bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehending Cardiac Dysfunction by Oxidative Stress: Untargeted Metabolomics of In Vitro Samples
Authors: Amaral Alan Gonçalves , Moretto Isabela Aparecida , Zandonadi Flávia da Silva , Zamora-Obando Hans Rolando , Rocha Isabela , Sussulini Alessandra , Thomaz André Alexandre de , Oliveira Regina Vincenzi , Santos Aline Mara dos , Simionato Ana Valéria Colnaghi 
Published: April 2022

Cardiovascular diseases (CVDs) are noncommunicable diseases known for their complex etiology and high mortality rate. Oxidative stress (OS), a condition in which the release of free radical exceeds endogenous antioxidant capacity, is pivotal in CVC, such as myocardial infarction, ischemia/reperfusion, and heart failure. Due to the lack of information about the implications of OS on cardiovascular conditions, several methodologies have been applied to investigate the causes and consequences, and to find new ways of diagnosis and treatment as well. In the present study, cardiac dysfunction was evaluated by analyzing cells’ alterations with untargeted metabolomics, after simulation of an oxidative stress condition using hydrogen peroxide (H2O2) in H9c2 myocytes. Optimizations of H2O2 concentration, cell exposure, and cell recovery times were performed through MTT assays. Intracellular metabolites were analyzed right after the oxidative stress (oxidative stress group) and after 48 h of cell recovery (recovery group) by ultra-high-performance liquid chromatography coupled to mass spectrometry (UHPLC-MS) in positive and negative ESI ionization mode. Significant alterations were found in pathways such as “alanine, aspartate and glutamate metabolism”, “glycolysis”, and “glutathione metabolism”, mostly with increased metabolites (upregulated). Furthermore, our results indicated that the LC-MS method is effective for studying metabolism in cardiomyocytes and generated excellent fit (R2Y &gt; 0.987) and predictability (Q2 &gt; 0.84) values.
Colorimetric and Fluorescence Dual-Mode Biosensors Based on Peroxidase-Like Activity of the Co3O4 Nanosheets
Authors: Tan Jingying , Geng Weifu , Li Junde , Wang Zhen , Zhu Shaohao , Wang Xiuzhong 
Published: April 2022

The mimic enzyme has become a research hotspot in recent years because of its advantages of high stability, convenient preparation, and low price. In this article, Co3O4 nanosheets synthesized by a simple hydrothermal method possess the characteristics of a peroxidase-like activity. The results demonstrated that 3,3′,5,5′-Tetramethylbenzidine (TMB) could be oxidized by H2O2 to produce a typical blue product (oxTMB) which has a strong absorption at 650 nm wavelength with the help of the Co3O4 nanosheets. Thus, a simple and sensitive colorimetric detection method for H2O2 was established with a good linear relationship (2–200 μM) and a low limit of detection (0.4 μM). Meanwhile, the colorimetric product can effectively quench the fluorescence emitted by Ru(bpy)32+. Therefore, a colorimetric and fluorescence dual detection mode photochemical sensor for H2O2 detection is constructed based on the principle of the inner filter effect (IFE) between the colorimetric product (oxTMB) and Ru(bpy)32+. It can effectively avoid the false positive problem of a single detection mode. In the presence of glucose oxidase, glucose can be catalyzed to produce gluconic acid and H2O2; therefore, the sensor can also be used for the determination of glucose with a good linear relationship (0.02–2 μM) and a low limit of detection (5 nM). Experimental results showed that the sensor has a high sensitivity and strong anti-interference ability which can be used for the detection of actual samples.
Remote Conditioning by Rhythmic Compression of Limbs Ameliorated Myocardial Infarction by Downregulation of Inflammation via A2 Adenosine Receptors
Authors: Xu Senlei , Gu Renjun , Bian Xiangyu , Xu Xin , Xia Xuefeng , Liu Yuchen , Jia Chengjie , Gu Yihuang , Zhang Hongru 
Published: April 2022

