bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction
Authors: Bors Sacha , Abler Daniel , Dietz Matthieu , Andrearczyk Vincent , Fageot Julien , Nicod-Lalonde Marie , Schaefer Niklaus , DeKemp Robert , Kamani Christel H. , Prior John O. , Depeursinge Adrien
Published: April 2024

Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myocardial Blood Flow (sMBF) or Myocardial Flow Reserve (MFR) constitutes the gold standard for prognosis assessment. We propose a systematic investigation of the value of Artificial Intelligence (AI) to leverage [$$^{82}$$

82

Rb] Silicon PhotoMultiplier (SiPM) PET MPI for MACE prediction. We establish a general pipeline for AI model validation to assess and compare the performance of global (i.e. average of the entire MPI signal), regional (17 segments), radiomics and Convolutional Neural Network (CNN) models leveraging various MPI signals on a dataset of 234 patients. Results showed that all regional AI models significantly outperformed the global model ($$p<0.001$$

p
<
0.001

), where the best AUC of 73.9% (CI 72.5–75.3) was obtained with a CNN model. A regional AI model based on MBF averages from 17 segments fed to a Logistic Regression (LR) constituted an excellent trade-off between model simplicity and performance, achieving an AUC of 73.4% (CI 72.3–74.7). A radiomics model based on intensity features revealed that the global average was the least important feature when compared to other aggregations of the MPI signal over the myocardium. We conclude that AI models can allow better personalized prognosis assessment for MACE.
A systems biology-based mathematical model demonstrates the potential anti-stress effectiveness of a multi-nutrient botanical formulation
Authors: Saxena Abha , Prabhudesai Kaushiki S. , Damle Aparna , Ramakrishnan Shyam , Durairaj Palaniyamma , Kalankariyan Sumathi , Vijayalakshmi A. B. , Venkatesh K. V.
Published: April 2024

Stress is an adaptive response to the stressors that adversely affects physiological and psychological health. Stress elicits HPA axis activation, resulting in cortisol release, ultimately contributing to oxidative, inflammatory, physiological and mental stress. Nutritional supplementations with antioxidant, anti-inflammatory, and stress-relieving properties are among widely preferred complementary approaches for the stress management. However, there is limited research on the potential combined impact of vitamins, minerals and natural ingredients on stress. In the present study, we have investigated the effect of a multi-nutrient botanical formulation, Nutrilite® Daily Plus, on clinical stress parameters. The stress-modulatory effects were quantified at population level using a customized sub-clinical inflammation mathematical model. The model suggested that combined intervention of botanical and micronutrients lead to significant decline in physical stress (75% decline), mental stress (70% decline), oxidative stress (55% decline) and inflammatory stress (75% decline) as evident from reduction in key stress parameters such as ROS, TNF-α, blood pressure, cortisol levels and PSS scores at both individual and population levels. Further, at the population level, the intervention relieved stress in 85% of individuals who moved towards a healthy state. The in silico studies strongly predicts the use of Gotukola based Nutrilite® Daily Plus as promising anti-stress formulation.
Evolutionarily conserved ovarian fluid proteins are responsible for extending egg viability in salmonid fish
Authors: Gueho Aurélie , Żarski Daniel , Rime Hélène , Guével Blandine , Com Emmanuelle , Lavigne Régis , Nguyen Thaovi , Montfort Jérôme , Pineau Charles , Bobe Julien
Published: April 2024

In contrast to most fishes, salmonids exhibit the unique ability to hold their eggs for several days after ovulation without significant loss of viability. During this period, eggs are held in the body cavity in a biological fluid, the coelomic fluid (CF) that is responsible for preserving egg viability. To identify CF proteins responsible for preserving egg viability, a proteomic comparison was performed using 3 salmonid species and 3 non-salmonid species to identify salmonid-specific highly abundant proteins. In parallel, rainbow trout CF fractions were purified and used in a biological test to estimate their egg viability preservation potential. The most biologically active CF fractions were then subjected to mass spectrometry analysis. We identified 50 proteins overabundant in salmonids and present in analytical fractions with high egg viability preservation potential. The identity of these proteins illuminates the biological processes participating in egg viability preservation. Among identified proteins of interest, the ovarian-specific expression and abundance in CF at ovulation of N-acetylneuraminic acid synthase a (Nansa) suggest a previously unsuspected role. We show that salmonid CF is a complex biological fluid containing a diversity of proteins related to immunity, calcium binding, lipid metabolism, proteolysis, extracellular matrix and sialic acid metabolic pathway that are collectively responsible for preserving egg viability.
Quantitative measurement and comparison of breakthroughs inside the gas diffusion layer using lattice Boltzmann method and computed tomography scan
Authors: Pourrahmani Hossein , Hosseini Milad , Moussaoui Hamza , Oveisi Emad , Siavashi Majid , Van Herle Jan
Published: April 2024

