Assessing Spatial Representativeness of Global Flux Tower Eddy-Covariance Measurements Using Data from FLUXNET2015.

Large datasets of carbon dioxide, energy, and water fluxes were measured with the eddy-covariance (EC) technique, such as FLUXNET2015. These datasets are widely used to validate remote-sensing products and benchmark models. One of the major challenges in utilizing EC-flux data is determining the spatial extent to which measurements taken at individual EC towers reflect model-grid or remote sensing pixels. To minimize the potential biases caused by the footprint-to-target area mismatch, it is important to use flux datasets with awareness of the footprint. This study analyze the spatial representativeness of global EC measurements based on the open-source FLUXNET2015 data, using the published flux footprint model (SAFE-f). The calculated annual cumulative footprint climatology (ACFC) was overlaid on land cover and vegetation index maps to create a spatial representativeness dataset of global flux towers. The dataset includes the following components: (1) the ACFC contour (ACFCC) data and areas representing 50%, 60%, 70%, and 80% ACFCC of each site, (2) the proportion of each land cover type weighted by the 80% ACFC (ACFCW), (3) the semivariogram calculated using Normalized Difference Vegetation Index (NDVI) considering the 80% ACFCW, and (4) the sensor location bias (SLB) between the 80% ACFCW and designated areas (e.g. 80% ACFCC and window sizes) proxied by NDVI. Finally, we conducted a comprehensive evaluation of the representativeness of each site from three aspects: (1) the underlying surface cover, (2) the semivariogram, and (3) the SLB between 80% ACFCW and 80% ACFCC, and categorized them into 3 levels. The goal of creating this dataset is to provide data quality guidance for international researchers to effectively utilize the FLUXNET2015 dataset in the future.

Analysis of ceRNA Network and Identification of Potential Treatment Target and Biomarkers of Endothelial Cell Injury in Sepsis.

Background: Sepsis is a complex clinical syndrome caused by a dysregulated host immune response to infection. This study aimed to identify a competing endogenous RNA (ceRNA) network that can greatly contribute to understanding the pathophysiological process of sepsis and determining sepsis biomarkers. Methods: The GSE100159, GSE65682, GSE167363, and GSE94717 datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene coexpression network analysis was performed to find modules possibly involved in sepsis. A long noncoding RNA-microRNA-messenger RNA (lncRNA-miRNA-mRNA) network was constructed based on the findings. Single-cell analysis was performed. Human umbilical vein endothelial cells were treated with lipopolysaccharide (LPS) to create an in vitro model of sepsis for network verification. Reverse transcription-polymerase chain reaction, fluorescence in situ hybridization, and luciferase reporter genes were used to verify the bioinformatic analysis. Result: By integrating data from three GEO datasets, we successfully constructed a ceRNA network containing 18 lncRNAs, 7 miRNAs, and 94 mRNAs based on the ceRNA hypothesis. The lncRNA ZFAS1 was found to be highly expressed in LPS-stimulated endothelial cells and may thus play a role in endothelial cell injury. Univariate and multivariate Cox analyses showed that only SLC26A6 was an independent predictor of prognosis in sepsis. Overall, our findings indicated that the ZFAS1/hsa-miR-449c-5p/SLC26A6 ceRNA regulatory axis may play a role in the progression of sepsis. Conclusion: The sepsis ceRNA network, especially the ZFAS1/hsa-miR-449c-5p/SLC26A6 regulatory axis, is expected to reveal potential biomarkers and therapeutic targets for sepsis management.

Environmentally adaptive polysaccharide-based hydrogels and their applications in extreme conditions: A review.

