bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

AbstractIn 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

AbstractClarifying 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

AbstractThe 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

AbstractThe 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

AbstractThis 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

AbstractThe 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

AbstractObservations 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

AbstractAs 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

AbstractEssential 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

AbstractCat 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

Abstract
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

AbstractVarious 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.
Polyketides with α-glucosidase inhibitory and neuroprotective activities from Aspergillus versicolor associated with Pedicularis sylvatica
Authors: Jiang Ting-Ting , Zhai Liang-Liang , Wang Zi-Jue , Wang Xin-Yu , Li Jian-Nan , Zhai Yi-Jie , Li Ding , Han Wen-Bo 
Published: April 2024

Eight α-glucosidase inhibitory and neuroprotective polyketides from Aspergillus versicolor were reported in this article.