BackgroundRemote ischemic conditioning (RIC) is a cardioprotective phenomenon, yet transient ischemia is not a requisite trigger for remote cardioprotection. In fact, RIC is a stimulus compound containing interruption of the blood vessel and tissue compression. In this study, we evaluate the effects of remote tissue compression on infarct size after myocardial infarction and explore its preliminary mechanisms.Methods and ResultsWe used a murine model of myocardial infarction to assess ischemia injury and identified remote conditioning by rhythmic compression on forelimb as a novel cardioprotective intervention. We show that the cardioprotective signal transduction of remote conditioning from the trigger limb to the heart involves the release of adenosine. Our results demonstrate that A2a and A2b receptors are indispensable parts for cardioprotection of remote conditioning, which is linked to its anti-inflammatory properties by the subsequent activation of cAMP/PKA/NF-κB axis.ConclusionOur results establish a new connection between remote tissue compression and cardiovascular diseases, which enhances our cognition about the role of tissue compression on RIC cardioprotection.
Long-Term Effect of β-Blocker Use on Clinical Outcomes in Postmyocardial Infarction Patients: A Systematic Review and Meta-Analysis
Authors: Liang Chunling , Zhang Chenhao , Gan Shibao , Chen Xiaojie , Tan Zhihui 
Published: April 2022

BackgroundPrior studies provided inconsistent results regarding long-term effect of β-blocker use on clinical outcomes in postmyocardial infarction (MI) patients.MethodsWe searched for articles regarding long-term effect of β-blocker use on clinical outcomes in patients after MI and published them before July 2021 in the databases as follows: PubMed, Web of Science, MEDLINE, EMBASE, and Google Scholar. STATA 12.0 software was used to compute hazard ratios (HRs) and their 95% confidence intervals (CIs).ResultsThe study indicated that β-blocker group had significantly lower long-term all-cause mortality, cardiovascular mortality, major adverse cardiac events (MACEs) in post-MI patients, compared to no β-blocker group (all-cause mortality: HR, 0.67; 95% CI: 0.56–0.80; cardiovascular mortality: HR, 0.62; 95% CI: 0.49–0.78; MACE: HR, 0.87; 95% CI: 0.75–1.00). The study indicated no significant long-term effect of β-blocker use on risk of hospitalization for heart failure (HF), risk of recurrent MI, risk of stroke, and risk of repeat revascularization in post-MI patients (risk of hospitalization for HF: HR, 0.82; 95% CI: 0.58–1.16; risk of recurrent MI: HR, 0.93; 95% CI: 0.78–1.11; risk of stroke: HR, 0.94; 95% CI: 0.79–1.12; risk of repeat revascularization: HR, 0.91; 95% CI: 0.80–1.04).ConclusionsThe meta-analysis demonstrated significant long-term effects of β-blocker use on all-cause mortality, cardiovascular mortality, and risk of MACE in post-MI patients, whereas no significant long-term effect was shown on risk of hospitalization for HF, risk of recurrent MI, risk of stroke, and risk of repeat revascularization in post-MI patients.
Sex-Dependent Performance of the Neutrophil-to-Lymphocyte, Monocyte-to-Lymphocyte, Platelet-to-Lymphocyte and Mean Platelet Volume-to-Platelet Ratios in Discriminating COVID-19 Severity
Authors: Fors Martha , Ballaz Santiago , Ramírez Hegira , Mora Francisco X. , Pulgar-Sánchez Mary , Chamorro Kevin , Fernández-Moreira Esteban 
Published: April 2022