In Proton Exchange Membrane Fuel Cells (PEMFCs), the presence of residual water within the Gas Diffusion Layer (GDL) poses challenges during cold starts and accelerates degradation. A computational model based on the Lattice Boltzmann Method (LBM) was developed to consider the capillary pressure inside the PEMFC and to analyze the exact geometries of the GDLs, which were obtained using the Computed Tomography scan. The novelty of this study is to suggest a methodology to compare the quantitative water removal performance of the GDLs without long-term experimental testing. Two different samples of GDLs were considered, pristine and aged. The results of quantitative measurements revealed the amount of water columns (breakthroughs) inside each sample. Considering the volume of 12,250,000 µm3 for each sample, the pristine and the aged samples are prone to have 774,200 µm3 (6.32%) and 1,239,700 µm3 (10.12%) as water columns in their porous domain. Micro-structural properties such as connectivity, mean diameter, effective diffusivity, etc. were also compared to observe the impacts of aging on the properties of the GDL.
Palaeogenomic insights into the origins of early settlers on the island of Cyprus
Authors: Heraclides Alexandros , Aristodemou Aris , Georgiou Andrea N. , Antoniou Marios , Ilgner Elisabeth , Davranoglou Leonidas-Romanos
Published: April 2024

Archaeological evidence supports sporadic seafaring visits to the Eastern Mediterranean island of Cyprus by Epipaleolithic hunter-gatherers over 12,000 years ago, followed by permanent settlements during the early Neolithic. The geographical origins of these early seafarers have so far remained elusive. By systematically analysing all available genomes from the late Pleistocene to early Holocene Near East (c. 14,000–7000 cal BCE), we provide a comprehensive overview of the genetic landscape of the early Neolithic Fertile Crescent and Anatolia and infer the likely origins of three recently published genomes from Kissonerga-Mylouthkia (Cypriot Late Pre-Pottery Neolithic B, c. 7600–6800 cal BCE). These appear to derive roughly 80% of their ancestry from Aceramic Neolithic Central Anatolians residing in or near the Konya plain, and the remainder from a genetically basal Levantine population. Based on genome-wide weighted ancestry covariance analysis, we infer that this admixture event took place roughly between 14,000 and 10,000 BCE, coinciding with the transition from the Cypriot late Epipaleolithic to the Pre-Pottery Neolithic A (PPNA). Additionally, we identify strong genetic affinities between the examined Cypro-LPPNB individuals and later northwestern Anatolians and the earliest European Neolithic farmers. Our results inform archaeological evidence on prehistoric demographic processes in the Eastern Mediterranean, providing important insights into early seafaring, maritime connections, and insular settlement.
A GAN-BO-XGBoost model for high-quality patents identification
Authors: Wu Zengyuan , Zhao Jiali , Li Ying , Wang Zelin , He Bin , Chen Liang
Published: April 2024

The number of patents increases quickly, while more and more low-quality patents are emerging. It’s important to identify high-quality patents from massive data quickly and accurately for organizational R&D decision-making and patent layout. However, due to low percentage of high-quality patents, it is challenging to identify them efficiently. In order to solve above problem, we reconstruct the existing index system for identifying high-quality patents by adding 4 features from technological strength of patentees. Furthermore, we propose an improved model by integrating resampling technique and ensemble learning algorithm. First, generative adversarial networks (GAN) are used to expand minority samples. Second, Extreme Gradient Boosting algorithm (XGBoost) with Bayesian optimization (BO) is used to identify high-quality patents. For clarity, this model is called a GAN-BO-XGBoost model. To test the effectiveness of above model, we use patent data in field of lithography technology. Tenfold cross-validation is carried out to evaluate the performance between our proposed model and other models. The results show that GAN-BO-XGBoost model performs better and it’s more stable than other models.
Passing path predicts shooting outcome in football
Authors: Cao Shun
Published: April 2024

What determines the outcome of a shot (scored or unscored) in football (soccer)? Numerous studies have investigated various aspects of this question, including the skills and physical/mental state of the shooter or goalkeeper, the positional information of shots, as well as the attacking styles and defensive formations of the opposing team. However, a critical question has received limited attention: How does the passing path affect the outcome of a shot? In other words, does the path of the ball before shooting significantly influence the result when the same player takes two shots from the same location? This study aims to fill the gap in the literature by conducting qualitative studies using a dataset comprising 34,938 shots, along with corresponding passing paths from top-tier football leagues and international competitions such as the World Cup. Eighteen path features were extracted and applied to three different machine-learning models. The results indicate that the passing path, whether with or without the positional information of shots, can indeed predict shooting outcomes and reveal influential path features. Moreover, it suggests that taking quick actions to move the ball across areas with a high probability of scoring a goal can significantly increases the chance of a successful shot. Interestingly, certain path features that are commonly considered important for team performance, such as the distribution of passes among players and the overall path length, were found to be less significant for shooting outcomes. These findings enhance our understanding of the effective ball-passing and provide valuable insights into the critical factors for achieving successful shots in football games.
A SARS-CoV-2 outbreak investigation at a storage and distribution centre in England: an assessment of worker- and workplace-related risk factors
Authors: Raja Amber I. , Nicholls Gillian , Coldwell Matthew , van Veldhoven Karin , Sandys Vince , Atkinson Barry , Nicholls Ian , Spencer Antony , Graham Alice , Higgins Hannah , Atchison Christina , Keen Chris , Fletcher Tony , Pearce Neil , Brickley Elizabeth B. , Chen Yiqun
Published: April 2024

