In Vivo Radioprotective Activity of Cell-Permeable Bifunctional Antioxidant Enzyme GST-TAT-SOD against Whole-Body Ionizing Irradiation in Mice

GST-TAT-SOD was the fusion of superoxide dismutase (SOD), cell-permeable peptide TAT, and glutathione-S-transferase (GST). It was proved to be a potential selective radioprotector in vitro in our previous work. This study evaluated the in vivo radioprotective activity of GST-TAT-SOD against whole-body irradiation. We demonstrated that intraperitoneal injection of 0.5 ml GST-TAT-SOD (2 kU/ml) 2 h before the 6 Gy whole-body irradiation in mice almost completely prevented the splenic damage. It could significantly enhance the splenic antioxidant activity which kept the number of splenic white pulp and consequently resisted the shrinkage of the spleen. Moreover, the thymus index, hepatic antioxidant activity, and white blood cell (WBC) count of peripheral blood in irradiated mice pretreated with GST-TAT-SOD also remarkably increased. Although the treated and untreated irradiated mice showed no significant difference in the growth rate of animal body weight at 7 days postirradiation, the highest growth rate of body weight was observed in the GST-TAT-SOD-pretreated group. Furthermore, GST-TAT-SOD pretreatment increased resistance against 8 Gy whole-body irradiation and enhanced 30 d survival. The overall effect of GST-TAT-SOD seemed to be a bit more powerful than that of amifostine. In conclusion, GST-TAT-SOD would be a safe and potentially promising radioprotector

A novel anoikis-related gene prognostic signature and its correlation with the immune microenvironment in colorectal cancer

Background: Anoikis is a type of apoptosis associated with cell detachment. Resistance to anoikis is a focal point of tumor metastasis. This study aimed to explore the relationship among anoikis-related genes (ARGs), immune infiltration, and prognosis in colorectal cancer (CRC).Methods: The transcriptome profile and clinical data on patients with CRC were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Patients were divided into two clusters based on the expression of ARGs. Differences between the two ARG molecular subtypes were analyzed in terms of prognosis, functional enrichment, gene mutation frequency, and immune cell infiltration. An ARG-related prognostic signature for predicting overall survival in patients with CRC was developed and validated using absolute value convergence and selection operator (LASSO) regression analysis. The correlation between the signature risk score and clinicopathological features, immune cell infiltration, immune typing, and immunotherapy response was analyzed. The risk score combined with clinicopathological characteristics was used to construct a nomogram to assess CRC patients’ prognosis.Results: Overall, 151 ARGs were differentially expressed in CRC. Two ARG subtypes, namely, ARG-high and ARG-low groups, were identified and correlated with CRC prognosis. The gene mutation frequency and immune, stromal, and ESTIMATE scores of the ARG-high group were higher than those of the ARG-low group. Moreover, CD8, natural killer cells, M1 macrophages, human leukocyte antigen (HLA), and immune checkpoint-related genes were significantly increased in the ARG-high group. An optimized 25-gene CRC prognostic signature was successfully constructed, and its prognostic predictive ability was validated. The high-risk score was correlated with T, N, M, and TNM stages. Risk scores were negatively correlated with dendritic cells, eosinophils, and CD4 cells, and significantly positively correlated with regulatory T cells. Patients in the high-risk group were more likely to exhibit immune unresponsiveness. Finally, the nomogram model was constructed and showed good prognostic predictive power.Conclusion: ARGs are associated with clinicopathological features and the prognosis of CRC, and play important roles in the immune microenvironment. Herein, we underpinned the usefulness of ARGs in CRC to develop more effective immunotherapy techniques

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Development and validation of a novel prognostic signature based on m6A/m5C/m1A-related genes in hepatocellular carcinoma