BackgroundThe neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and mean platelet volume-to-platelet ratio (MPR) are combined hematology tests that predict COVID-19 severity, although with different cut-off values. Because sex significantly impacts immune responses and the course of COVID-19, the ratios could be biased by sex.PurposeThis study aims to evaluate sex-dependent differences in the contribution of NLR, PLR, MLR, and MPR to COVID-19 severity and mortality upon hospital admission using a sample of pneumonia patients with SARS-CoV-2 infection.MethodsThis single-center observational cross-sectional study included 3,280 confirmed COVID-19 cases (CDC 2019-Novel Coronavirus real-time RT-PCR Diagnostic) from Quito (Ecuador). The receiver operating characteristic (ROC) curve analysis was conducted to identify optimal cut-offs of the above parameters when discriminating severe COVID-19 pneumonia and mortality risks after segregation by sex. Severe COVID-19 pneumonia was defined as having PaO2 &lt; 60 mmHg and SpO2 &lt; 94%, whereas non-severe COVID-19 pneumonia was defined as having PaO2 ≥ 60 mmHg and SpO2 ≥ 94%.ResultsThe mortality rate of COVID-19 among men was double that in women. Severe COVID-19 pneumonia and non-surviving patients had a higher level of NLR, MLR, PLR, and MPR. The medians of NLR, MLR, and MPR in men were significantly higher, but PLR was not different between men and women. In men, these ratios had lower cut-offs than in women (NLR: 2.42 vs. 3.31, MLR: 0.24 vs. 0.35, and PLR: 83.9 vs. 151.9). The sensitivity of NLR, MLR, and PLR to predict pneumonia severity was better in men (69–77%), whereas their specificity was enhanced in women compared to men (70–76% vs. 23–48%).ConclusionThese ratios may represent widely available biomarkers in COVID-19 since they were significant predictors for disease severity and mortality although with different performances in men and women.
Machine Learning Analyzed Weather Conditions as an Effective Means in the Predicting of Acute Coronary Syndrome Prevalence
Authors: Wlodarczyk Aleksandra , Molek Patrycja , Bochenek Bogdan , Wypych Agnieszka , Nessler Jadwiga , Zalewski Jaroslaw 
Published: April 2022

BackgroundThe prediction of the number of acute coronary syndromes (ACSs) based on the weather conditions in the individual climate zones is not effective. We sought to investigate whether an artificial intelligence system might be useful in this prediction.MethodsBetween 2008 and 2018, a total of 105,934 patients with ACS were hospitalized in Lesser Poland Province, one covered by two meteorological stations. The predicted daily number of ACS has been estimated with the Random Forest machine learning system based on air temperature (°C), air pressure (hPa), dew point temperature (Td) (°C), relative humidity (RH) (%), wind speed (m/s), and precipitation (mm) and their daily extremes and ranges derived from the day of ACS and from 6 days before ACS.ResultsOf 840 pairwise comparisons between individual weather parameters and the number of ACS, 128 (15.2%) were significant but weak with the correlation coefficients ranged from −0.16 to 0.16. None of weather parameters correlated with the number of ACS in all the seasons and stations. The number of ACS was higher in warm front days vs. days without any front [40 (29–50) vs. 38 (27–48), respectively, P &lt; 0.05]. The correlation between the predicted and observed daily number of ACS derived from machine learning was 0.82 with 95% CI of 0.80–0.84 (P &lt; 0.001). The greatest importance for machine learning (range 0–1.0) among the parameters reached Td daily range with 1.00, pressure daily range with 0.875, pressure maximum daily range with 0.864, and RH maximum daily range with 0.853, whereas among the clinical parameters reached hypertension daily range with 1.00 and diabetes mellitus daily range with 0.28. For individual seasons and meteorological stations, the correlations between the predicted and observed number of ACS have ranged for spring from 0.73 to 0.77 (95% CI 0.68–0.82), for summer from 0.72 to 0.76 (95% CI 0.66–0.81), for autumn from 0.72 to 0.83 (95% CI 0.67–0.87), and for winter from 0.76 to 0.79 (95% CI 0.71–0.83) (P &lt; 0.001 for each).ConclusionThe weather parameters have proven useful in predicting the prevalence of ACS in a temperate climate zone for all the seasons, if analyzed with an artificial intelligence system. Simultaneously, the analysis of individual weather parameters or frontal scenarios has provided only weak univariate relationships. These findings will require validation in other climatic zones.
Flow Path of the Carbonate Geothermal Water in Xiong’an New Area, North China: Constraints From 14C Dating and H-O Isotopes
Authors: Zhang Baojian , Wang Siqi , Kang Fengxin , Li Yanyan , Zhuo Linyang , Gao Jun , Yuan Wenzhen , Xing Yifei 
Published: April 2022