An outbreak of SARS-CoV-2 (1 March to 10 May 2021) with an attack rate of 26.5% among approximately 1150 workers at a storage and distribution centre in England prompted a multidisciplinary outbreak investigation (5 May to 6 August 2021), with the aim of better understanding worker- and workplace-related risk factors for viral transmission in the warehousing sector. Overall, environmental factors (e.g., ventilation, humidity and temperature) were assessed to be appropriate at the facility. Nevertheless, 39 (51.3%) surface samples from across the site tested positive for low/ very low levels of SARS-CoV-2 RNA (Ct value ≥ 32.0 for all). Among the study participants, of whom 35.6% were confirmed or suspected cases, 95.5% reported having received COVID-19 prevention training, 100.0% reported handwashing, and 80.0% reported use of face coverings at work. Notably, 43.9% and 19.0% reported working with a symptomatic and a positive contact respectively. Furthermore, 80.5% and 46.3% had concerns regarding reduction in their income and future unemployment, respectively, due to self-isolation. The findings of this study suggest that, in addition to targeted workplace infection control measures and tailored work area specific risk assessments, an enhanced and equitable sick leave policy may help limit presenteeism and viral transmission in large workplaces.
Phyco-synthesis of silver nanoparticles by environmentally safe approach and their applications
Authors: Choudhary Sunita , Kumawat Geetanjali , Khandelwal Manisha , Khangarot Rama Kanwar , Saharan Vinod , Nigam Subhasha , Harish
Published: April 2024

In recent years, there has been an increasing interest in the green synthesis of metallic nanoparticles, mostly because of the evident limitations associated with chemical and physical methods. Green synthesis, commonly referred to as "biogenic synthesis," is seen as an alternative approach to produce AgNPs (silver nanoparticles). The current work focuses on the use of Asterarcys sp. (microalga) for biological reduction of AgNO3 to produce AgNPs. The optimal parameters for the reduction of AgNPs were determined as molarity of 3 mM for AgNO3 and an incubation duration of 24 h at pH 9, using a 20:80 ratio of algal extract to AgNO3. The biosynthesized Ast-AgNPs were characterised using ultraviolet–visible spectroscopy (UV–Vis), zeta potential, scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), and high-resolution transmission electron microscopy (HR-TEM) with selected area electron diffraction (SAED) patterns. The nanoparticles exhibited their highest absorption in the UV–visible spectra at 425 nm. The X-ray diffraction (XRD) investigation indicated the presence of characteristic peaks at certain angles: 38.30° (1 1 1), 44.40° (2 0 0), 64.64° (2 2 0), and 77.59° (3 1 1) according to the JCPDS file No. 04-0783. Based on SEM and TEM, the Ast-AgNPs had an average size of 35 nm and 52 nm, respectively. The zeta potential was determined to be − 20.8 mV, indicating their stability. The highest antibacterial effectiveness is shown against Staphylococcus aureus, with a zone of inhibition of 25.66 ± 1.52 mm at 250 μL/mL conc. of Ast-AgNPs. Likewise, Ast-AgNPs significantly suppressed the growth of Fusarium sp. and Curvularia sp. by 78.22% and 85.05%, respectively, at 150 μL/mL conc. of Ast-AgNPs. In addition, the Ast-AgNPs exhibited significant photocatalytic activity in degrading methylene blue (MB), achieving an 88.59% degradation in 120 min, revealing multiple downstream applications of Ast-AgNPs.
A new prediction nomogram of non-sentinel lymph node metastasis in cT1-2 breast cancer patients with positive sentinel lymph nodes
Authors: Yang Liu , Zhao Xueyi , Yang Lixian , Chang Yan , Cao Congbo , Li Xiaolong , Wang Quanle , Song Zhenchuan
Published: April 2024

We aimed to analyze the risk factors and construct a new nomogram to predict non-sentinel lymph node (NSLN) metastasis for cT1-2 breast cancer patients with positivity after sentinel lymph node biopsy (SLNB). A total of 830 breast cancer patients who underwent surgery between 2016 and 2021 at multi-center were included in the retrospective analysis. Patients were divided into training (n = 410), internal validation (n = 298), and external validation cohorts (n = 122) based on periods and centers. A nomogram-based prediction model for the risk of NSLN metastasis was constructed by incorporating independent predictors of NSLN metastasis identified through univariate and multivariate logistic regression analyses in the training cohort and then validated by validation cohorts. The multivariate logistic regression analysis revealed that the number of positive sentinel lymph nodes (SLNs) (P < 0.001), the proportion of positive SLNs (P = 0.029), lymph-vascular invasion (P = 0.029), perineural invasion (P = 0.023), and estrogen receptor (ER) status (P = 0.034) were independent risk factors for NSLN metastasis. The area under the receiver operating characteristics curve (AUC) value of this model was 0.730 (95% CI 0.676–0.785) for the training, 0.701 (95% CI 0.630–0.773) for internal validation, and 0.813 (95% CI 0.734–0.891) for external validation cohorts. Decision curve analysis also showed that the model could be effectively applied in clinical practice. The proposed nomogram estimated the likelihood of positive NSLNs and assisted the surgeon in deciding whether to perform further axillary lymph node dissection (ALND) and avoid non-essential ALND as well as postoperative complications.
The southernmost Errina antarctica hydrocoral savannah in Patagonian waters
Authors: De la Torriente Ana , Espinoza-León Ingrid M. , Valenzuela-Lobos Lorena A. , Antolinez Ana , Serrano Alberto
Published: April 2024

