scholarly journals The dynamics of early-stage transmission of COVID-19: A novel quantification of the role of global temperature

2022 ◽  
Author(s):  
Lu Liu
2015 ◽  
Vol 10 (2) ◽  
pp. 101-110 ◽  
Author(s):  
Matias E. Valsecchi ◽  
Gerrit Kimmey ◽  
Arvinder Bir ◽  
Damian Silbermins

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3314
Author(s):  
Tomasz Kowalczyk ◽  
Joanna Kisluk ◽  
Karolina Pietrowska ◽  
Joanna Godzien ◽  
Miroslaw Kozlowski ◽  
...  

Identification of the NSCLC subtype at an early stage is still quite sophisticated. Metabolomics analysis of tissue and plasma of NSCLC patients may indicate new, and yet unknown, metabolic pathways active in the NSCLC. Our research characterized the metabolomics profile of tissue and plasma of patients with early and advanced NSCLC stage. Samples were subjected to thorough metabolomics analyses using liquid chromatography-mass spectrometry (LC-MS) technique. Tissue and/or plasma samples from 137 NSCLC patients were analyzed. Based on the early stage tissue analysis, more than 200 metabolites differentiating adenocarcinoma (ADC) and squamous cell lung carcinoma (SCC) subtypes as well as normal tissue, were identified. Most of the identified metabolites were amino acids, fatty acids, carnitines, lysoglycerophospholipids, sphingomyelins, plasmalogens and glycerophospholipids. Moreover, metabolites related to N-acyl ethanolamine (NAE) biosynthesis, namely glycerophospho (N-acyl) ethanolamines (GP-NAE), which discriminated early-stage SCC from ADC, have also been identified. On the other hand, the analysis of plasma of chronic obstructive pulmonary disease (COPD) and NSCLC patients allowed exclusion of the metabolites related to the inflammatory state in lungs and the identification of compounds (lysoglycerophospholipids, glycerophospholipids and sphingomyelins) truly characteristic to cancer. Our results, among already known, showed novel, thus far not described, metabolites discriminating NSCLC subtypes, especially in the early stage of cancer. Moreover, the presented results also indicated the activity of new metabolic pathways in NSCLC. Further investigations on the role of NAE biosynthesis pathways in the early stage of NSCLC may reveal new prognostic and diagnostic targets.


Author(s):  
Francesca Pagani ◽  
Elisa Tratta ◽  
Patrizia Dell’Era ◽  
Manuela Cominelli ◽  
Pietro Luigi Poliani

AbstractEarly B-cell factor-1 (EBF1) is a transcription factor with an important role in cell lineage specification and commitment during the early stage of cell maturation. Originally described during B-cell maturation, EBF1 was subsequently identified as a crucial molecule for proper cell fate commitment of mesenchymal stem cells into adipocytes, osteoblasts and muscle cells. In vessels, EBF1 expression and function have never been documented. Our data indicate that EBF1 is highly expressed in peri-endothelial cells in both tumor vessels and in physiological conditions. Immunohistochemistry, quantitative reverse transcription polymerase chain reaction (RT-qPCR) and fluorescence-activated cell sorting (FACS) analysis suggest that EBF1-expressing peri-endothelial cells represent bona fide pericytes and selectively express well-recognized markers employed in the identification of the pericyte phenotype (SMA, PDGFRβ, CD146, NG2). This observation was also confirmed in vitro in human placenta-derived pericytes and in human brain vascular pericytes (HBVP). Of note, in accord with the key role of EBF1 in the cell lineage commitment of mesenchymal stem cells, EBF1-silenced HBVP cells showed a significant reduction in PDGFRβ and CD146, but not CD90, a marker mostly associated with a prominent mesenchymal phenotype. Moreover, the expression levels of VEGF, angiopoietin-1, NG2 and TGF-β, cytokines produced by pericytes during angiogenesis and linked to their differentiation and activation, were also significantly reduced. Overall, the data suggest a functional role of EBF1 in the cell fate commitment toward the pericyte phenotype.


Author(s):  
Vishal Rao ◽  
Anand Subash ◽  
Piyush Sinha ◽  
Sameep Shetty ◽  
Shalini Thakur ◽  
...  

2017 ◽  
Vol 58 (5) ◽  
pp. 863-873 ◽  
Author(s):  
Lai Ma ◽  
Dechun Zhang ◽  
Qisong Miao ◽  
Jing Yang ◽  
Yuanhu Xuan ◽  
...  

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dan Wu ◽  
Tingzhong Yang ◽  
Daniel L. Hall ◽  
Guihua Jiao ◽  
Lixin Huang ◽  
...  

Abstract Background The COVID-19 pandemic brings unprecedented uncertainty and stress. This study aimed to characterize general sleep status among Chinese residents during the early stage of the outbreak and to explore the network relationship among COVID-19 uncertainty, intolerance of uncertainty, perceived stress, and sleep status. Methods A cross-sectional correlational survey was conducted online. A total of 2534 Chinese residents were surveyed from 30 provinces, municipalities, autonomous regions of China and regions abroad during the period from February 7 to 14, 2020, the third week of lockdown. Final valid data from 2215 participants were analyzed. Self-report measures assessed uncertainty about COVID-19, intolerance of uncertainty, perceived stress, and general sleep status. Serial mediation analysis using the bootstrapping method and path analysis were applied to test the mediation role of intolerance of uncertainty and perceived stress in the relationship between uncertainty about COVID-19 and sleep status. Results The total score of sleep status was 4.82 (SD = 2.72). Age, place of residence, ethnicity, marital status, infection, and quarantine status were all significantly associated with general sleep status. Approximately half of participants (47.1%) reported going to bed after 12:00 am, 23.0% took 30 min or longer to fall asleep, and 30.3% slept a total of 7 h or less. Higher uncertainty about COVID-19 was significantly positively correlated with higher intolerance of uncertainty (r = 0.506, p < 0.001). The mediation analysis found a mediating role of perceived stress in the relationship between COVID-19 uncertainty and general sleep status (β = 0.015, 95%C.I. = 0.009–0.021). However, IU was not a significant mediator of the relationship between COVID-19 uncertainty and sleep (β = 0.009, 95%C.I. = − 0.002–0.020). Moreover, results from the path analysis further showed uncertainty about COVID-19 had a weak direct effect on poor sleep (β = 0.043, p < 0.05); however, there was a robust indirect effect on poor sleep through intolerance of uncertainty and perceived stress. Conclusions These findings suggest that intolerance of uncertainty and perceived stress are critical factors in the relationship between COVID-19 uncertainty and sleep outcomes. Results are discussed in the context of the COVID-19 pandemic, and practical policy implications are also provided.


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