Studying the flow path of geothermal water in geothermal fields is an important basis for the scientific development and management of geothermal resources. However, due to the influence of engineering volume, economic benefits and demand, it is very difficult to fully grasp the flow path of deep geothermal water in large areas. The use of hydrogeochemical tracers to determine the flow path of geothermal water is a scientific and effective research method. In order to accurately describe the flow path of carbonate geothermal water in the Xiong’an New Area and its surrounding areas, this study systematically analyzed the 14C, 18O, and 2H data of carbonate and Cenozoic sandstone geothermal water, Quaternary groundwater, as well as mountain spring water of the study area. Based on these results, we can conclude that 1) The 14C, d, and 18O values are favourable clues for indicating the circulating runoff conditions and runoff paths of geothermal water. 2) The salinity of the Xushui-Wenan and Lilan transfer zone are &lt;3 g/l, the 14C values are lower than 25000 years, the d value is higher, and the phenomenon of “18O drift” is weak, all these indicating the dominant flow path of carbonate geothermal water, featured by relative lower temperature. 3) The salinity of karst geothermal water in the southwest of Gaoyang low uplift, Rongcheng uplift and Niutuozhen uplift is &gt; 3 g/l, the 14C values are higher than 40,000 years, the d value is lower, and the phenomenon of “18O drift” is obvious, all these indicating that the tectonic sites are the convergence areas of regional karst geothermal water, featured by relative high temperature. 4) The hydrochemical indicators combined with previous carbonate groundwater flow field indicate that the recharge of carbonate geothermal water in the Xiong’an New Area may not only drive from the western Taihang Mountains, but also along the Xushui-Wenan transfer zone and the Lilan fault, with the recharge of carbonate groundwater from the Cangxian uplift from east to west. By further identifying and defining the dominant flow path and supply direction of carbonate geothermal water in the Xiong’an New Area and surrounding areas, it provides strong support for the scientific development of regional carbonate geothermal water.
Detecting Geothermal Resources in a Plateau Area: Constraints From Land Surface Temperature Characteristics Using Landsat 8 Data
Authors: Dong Ben , Dong Shuyi , Wang Yingchun , Wen Fayang , Yu Chunmei , Zhou Jinlin , Song Rongcai 
Published: April 2022

Geothermal energy is a kind of clean energy, which attracts more attention. The detection of geothermal resources is inseparable from regional geothermal prospects. Land surface temperature (LST) is an indispensable parameter for geothermal exploration, but the retrieval accuracy of LST for complex and remote areas is currently a major challenge. In this article, based on Landsat 8 remote sensing data, the characteristics of surface temperature retrieval methods are systematically reviewed, and the differences among these three algorithms are researched by using them to detect the surface temperature in the study area, which is Kangding County, Sichuan Province, China. Then the experimental results of the three algorithms are verified by using long-time (more than 1 year) measured data from the two monitoring sites, and the monitoring sites are situated in Zhonggu and Lao Yulin area of Kangding County. The results show that the radiative transfer equation (RTE) has the highest accuracy, and the mean error is 0.372°C; mono-window algorithm (MW) has a mean error of −0.606°C; and the split-window (SW) algorithm has the lowest accuracy, with a mean error of −2.07°C. The experimental results were used to select an algorithm with relatively high accuracy and low sensitivity. At the same time, a time series was used to perform temperature retrieval for this study area from November 2016 to December 2017 to evaluate the applicability of the method. The result shows that the RTE has the highest accuracy in mid-winter and a relatively low accuracy in summer in Kangding County. The purpose of this article is to establish a suitable method for high-precision surface temperature retrieval in plateau areas and to provide technical support for exploring geothermal resources or evaluating geothermal potential in these areas.
Prevalence of Clinically Relevant Germline BRCA Variants in a Large Unselected South African Breast and Ovarian Cancer Cohort: A Public Sector Experience
Authors: Van der Merwe Nerina C. , Combrink Herkulaas MvE , Ntaita Kholiwe S. , Oosthuizen Jaco 
Published: April 2022