Marine animal forest (MAF) are animal-dominated megabenthic communities that support high biodiversity levels and play key roles in ecosystem functioning. However, there is limited data available in Patagonian waters related to the presence of these vulnerable benthic communities. We report a monospecific MAF of Errina antartica in Angostura Tomms, which represents the southernmost known living MAF of this species. With coverages reaching up to 28.5% of the substrate from 1.23 m to, at least, 33 m depth is the shallowest stylasterid assemblage described worldwide to date. The size of the colonies ranged from 0.14 to 15.8 cm, with small colonies (< 10 cm) being the most abundant (99%). We hypothesize that this MAF might correspond to a recent colonization of a space, extending its distribution range towards shallower areas or it could be an assemblage formed at the limit of the species’ distribution in which the environmental conditions are not optimal for the major development of the colonies. Additionally, results showed that habitats structured by three-dimensional sessile invertebrate such as E. antarctica showed higher values of species richness and alpha diversity than non-biogenic habitats. Analyses were based on 297 photos taken at 22 different sites in the western Strait of Magellan, along vertical transects from 5 to 25 m depth. Our study highlights the importance of the benthic communities existing in Patagonian waters, evidencing the need to act actively to ensure their maintenance.
A multimodal approach to cross-lingual sentiment analysis with ensemble of transformer and LLM
Authors: Miah Md Saef Ullah , Kabir Md Mohsin , Sarwar Talha Bin , Safran Mejdl , Alfarhood Sultan , Mridha M. F.
Published: April 2024

Sentiment analysis is an essential task in natural language processing that involves identifying a text’s polarity, whether it expresses positive, negative, or neutral sentiments. With the growth of social media and the Internet, sentiment analysis has become increasingly important in various fields, such as marketing, politics, and customer service. However, sentiment analysis becomes challenging when dealing with foreign languages, particularly without labelled data for training models. In this study, we propose an ensemble model of transformers and a large language model (LLM) that leverages sentiment analysis of foreign languages by translating them into a base language, English. We used four languages, Arabic, Chinese, French, and Italian, and translated them using two neural machine translation models: LibreTranslate and Google Translate. Sentences were then analyzed for sentiment using an ensemble of pre-trained sentiment analysis models: Twitter-Roberta-Base-Sentiment-Latest, bert-base-multilingual-uncased-sentiment, and GPT-3, which is an LLM from OpenAI. Our experimental results showed that the accuracy of sentiment analysis on translated sentences was over 86% using the proposed model, indicating that foreign language sentiment analysis is possible through translation to English, and the proposed ensemble model works better than the independent pre-trained models and LLM.
Variable characteristics overlooked in human K-562 leukemia cell lines with a common signature
Authors: Kasai Fumio , Mizukoshi Kumiko , Nakamura Yukio
Published: April 2024

K-562 is a well-known in vitro cellular model that represents human leukemia cell lines. Although the K-562 cells have been extensively characterized, there are inconsistencies in the data across publications, showing the presence of multiple K-562 cell lines. This suggests that analyzing a single K-562 cell line is insufficient to provide reliable reference data. In this study, we compared three K-562 cell lines with different IDs (RCB0027, RCB1635, and RCB1897) to investigate the fundamental characteristics of K-562 cells. Amplifications of the BCR-ABL1 fusion gene and at 13q31 were detected in all three cell lines, whereas each genome exhibited distinctive features of sequence variants and loss of heterozygosity. This implies that each K-562 cell line can be characterized by common and unique features through a comparison of multiple K-562 cell lines. Variations in transcriptome profiles and hemoglobin synthesis were also observed among the three cell lines, indicating that they should be considered sublines that have diverged from the common ancestral K-562 despite no changes from the original cell name. This leads to unintentional differences in genotypes and/or phenotypes among cell lines that share the same name. These data show that characterizing a single K-562 cell line does not necessarily provide data that are applicable to other K-562 cells. In this context, it is essential to modify cell names in accordance with changes in characteristics during cell culture. Furthermore, our data could serve as a reference for evaluating other K-562 sublines, facilitating the discovery of new K-562 sublines with distinct characteristics. This approach results in the accumulation of K-562 sublines with diverged characteristics and expands the options available, which may help in selecting the most suitable K-562 subline for each experiment.
Increasing the efficiency of cone-beam CT based delta-radiomics using automated contours to predict radiotherapy-related toxicities in prostate cancer
Authors: Delgadillo Rodrigo , Deana Anthony M. , Ford John C. , Studenski Matthew T. , Padgett Kyle R. , Abramowitz Matthew C. , Pra Alan Dal , Spieler Benjamin O. , Dogan Nesrin
Published: April 2024

Extracting longitudinal image quantitative data, known as delta-radiomics, has the potential to capture changes in a patient’s anatomy throughout the course of radiation treatment for prostate cancer. Some of the major challenges of delta-radiomics studies are contouring the structures for individual fractions and accruing patients’ data in an efficient manner. The manual contouring process is often time consuming and would limit the efficiency of accruing larger sample sizes for future studies. The problem is amplified because the contours are often made by highly trained radiation oncologists with limited time to dedicate to research studies of this nature. This work compares the use of automated prostate contours generated using a deformable image-based algorithm to make predictive models of genitourinary and changes in total international prostate symptom score in comparison to manually contours for a cohort of fifty patients. Area under the curve of manual and automated models were compared using the Delong test. This study demonstrated that the delta-radiomics models were similar for both automated and manual delta-radiomics models.
Dysregulation of TCONS_00006091 contributes to the elevated risk of oral squamous cell carcinoma by upregulating SNAI1, IRS and HMGA2
Authors: Ma Danhua , Chen Jijun , Shi Yuyuan , Gao Hongyan , Wei Zhen , Fan Jiayan , Wang Liang
Published: April 2024