Polysaccharide hydrogels are one of the most promising hydrogel materials due to their inherent characteristics, including biocompatibility, biodegradability, renewability, and easy modification, and their structure and functional designs have been widely researched to adapt to different application scenarios as well as to broaden their application fields. As typical wet-soft materials, the high water content and water-absorbing ability of polysaccharide-based hydrogels (PHs) are conducive to their wide biomedical applications, such as wound healing, tissue repair, and drug delivery. In addition, along with technological progress, PHs have shown potential application prospects in some high-tech fields, including human-computer interaction, intelligent driving, smart dressing, flexible sensors, etc. However, in practical applications, due to the poor ability of PHs to resist freezing below zero, dehydration at high temperature, and acid-base/swelling-induced deformation in a solution environment, they are prone to lose their wet-soft peculiarities, including structural integrity, injectability, flexibility, transparency, conductivity and other inherent characteristics, which greatly limit their high-tech applications. Hence, reducing their freezing point, enhancing their high-temperature dehydration resistance, and improving their extreme solution tolerance are powerful approaches to endow PHs with multienvironmental adaptability, broadening their application areas. This report systematically reviews the study advances of environmentally adaptive polysaccharide-based hydrogels (EAPHs), comprising anti-icing hydrogels, high temperature/dehydration resistant hydrogels, and acid/base/swelling deformation resistant hydrogels in recent years. First, the construction methods of EAPHs are presented, and the mechanisms and properties of freeze-resistant, high temperature/dehydration-resistant, and acid/base/swelling deformation-resistant adaptations are simply demonstrated. Meanwhile, the features of different strategies to prepare EAPHs as well as the strategies of simultaneously attaining multienvironmental adaptability are reviewed. Then, the applications of extreme EAPHs are summarized, and some meaningful works are well introduced. Finally, the issues and future outlooks of PH environment adaptation research are elucidated.

Pentraxin-3 as a predictive marker of mortality in sepsis: an updated systematic review and meta-analysis.

BACKGROUND: The purpose of this study was to clarify the prognostic value of Pentraxin-3 (PTX3) on the mortality of patients with sepsis. METHODS: Publications published up to January 2021 were retrieved from PubMed, EMBASE, and the Cochrane library. Data from eligible cohort and case-control studies were extracted for the meta-analysis. Multivariate regression analysis was used to evaluate the correlation of the outcomes with sample size and male proportion. RESULTS: A total of 17 studies covering 3658 sepsis patients were included. PTX3 level was significantly higher in non-survivor compared to survivor patients (SMD (95% CI): -1.06 (-1.43, -0.69), P < 0.001). Increased PTX3 level was significantly associated with mortality (HR (95% CI): 2.09 (1.55, 2.81), P < 0.001). PTX3 showed good predictive capability for mortality (AUC:ES (95% CI): 0.73 (0.70, 0.77), P < 0.001). The outcome comparing PTX3 level in non-survivors vs. survivors and the outcome of the association between PTX3 and mortality were associated with sample size but not male proportion. AUC was associated with both sample size and male proportion. CONCLUSIONS: PTX3 level was significantly higher in non-survivor compared to survivor patients with sepsis. Elevated PTX3 level was significantly associated with mortality. Furthermore, the level of PTX3 might predict patient mortality.

Increased 28-day mortality due to fluid overload prior to continuous renal replacement in sepsis associated acute kidney injury.

Patients with sepsis are prone to fluid overload (FO) due to fluid resuscitation, irrespective of stage of acute kidney injury (AKI). The aim of our study was to analyze the association between FO at continuous renal replacement therapy (CRRT) initiation and 28-day mortality in patients with sepsis associated AKI (S-AKI). In this retrospective study, data for patient characteristics were collected and 28-day mortality were studied. We also analyze association of variables, including FO degrees with 28-day mortality. Earlier commencement of CRRT showed better outcome. Non-survivors had higher FO than survivor (9.17% vs. 5.20%; p = 0.016). Survival in patients with FO > 10% over 28 days was significantly worse compared to those with FO ≤ 10% (p = 0.006). Multivariate analysis showed, FO > 10% (95%CI [1.721, 17.195], p = 0.004) was significantly associated with increased 28-day mortality. In S-AKI requiring CRRT, FO > 10% at CRRT initiation was independently associated with 28-day mortality.

Hemorrhage and venous thromboembolism in critically ill patients with COVID-19.