Breast cancer is a multifaceted disease that currently represents a leading cause of death in women worldwide. Over the past two decades (1998–2020), the National Health Laboratory Service’s Human Genetics Laboratory in central South Africa screened more than 2,974 breast and/or ovarian cancer patients for abnormalities characteristic of the widely known familial breast cancer genes, Breast Cancer gene 1 (BRCA1) and Breast Cancer gene 2 (BRCA2). Patients were stratified according to the presence of family history, age at onset, stage of the disease, ethnicity and mutation status relative to BRCA1/2. Collectively, 481 actionable (likely-to pathogenic) variants were detected in this cohort among the different ethnic/racial groups. A combination of old (pre-2014) and new (post-2014) laboratory techniques was used to identify these variants. Additionally, targeted genotyping was performed as translational research revealed the first three recurrent South African pathogenic variants, namely BRCA1 c.1374del (legacy name 1493delC), BRCA1 c.2641G&gt;T (legacy name E881X) and BRCA2 c.7934del (legacy name 8162delG). This initial flagship study resulted in a cost-effective diagnostic test that enabled screening of a particular ethnic group for these variants. Since then, various non-Afrikaner frequent variants were identified that were proven to represent recurrent variants. These include BRCA2 c.5771_5774del (legacy name 5999del4) and BRCA2 c.582G&gt;A, both Black African founder mutations. By performing innovative translational research, medical science in South Africa can adopt first-world technologies into its healthcare context as a developing country. Over the past two decades, the progress made in the public sector enabled a pivotal shift away from population-directed genetic testing to the screening of potentially all breast and ovarian cancer patients, irrespective of ethnicity, family history or immunohistochemical status. The modifications over the years complied with international standards and guidelines aimed at universal healthcare for all. This article shares all the cohort stratifications and the likely-to pathogenic variants detected.
Genomic Surveillance of COVID-19 Variants With Language Models and Machine Learning
Authors: Nagpal Sargun , Pal Ridam , Ashima  , Tyagi Ananya , Tripathi Sadhana , Nagori Aditya , Ahmad Saad , Mishra Hara Prasad , Malhotra Rishabh , Kutum Rintu , Sethi Tavpritesh 
Published: April 2022

The global efforts to control COVID-19 are threatened by the rapid emergence of novel SARS-CoV-2 variants that may display undesirable characteristics such as immune escape, increased transmissibility or pathogenicity. Early prediction for emergence of new strains with these features is critical for pandemic preparedness. We present Strainflow, a supervised and causally predictive model using unsupervised latent space features of SARS-CoV-2 genome sequences. Strainflow was trained and validated on 0.9 million sequences for the period December, 2019 to June, 2021 and the frozen model was prospectively validated from July, 2021 to December, 2021. Strainflow captured the rise in cases 2 months ahead of the Delta and Omicron surges in most countries including the prediction of a surge in India as early as beginning of November, 2021. Entropy analysis of Strainflow unsupervised embeddings clearly reveals the explore-exploit cycles in genomic feature-space, thus adding interpretability to the deep learning based model. We also conducted codon-level analysis of our model for interpretability and biological validity of our unsupervised features. Strainflow application is openly available as an interactive web-application for prospective genomic surveillance of COVID-19 across the globe.
The Proliferation of Glioblastoma Is Contributed to Kinesin Family Member 18A and Medical Data Analysis of GBM
Authors: Wang Lei-Bo , Zhang Xue-Bin , Liu Jun , Liu Qing-Jun 
Published: April 2022

Background: Glioblastoma (GBM) is widely known as a classical kind of malignant tumor originating in the brain with high morbidity and mortality. Targeted therapy has shown great promise in treating glioblastoma, but more promising targets, including effective therapeutic targets, remain to be identified. 18A (KIF18A) is a microtubule-based motor protein that is dysregulated and involved in the progression of multiple human cancers. However, the possible effects of KIF18A on GBM progression are still unclear.Methods: We performed DEG analysis, medical data analysis, and network analysis to identify critical genes affecting glioma progression. We also performed immunohistochemical analysis of the KIF18A levels in 94 patients with glioblastoma and the associated surrounding tissues. Patients were divided into two groups according to the high and low expression. Using a clinical analysis, we showed the potential associations between KIF18A expression and clinical characteristics of 94 GBM patients. We then investigated the effects of KIF18A on GBM cell proliferation by colony establishment, MTT, and immune blogging. The possible effect of KIF18A on GBM tumor growth was determined in mice.Results: We identified KIF18A as a potential gene affecting GBM progression. We further demonstrated that GBM tissues expressed KIF18A much higher, and its presentation was associated with recurrence in glioblastoma patients. We believe KIF18A promotes GBM cell proliferation.Conclusion: We demonstrated that KIF18A could be a promising target in treating GBM.