In this study, we aimed to study the role of TCONS_00006091 in the pathogenesis of oral squamous cellular carcinoma (OSCC) transformed from oral lichen planus (OLP). This study recruited 108 OSCC patients which transformed from OLP as the OSCC group and 102 OLP patients with no sign of OSCC as the Control group. ROC curves were plotted to measure the diagnostic values of TCONS_00006091, miR-153, miR-370 and let-7g, and the changes in gene expressions were measured by RT-qPCR. Sequence analysis and luciferase assays were performed to analyze the molecular relationships among these genes. Cell proliferation and apoptosis were observed via MTT and FCM. TCONS_00006091 exhibited a better diagnosis value for OSCC transformed from OLP. OSCC group showed increased TCONS_00006091 expression and decreased expressions of miR-153, miR-370 and let-7g. The levels of SNAI1, IRS and HMGA2 was all significantly increased in OSCC patients. And TCONS_00006091 was found to sponge miR-153, miR-370 and let-7g, while these miRNAs were respectively found to targe SNAI1, IRS and HMGA2. The elevated TCONS_00006091 suppressed the expressions of miR-153, miR-370 and let-7g, leading to the increased expression of SNAI1, IRS and HMGA2. Also, promoted cell proliferation and suppressed apoptosis were observed upon the over-expression of TCONS_00006091. This study demonstrated that the expressions of miR-153, miR-370 and let-7g were down-regulated by the highly expressed TCONS_00006091 in OSCC patients, which accordingly up-regulated the expressions of SNAI1, IRS and HMGA2, resulting in the promoted cell proliferation and suppressed cell apoptosis.
The factors affecting the performance of the tunnel wall drilling task and their priority
Authors: Gao Peng-Fei , Zhi Jin-Yi , Hu Ji-Dong , Wang Jin , Xu Yong-Sheng , Zou Rui , Ding Tie-Cheng , Yang Lin
Published: April 2024

Clarifying the relationship between the man–machine environment and its impact on the tunnel wall drilling task performance (TWDTP) is crucial for enhancing the task performance. Based on a questionnaire survey, indicators of the man–machine environment that affect the TWDTP were proposed in this study, and exploratory factor analysis and a structural equation model were employed to examine the potential factors influencing the task performance and their degrees of influence. By comparing the discrepancy between the perceived performance and importance, the satisfaction of potential factors was evaluated, and the priority order for optimizing these factors was determined by considering the degree of influence and dissatisfaction. The results of survey data analysis based on actual tunnel drilling operation scenarios indicated that tools had the greatest impact on the TWDTP, followed by the quality of the physical environment, while human factors had the least influence on the task performance. Convenient functional maintenance is the key to improving the TWDTP, along with enhancing the quality of the working environment. Once these main aspects are optimized, it is important to consider additional factors such as availability of spare tools, efficient personnel organization, man–tool matching, and safety and health assurance. This research approach provides significant guidance in understanding the relationships between the man–machine environmental factors affecting the performance of complex engineering tasks and identifying key influencing factors, thus providing essential insights for optimizing the TWDTP.
Air pollution, cardiorespiratory fitness and biomarkers of oxidative status and inflammation in the 4HAIE study
Authors: Cipryan Lukas , Litschmannova Martina , Barot Tomas , Dostal Tomas , Sindler Dominik , Kutac Petr , Jandacka Daniel , Hofmann Peter
Published: April 2024

The aim of this study was to investigate the associations between cardiorespiratory fitness (CRF), long-term air pollution exposure and biochemical markers of oxidative status and inflammation. This is a cross-sectional investigation focusing on biochemical markers of oxidative status and inflammation. Participants were Caucasian (N = 1188; age 18–65 years) who lived for at least 5 years in a high air-polluted (Moravian-Silesian; MS) or low air-polluted (South Bohemia; SB) region of the Czech Republic. Healthy runners and inactive individuals were recruited. A multiple regression analysis was used to explain the relationship between multiple independent variables (CRF, trunk fat mass, sex, socioeconomic status, and region (MS region vs. SB region) and dependent variables (oxidative status, inflammation). CRF, trunk fat mass, age and sex significantly predicted almost all selected markers of oxidative status and inflammation (except GSSG, GSH/GSSG and BDNF). Participants living in the MS region presented significantly higher GPx (by 3.1%) and lower BDNF values (by 4.5%). All other investigated biochemical markers were not significantly influenced by region. We did not find meaningful interactions between long-term air-pollution exposure versus markers of oxidative status and inflammation. However, we showed various significant interactions with sex, age, CRF and body composition. The significant association of living in the high air polluted MS region with the BDNF level warrants further attention.
A logistic-tent chaotic mapping Levenberg Marquardt algorithm for improving positioning accuracy of grinding robot
Authors: Liu Jian , Deng Yonghong , Liu Yulin , Chen Linlin , Hu Zhenzhen , Wei Peiyang , Li Zhibin
Published: April 2024