Abstract Background RNA methylation modification plays an important role in cancers. This study sought to examine the association between m6A/m5C/m1A-related genes and hepatocellular carcinoma (HCC). Methods Gene expression and clinical data of HCC patients were obtained from the TCGA database. Unsupervised consensus clustering was performed according to the expression of m6A/m5C/m1A-related genes in HCC. The relationships among prognosis, clinicopathological features and molecular subtypes were analyzed. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to establish the m6A/m5C/m1A-related gene prognostic signature. Furthermore, the prognostic signature was validated based on the ICGC dataset. RT‒qPCR was used to detect the expression of the model genes in HCC. Clinicopathological features, functional enrichment, gene mutations, immune cell infiltration, and immunotherapy response in different risk groups were analyzed. A nomogram based on risk score and stage was constructed to predict HCC patient prognosis. Results Two m6A/m5C/m1A-related molecular subtypes were identified in HCC, and the prognosis of cluster C1 was worse than that of cluster C2 (p < 0.001). Highly expressed genes in cluster C1 are significantly correlated with G3-4, T3-4, stage III-IV (p < 0.05). An m6A/m5C/m1A-related prognostic signature was established and validated. The RT‒qPCR results showed that the risk signature genes were significantly upregulated in liver cancer tissue (p < 0.05). The prognosis of HCC patients in the high-risk group was worse than that of those in the low-risk group (p < 0.05). Multivariate Cox analysis indicated that the risk score was an independent factor predicting prognosis in HCC patients. ssGSEA revealed that the risk score correlated with the tumor immune microenvironment in HCC. Gene mutation analysis showed that the tumor mutation burden of patients in the high-risk group was much higher (p < 0.05), and the prognosis of HCC patients with high risk scores and high mutation burden was the worst (p = 0.007). A nomogram combining risk scores with clinicopathological features showed performed well in predicting HCC prognosis. Conclusions The m6A/m5C/m1A-related genes could predict the prognosis and tumor microenvironment features of HCC and can be important biomarkers relevant to the immunotherapy response

Experimental Study and Bearing Capacity Analysis of Retrofitted Built-Up Steel Angle Members under Axial Compression

Against the update of load design standards and requirement of long-term service, many latticed towers using steel angles subjected to gradual performance degradation must be retrofitted for bearing further social functions, e.g., electric power transmission and fifth-generation mobile communication. Therefore, this paper proposed a non-destructive reinforcement method for steel angles by avoiding unnecessary new construction or complex reinforcement procedure. The non-destructive reinforcement of a steel angle is composed of a steel angle, reinforcement plate, and fixture. Standardized fixtures are used to connect the reinforcement plate and steel angle to achieve steel angle reinforcement. In retrofitting tests, built-up steel angle members were loaded under axial compression, in which the failure mode and reinforcement effect of key parameters (e.g., clamp type, slenderness ratio, and clamp distance) were analyzed and compared, where a significant reinforcement effect was obtained with the capacity increment within 39~174%; the clamp types and clamp distance had a slight effect on bearing capacity; and the proposed reinforcement method was more effective for slender members. Based on the mechanical mechanism analysis and failure mode, the accuracy of the design method for calculating the bearing capacity of those built-up steel angle members was suggested and verified, in which a simplified mechanical model for the flexural-buckling mode was developed. The design method based on AISC360-16 agreed well with the test result and could be effectively used for calculating the flexural–torsional bearing capacity of those built-up steel angles. This study can provide a valuable reference for the design and application of non-destructive reinforcement of angle steel towers

Using Co-polymers to Improve Soil Strength and Mitigate Fugitive Dust Emissions: Laboratory Evaluation

A report by the Federal Highway Administration (FHWA) in the USA stated that there are over 1.4 million miles (2.3 million kilometres) of unpaved roads in the United States, over 1/3 of the U.S highway systems. Unpaved roads play an important role in transporting goods and passengers in between urban and suburban areas. However, most unpaved roads are gravel and unimproved that have exposed a severe issue for local transportation networks. Particularly when unpaved roads are in wet conditions (rain or snow), the muddy and soft surface roads have created a hazardous environment for traffic operations. The paper presents an improvement plan using co-polymer dust suppressants to be mixed with soils collected in Northern Arizona. Soil samples were mixed with the co-polymer dust suppressants using four concentration rates (0% water, 1%, 3%, and 5% by weight). A series of tests were performed including surface strength (resistant penetration) test, dynamic rolling test, and unconfined compressive shear test. The results show that the addition of co-polymer dust suppressants in the soil has improved the soil shear strength and decreased dust emissions, provided the results from the surface strength test, dynamic rolling test, and unconfined compressive strength test are promising