OBJECTIVE: The majority of patients with COVID-19 showed mild symptoms. However, approximately 5% of them were critically ill and require intensive care unit admission for advanced life supports. Patients in the intensive care unit were high risk for venous thromboembolism and hemorrhage due to the immobility and anticoagulants used during advanced life supports. The aim of the study was to report the incidence and treatments of the two complications in such patients. METHOD: Patients with COVID-19 (Group 1) and patients with community-acquired pneumonia (Group 2) that required intensive care unit admission were enrolled in this retrospective study. Their demographics, laboratory results, ultrasound findings and complications such as venous thromboembolism and hemorrhage were collected and compared. RESULTS: Thirty-four patients with COVID-19 and 51 patients with community-acquired pneumonia were included. The mean ages were 66 and 63 years in Groups 1 and 2, respectively. Venous thromboembolism was detected in 6 (18%) patients with COVID-19 and 18 (35%) patients with community-acquired pneumonia (P = 0.09). The major type was distal deep venous thrombosis. Twenty-one bleeding events occurred in 12 (35%) patients with COVID-19 and 5 bleeding events occurred in 5 (10%) patients with community-acquired pneumonia, respectively (P = 0.01). Gastrointestinal system was the most common source of bleeding. With the exception of one death due to intracranial bleeding, blood transfusion with or without surgical/endoscopic treatments was able to manage the bleeding in the remaining patients. Multivariable logistic regression showed increasing odds of hemorrhage with extracorporeal membrane oxygenation (odds ratio: 13.9, 95% confidence interval: 4.0-48.1) and COVID-19 (odds ratio: 4.7, 95% confidence interval: 1.2-17.9). CONCLUSION: Venous thromboembolism and hemorrhage were common in both groups. The predominant type of venous thromboembolism was distal deep venous thrombosis, which presented a low risk of progression. COVID-19 and extracorporeal membrane oxygenation were risk factors for hemorrhage. Blood transfusion with or without surgical/endoscopic treatments was able to manage it in most cases.

[Master genes and co-expression network analysis in peripheral blood mononuclear cells of patients with gram-positive and gram-negative sepsis].

OBJECTIVE: To investigate the functional pathways enriched and differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMCs) of patients with gram-positive and gram-negative sepsis. METHODS: Dataset GSE9960 obtained from NCBI GEO database containing PBMC samples from 16 non-infectious systematic inflammatory response syndrome (SIRS) patients, 17 gram-positive septic patients and 18 gram-negative septic patients were included in the study. Functional pathway annotations were conducted by gene set enrichment analysis and weighted gene co-expression network analysis. DEGs were filtered and master DEGs were then validated in PBMCs of gram-positive septic, gram-negative septic and non-infectious SIRS patients. RESULTS: The enriched gene sets in gram-positive sepsis and gram-negative sepsis were significantly different. The results indicated the opposite co-expression networks in SIRS and gram-negative sepsis, and the entirely different co-expression networks in gram-positive and gram-negative sepsis. Furthermore, we validated that TYMS was up-regulated in gram-positive sepsis (P<0.05), CD3D was down-regulated in gram-negative sepsis (P<0.01), while IRAK3 was up-regulated in gram-negative sepsis (P<0.05). CONCLUSIONS: The results indicate that there are differences in the mechanism and pathogenesis of gram-positive and gram-negative sepsis, which may provide potential markers for sepsis diagnosis and empirical antimicrobial therapy.

Regulatory Master Genes Identification and Drug Repositioning by Integrative mRNA-miRNA Network Analysis for Acute Type A Aortic Dissection.

Acute type A aortic dissection (ATAAD) is a life-threatening disease. The understanding of its pathogenesis and treatment approaches remains unclear. In the present work, differentially expressed genes (DEGs) from two ATAAD datasets GSE52093 and GSE98770 were filtered. Transcription factor TEAD4 was predicted as a key modulator in protein-protein interaction (PPI) network. Weighted correlation network analysis (WGCNA) identified five modules in GSE52093 and four modules in GSE98770 were highly correlated with ATAAD. 71 consensus DEGs of highly correlated modules were defined and functionally annotated. L1000CDS2 was executed to predict drug for drug repositioning in ATAAD treatment. Eight compounds were filtered as potential drugs. Integrative analysis revealed the interaction network of five differentially expressed miRNA and 16 targeted DEGs. Finally, master DEGs were validated in human ATAAD samples and AD cell model in vitro. TIMP3 and SORBS1 were downregulated in ATAAD samples and AD cell model, while PRUNE2 only decreased in vitro. Calcium channel blocker and glucocorticoid receptor agonist might be potential drugs for ATAAD. The present study offers potential targets and underlying molecular mechanisms ATAAD pathogenesis, prevention and drug discovery.