The precision of workpiece machining is critically influenced by the geometric errors in the kinematics of grind robots, which directly affect their absolute positioning accuracy. To tackle this challenge, this paper introduces a logistic-tent chaotic mapping Levenberg Marquardt algorithm designed to accurately identify and compensate for this geometric error. the approach begins with the construction of a forward kinematic model and an error model specific to the robot. Then the algorithm is adopted to identify and compensate for the geometric error. The method establishes a mapping interval around the initial candidate solutions derived from iterative applications of the Levenberg Marquardt algorithm. Within this interval, the logistic-tent chaotic mapping method generates a diverse set of candidate solutions. These candidates are evaluated based on their fitness values, with the optimal solution selected for subsequent iterations. Empirical compensation experiments have validated the proposed method's precision and effectiveness, demonstrating a 6% increase in compensation accuracy and a 47.68% improvement in efficiency compared to existing state-of-the-art approaches. This process not only minimizes the truncation error inherent in the Levenberg Marquardt algorithm but also significantly enhances solution efficiency. Moreover, simulation experiments on grind processes further validate the method's ability to significantly improve the quality of workpiece machining.
No bidirectional relationship between sleep phenotypes and risk of proliferative diabetic retinopathy: a two-sample Mendelian randomization study
Authors: Liu Huan , Li Lin , Zan Xiaoning , Wei Jing
Published: April 2024

This study aimed to investigate the probable existence of a causal relationship between sleep phenotypes and proliferative diabetic retinopathy (PDR). Single nucleotide polymorphisms associated with sleep phenotypes were selected as instrumental variables at the genome-wide significance threshold (P < 5 × 10−8). Inverse‐variance weighted was applied as the primary Mendelian randomization (MR) analysis method, and MR Egger regression, weighted median, simple mode, and weighted mode methods were used as complementary analysis methods to estimate the causal association between sleep phenotypes and PDR. Results indicated that genetically predicted sleep phenotypes had no causal effects on PDR risk after Bonferroni correction (P = 0.05/10) [Chronotype: P = 0.143; Daytime napping: P = 0.691; Daytime sleepiness: P = 0.473; Insomnia: P = 0.181; Long sleep duration: P = 0.671; Morning person:P = 0.113; Short sleep duration: P = 0.517; Obstructive sleep apnea: P = 0.091; Sleep duration: P = 0.216; and snoring: P = 0.014]. Meanwhile, there are no reverse causality for genetically predicted PDR on sleep phenotypes [Chronotype: P = 0.100; Daytime napping: P = 0.146; Daytime sleepiness: P = 0.469; Insomnia: P = 0.571; Long sleep duration: P = 0.779; Morning person: P = 0.040; Short sleep duration: P = 0.875; Obstructive sleep apnea: P = 0.628; Sleep duration: P = 0.896; and snoring: P = 0.047]. This study’s findings did not support the causal effect of between sleep phenotypes and PDR. Whereas, longitudinal studies can further verify results validation.
Heart patient health monitoring system using invasive and non-invasive measurement
Authors: Mastoi Qurat-ul-Ain , Alqahtani Ali , Almakdi Sultan , Sulaiman Adel , Rajab Adel , Shaikh Asadullah , Alqhtani Samar M.
Published: April 2024

The abnormal heart conduction, known as arrhythmia, can contribute to cardiac diseases that carry the risk of fatal consequences. Healthcare professionals typically use electrocardiogram (ECG) signals and certain preliminary tests to identify abnormal patterns in a patient’s cardiac activity. To assess the overall cardiac health condition, cardiac specialists monitor these activities separately. This procedure may be arduous and time-intensive, potentially impacting the patient’s well-being. This study automates and introduces a novel solution for predicting the cardiac health conditions, specifically identifying cardiac morbidity and arrhythmia in patients by using invasive and non-invasive measurements. The experimental analyses conducted in medical studies entail extremely sensitive data and any partial or biased diagnoses in this field are deemed unacceptable. Therefore, this research aims to introduce a new concept of determining the uncertainty level of machine learning algorithms using information entropy. To assess the effectiveness of machine learning algorithms information entropy can be considered as a unique performance evaluator of the machine learning algorithm which is not selected previously any studies within the realm of bio-computational research. This experiment was conducted on arrhythmia and heart disease datasets collected from Massachusetts Institute of Technology-Berth Israel Hospital-arrhythmia (DB-1) and Cleveland Heart Disease (DB-2), respectively. Our framework consists of four significant steps: 1) Data acquisition, 2) Feature preprocessing approach, 3) Implementation of learning algorithms, and 4) Information Entropy. The results demonstrate the average performance in terms of accuracy achieved by the classification algorithms: Neural Network (NN) achieved 99.74%, K-Nearest Neighbor (KNN) 98.98%, Support Vector Machine (SVM) 99.37%, Random Forest (RF) 99.76 % and Naïve Bayes (NB) 98.66% respectively. We believe that this study paves the way for further research, offering a framework for identifying cardiac health conditions through machine learning techniques.
Assessing observational constraints on future European climate in an out-of-sample framework
Authors: O’Reilly Christopher H. , Brunner Lukas , Qasmi Saïd , Nogherotto Rita , Ballinger Andrew P. , Booth Ben , Befort Daniel J. , Knutti Reto , Schurer Andrew P. , Ribes Aurélien , Weisheimer Antje , Coppola Erika , McSweeney Carol
Published: April 2024

