evaluated the effects on model fit, identifiability, and model parameters’ association with clinically relevant metabolic indicators. Models calibrated on both plasma and interstitial glucose resulted in good model fit, and the parameter estimates associated with metabolic indicators such as insulin sensitivity measures in both cases. Moreover, practical identifiability of model parameters was improved in models estimated on CGM glucose compared to plasma glucose. Together these results suggest that CGM glucose may be considered as a minimally invasive alternative to plasma glucose measurements in model calibration to quantify the dynamics of glucose regulation.
Investigation into safflower injection as a prophylactic treatment for retinal vein occlusion in a rabbit model
Authors: Li Junling , Guo Zhenfeng , Wu Jianguo 
Published: April 2024

AbstractThe study aimed to assess the effect and mechanism of safflower injection in preventing retinal vein thrombosis in rabbits. Twenty healthy adult pigmented rabbits were randomly assigned to either the experimental group, receiving safflower injection, or the control group, receiving normal saline. After two weeks of treatment, blood samples were collected to analyze platelet adhesion and aggregation rates. Photodynamic therapy was applied to induce occlusion in the target retinal vein. Fundus photography and fluorescein angiography were recorded using a dynamic microscopic monitoring system, and laser speckle imaging was employed to assess blood flow in the affected vein. The experimental group exhibited significantly lower rates of platelet adhesion and aggregation compared to the control group. Following the induction of retinal vein occlusion, the experimental group showed a lower complete occlusion rate of the target retinal vein. Although initial blood flow in the target vein was similar between groups, the blood flow at 1, 3, and 5 min post-occlusion was significantly higher in the experimental group. Safflower injection delayed retinal vein thrombosis formation, preserved blood flow in the affected retinal area, and reduced platelet adhesion and aggregation. These effects facilitated vascular reperfusion within a limited timeframe.