Observations are increasingly used to constrain multi-model projections for future climate assessments. This study assesses the performance of five constraining methods, which have previously been applied to attempt to improve regional climate projections from CMIP5-era models. We employ an out-of-sample testing approach to assess the efficacy of these constraining methods when applied to “pseudo-observational” datasets to constrain future changes in the European climate. These pseudo-observations are taken from CMIP6 simulations, for which future changes were withheld and used for verification. The constrained projections are more accurate and broadly more reliable for regional temperature projections compared to the unconstrained projections, especially in the summer season, which was not clear prior to this study. However, the constraining methods do not improve regional precipitation projections. We also analysed the performance of multi-method projections by combining the constrained projections, which are found to be competitive with the best-performing individual methods and demonstrate improvements in reliability for some temperature projections. The performance of the multi-method projection highlights the potential of combining constraints for the development of constraining methods.
How will future climate change impact prescribed fire across the contiguous United States?
Authors: Jonko Alex , Oliveto Julia , Beaty Teresa , Atchley Adam , Battaglia Mike A. , Dickinson Matthew B. , Gallagher Michael R. , Gilbert Ash , Godwin Daniel , Kupfer John A. , Hiers J. Kevin , Hoffman Chad , North Malcolm , Restaino Joseph , Sieg Carolyn , Skowronski Nicholas
Published: April 2024

As of 2023, the use of prescribed fire to manage ecosystems accounts for more than 50% of area burned annually across the United States. Prescribed fire is carried out when meteorological conditions, including temperature, humidity, and wind speed are appropriate for its safe and effective application. However, changes in these meteorological variables associated with future climate change may impact future opportunities to conduct prescribed fire. In this study, we combine climate projections with information on prescribed burning windows for ecoregions across the contiguous United States (CONUS) to compute the number of days when meteorological conditions allow for the safe and effective application of prescribed fire under present-day (2006–2015) and future climate (2051–2060) conditions. The resulting projections, which cover 57% of all vegetated area across the CONUS, indicate fewer days with conditions suitable for prescribed burning across ecoregions of the eastern United States due to rising maximum daily temperatures, but opportunities increase in the northern and northwestern United States, driven primarily by rising minimum temperatures and declining wind speeds.
GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis
Authors: Skuladottir Astros Th. , Stefansdottir Lilja , Halldorsson Gisli H. , Stefansson Olafur A. , Bjornsdottir Anna , Jonsson Palmi , Palmadottir Vala , Thorgeirsson Thorgeir E. , Walters G. Bragi , Gisladottir Rosa S. , Bjornsdottir Gyda , Jonsdottir Gudrun A. , Sulem Patrick , Gudbjartsson Daniel F. , Knowlton Kirk U. , Jones David A. , Ottas Aigar ,   Estonian Biobank, Esko Tõnu , Mägi Reedik , Nelis Mari , Hudjashov Georgi , Pedersen Ole B. , Didriksen Maria , Brunak Søren , Banasik Karina , Hansen Thomas Folkmann , Erikstrup Christian ,   DBDS Genomic Consortium, Bay Jakob , Boldsen Jens Kjærgaard , Brodersen Thorsten , Burgdorf Kristoffer , Chalmer Mona Ameri , Dinh Khoa Manh , Dowsett Joseph , Feenstra Bjarke , Geller Frank , Gudbjartsson Daniel , Hindhede Lotte , Hjalgrim Henrik , Jacobsen Rikke Louise , Jemec Gregor , Jensen Bitten Aagaard , Kaspersen Katrine , Kjerulff Bertram Dalskov , Kogelman Lisette , Larsen Margit Anita Hørup , Louloudis Ioannis , Lundgaard Agnete , Mikkelsen Susan , Mikkelsen Christina , Nissen Ioanna , Nyegaard Mette , Pedersen Ole Birger , Henriksen Alexander Pil , Rohde Palle Duun , Rostgaard Klaus , Schwinn Michael , Stefánsson Hreinn , Sørensen Erik , Þorsteinsdóttir Unnur , Thørner Lise Wegner , Bruun Mie Topholm , Ullum Henrik , Werge Thomas , Westergaard David , Haavik Jan , Andreassen Ole A. , Rye David , Igland Jannicke , Ostrowski Sisse Rye , Milani Lili A. , Nadauld Lincoln D. , Stefansson Hreinn , Stefansson Kari
Published: April 2024

Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1. CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1, encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson’s disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.
Method to deterministically generate large-amplitude optical cat states
Authors: Li Zheng-Hong , Yu Fei , Li Zhen-Ya , Al-Amri M. , Zubairy M. Suhail
Published: April 2024

Cat states, as an important resource in the study of macroscopic quantum superposition and quantum information applications, have garnered widespread attention. To date, preparing large-sized optical cat states has remained challenging. We demonstrate that, by utilizing interaction-free measurement and the quantum Zeno effect, even a fragile quantum microscopic system can deterministically control and become entangled with strong light fields, thereby generating large-amplitude optical cat states. During the entire preparation process, our method ensures that the microscopic system functions within a weak field environment, so that its quantum property can be protected. Furthermore, we show that the preparation of cat states is possible even when the quantum microsystem suffers from significant photon loss, provided that optical losses from classical devices are kept low, which implies that the fidelity of the cat state can be enhanced by improvements to and the perfection of the classical optical system.
New insights into macrophage polarization and its prognostic role in patients with colorectal cancer liver metastasis
Authors: Khanduri Isha , Maki Harufumi , Verma Anuj , Katkhuda Riham , Anandappa Gayathri , Pandurengan Renganayaki , Zhang Shanyu , Mejia Alicia , Tong Zhimin , Solis Soto Luisa M. , Jadhav Akshaya , Wistuba Ignacio I. , Menter David , Kopetz Scott , Parra Edwin R. , Vauthey Jean-Nicolas , Maru Dipen M.
Published: April 2024

Background

As liver metastasis is the most common cause of mortality in patients with colorectal cancer, studying colorectal cancer liver metastasis (CLM) microenvironment is essential for improved understanding of tumor biology and to identify novel therapeutic targets.

Methods

We used a multiplex immunofluorescence platform to study tumor associated macrophage (TAM) polarization and adaptive T cell subtypes in tumor samples from 105 CLM patients (49 without and 56 with preoperative chemotherapy).

Results

CLM exhibited M2 macrophage polarization, and helper T cells were the prevalent adaptive T cell subtype. The density of total, M2 and TGFβ-expressing macrophages, and regulatory T cells was lower in CLM treated with preoperative chemotherapy. CLM with right-sided primary demonstrated enrichment of TGFβ-expressing macrophages, and with left-sided primary had higher densities of helper and cytotoxic T cells. In multivariate analysis, high density of M2 macrophages correlated with longer recurrence-free survival (RFS) in the entire cohort [hazard ratio (HR) 0.425, 95% CI 0.219–0.825, p = 0.011) and in patients without preoperative chemotherapy (HR 0.45, 95% CI 0.221–0.932, p = 0.032). High pSMAD3-expressing macrophages were associated with shorter RFS in CLM after preoperative chemotherapy.

Conclusions

Our results highlight the significance of a multi-marker approach to define the macrophage subtypes and identify M2 macrophages as a predictor of favorable prognosis in CLM.
IL-6 promotes tumor growth through immune evasion but is dispensable for cachexia
Authors: Kwon Young-Yon , Hui Sheng
Published: April 2024

Various cytokines have been implicated in cancer cachexia. One such cytokine is IL-6, deemed as a key cachectic factor in mice inoculated with colon carcinoma 26 (C26) cells, a widely used cancer cachexia model. Here we tested the causal role of IL-6 in cancer cachexia by knocking out the IL-6 gene in C26 cells. We found that the growth of IL-6 KO tumors was dramatically delayed. More strikingly, while IL-6 KO tumors eventually reached the similar size as wild-type tumors, cachexia still took place, despite no elevation in circulating IL-6. In addition, the knockout of leukemia inhibitory factor (LIF), another IL-6 family cytokine proposed as a cachectic factor in the model, also affected tumor growth but not cachexia. We further showed an increase in the infiltration of immune cell population in the IL-6 KO tumors compared with wild-type controls and the defective IL-6 KO tumor growth was rescued in immunodeficient mice while cachexia was not. Thus, IL-6 promotes tumor growth by facilitating immune evasion but is dispensable for cachexia.
Multi-angle tracking synthetic kinetics of phase evolution in Li-rich Mn-based cathodes
Authors: Xu Shenyang , Chen Zhefeng , Zhao Wenguang , Ren Wenju , Hou Chenxin , Liu Jiajie , Wang Wu , Yin Chong , Tan Xinghua , Lou Xiaobing , Yao Xiangming , Gao Zhihai , Liu Hao , Wang Lu , Yin Zuwei , Qiu Bao , Hu Bingwen , Li Tianyi , Dong Cheng , Pan Feng , Zhang Mingjian
Published: April 2024

This study investigates the two-phase fusion in Li-rich Mn-based cathodes, revealing the process from two-phase formation to solid solution, and optimizes performance by controlling the fusion extent in lithium and sodium cathode materials.
Soil-mimetic eco-friendly fertilizer gates: nanoclay-reinforced binary carbohydrates for improving crop efficiency
Authors: Sahu Bandana Kumari , Swami Kanchan , Kapoor Neelesh , Agrawal Ankit , Kataria Sarita , Sharma Parul , Kundu Priya , Thangavel Hema , Vattakkuniyil Anusree , Chaurasia Om Prakash , Shanmugam Vijayakumar
Published: April 2024

Controlled release of potassium from CS_NC_L coated MOP pellets through a revolving gate for crop production efficiency.
Engineering peptide-modified alginate-based bioinks with cell-adhesive properties for biofabrication
Authors: Karakaya Emine , Gleichauf Luisa , Schöbel Lisa , Hassan Ahmed , Soufivand Anahita Ahmadi , Tessmar Joerg , Budday Silvia , Boccaccini Aldo R. , Detsch Rainer
Published: April 2024

Alginate-based bioinks used for DoD approaches can be modified with specific peptide-containing components so that incorporated printed cells show significantly higher cell elongation ratios after 7 days (created with https://www.BioRender.com).
Self-degrading functional unit introduction for anti-oxidation ability enhancement of a poly(vinyl ethylene carbonate) electrolyte
Authors: Lin Zhiyuan , Chen Fang , Yin Xin , Ding Peipei , Xia Yonggao , Guo Xianwei , Yu Haijun
Published: April 2024

A novel poly(vinyl ethylene carbonate-3-sulfolene) electrolyte has been developed by copolymerizing monomer precursors, which has a wide electrochemical stability window of 5 V (vs. Li+/Li) attributed to the pre-degradation of sulfolene-based functional units.