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The study is to explore the role of ferroptosis-related genes (FRGs) in the occurrence and development of gastric cancer (GC), and to construct a new prognosis signature to predict the prognosis in GC. Clinical information and corresponding RNA data of GC patients were downloaded from TCGA and GEO databases. Consensus clustering was performed to identify new molecular subgroups. ESTIMATE, CIBERSORT, McpCounter and TIMER algorithm were used to analyze the infiltration of immune cells in two molecular subgroups. LASSO algorithm and multivariate Cox analysis were used to construct a prognostic risk signature. Functional analysis was conducted to elucidate the underlying mechanisms. Finally, the FRPGs were verified by Quantitative Real-Time PCR. We obtained 16 FRGs and divided GC patients into two subgroups by consistent clustering. Cluster C1 with a higher abundance of immune cell infiltration but lower probability in response to immunotherapy, it was reasonable to speculate that Cluster C1 was in accordance with the immune rejection type. Functional analysis showed that the biological process of DEGs in training cohort mainly included immune globulin, and human immune response mediated by circulating immune globulin. GSEA analysis showed that compared with Cluster C2, Cluster C1 showed lower expression in lipid metabolism. The nomogram combined with risk signature and clinical features can accurately predict the prognosis of GC patients. We identified two molecular subtypes, Clusters C1 and C2. In Cluster C1, patients with poor prognosis present with a hyperimmune status and low lipid metabolism, and we speculate that Cluster C1 was in accordance with the immune rejection type. The risk model based on FRPGs can accurately predict the prognosis of GC. These results indicated that ferroptosis is associated with TIME, and deserved considerable attention in determining immunotherapy treatment strategy for GC patients.

Fine particulate matter (PM2.5) is the primary air pollutant that is able to induce airway injury. Compelling evidence has shown the involvement of IL‐17A in lung injury, while its contribution to PM2.5‐induced lung injury remains largely unknown. Here, we probed into the possible role of IL‐17A in mouse models of PM2.5‐induced lung injury. Mice were instilled with PM2.5 to construct a lung injury model. Flow cytometry was carried out to isolate γδT and Th17 cells. ELISA was adopted to detect the expression of inflammatory factors in the supernatant of lavage fluid. Primary bronchial epithelial cells (mBECs) were extracted, and the expression of TGF signalling pathway‐, autophagy‐ and PI3K/Akt/mTOR signalling pathway‐related proteins in mBECs was detected by immunofluorescence assay and Western blot analysis. The mitochondrial function was also evaluated. PM2.5 aggravated the inflammatory response through enhancing the secretion of IL‐17A by γδT/Th17 cells. Meanwhile, PM2.5 activated the TGF signalling pathway and induced EMT progression in bronchial epithelial cells, thereby contributing to pulmonary fibrosis. Besides, PM2.5 suppressed autophagy of bronchial epithelial cells by up‐regulating IL‐17A, which in turn activated the PI3K/Akt/mTOR signalling pathway. Furthermore, IL‐17A impaired the energy metabolism of airway epithelial cells in the PM2.5‐induced models. This study suggested that PM2.5 could inhibit autophagy of bronchial epithelial cells and promote pulmonary inflammation and fibrosis by inducing the secretion of IL‐17A in γδT and Th17 cells and regulating the PI3K/Akt/mTOR signalling pathway.

Launched in 2006, the Formosa Satellite Mission 3–Constellation Observing System for Meteorology, Ionosphere and Climate (FORMOSAT-3/COSMIC) was the first constellation of microsatellites carrying global positioning system (GPS) radio occultation (RO) receivers. Radio occultation is an active remote sensing technique that provides valuable information on the vertical variations of electron density in the ionosphere, and temperature, pressure, and water vapor in the stratosphere and troposphere. COSMIC has demonstrated the great value of RO data in ionosphere, climate, and meteorological research and operational weather forecasting. However, there are still challenges using RO data, particularly in the moist lower troposphere and upper stratosphere. A COSMIC follow-on constellation, COSMIC-2, was launched into equatorial orbit in 2019. With increased signal-to-noise ratio (SNR) from improved receivers and digital beam steering antennas, COSMIC-2 will produce at least 5,000 high-quality RO profiles daily in the tropics and subtropics. In this paper, we summarize 1) recent (since 2011 when the last review was published) contributions of COSMIC and other RO observations to weather, climate, and space weather science; 2) the remaining challenges in RO applications; and 3) potential contributions to research and operations of COSMIC-2.

Purpose. Leukocyte telomere length (LTL) is an important biomarker of aging. The oxidative balance score (OBS) is used to assess the oxidative stress-related exposures of diet and lifestyle. This study is aimed at exploring if the OBS was associated with LTL. Methods. 3220 adults were included in this study from the National Health and Nutrition Examination Survey (NHANES) 1999-2002. LTL was assayed from leukocyte DNA. Twenty dietary and lifestyle factors were selected to score the OBS. Survey-based multivariable linear regression was conducted to assess the association between the OBS and log-transformed LTL. Results. The association between the OBS and log-transformed LTL was positive in females but not males. For females, compared with the lowest OBS category as a reference, the multivariable-adjusted beta estimate (95% confidence interval, CI) for the highest OBS category was 0.0701 (0.0205–0.1197) (p for trend<0.01), and the multivariable-adjusted beta estimate (95% CI) of the continuous OBS was 0.0039 (0.0014–0.0065). There was also the gender difference in the correlations of the dietary OBS and the lifestyle OBS with log-transformed LTL. Conclusion. There was a positive association between the OBS and LTL in females. This result suggested that diet and lifestyle might affect LTL by regulating oxidative balance.

Background Recent evidences showed that long noncoding RNAs (lncRNAs) are frequently dysregulated and play important roles in various cancers. Clear cell renal cell carcinoma (ccRCC) is one of the leading cause of cancer-related death, largely due to the metastasis of ccRCC. However, the clinical significances and roles of lncRNAs in metastatic ccRCC are still unknown. Methods lncRNA expression microarray analysis was performed to search the dysregulated lncRNA in metastatic ccRCC. quantitative real-time PCR was performed to measure the expression of lncRNAs in human ccRCC samples. Gain-of-function and loss-of-function experiments were performed to investigate the biological roles of lncRNAs on ccRCC cell proliferation, migration, invasion and in vivo metastasis. RNA pull-down, RNA immunoprecipitation, chromatin immunoprecipitation, and western blot were performed to explore the molecular mechanisms underlying the functions of lncRNAs. Results The microarray analysis identified a novel lncRNA termed metastatic renal cell carcinoma-associated transcript 1 (MRCCAT1), which is highly expressed in metastatic ccRCC tissues and associated with the metastatic properties of ccRCC. Multivariate Cox regression analysis revealed that MRCCAT1 is an independent prognostic factor for ccRCC patients. Overexpression of MRCCAT1 promotes ccRCC cells proliferation, migration, and invasion. Depletion of MRCCAT1 inhibites ccRCC cells proliferation, migration, and invasion in vitro, and ccRCC metastasis in vivo. Mechanistically, MRCCAT1 represses NPR3 transcription by recruiting PRC2 to NPR3 promoter, and subsequently activates p38-MAPK signaling pathway. Conclusions MRCCAT1 is a critical lncRNA that promotes ccRCC metastasis via inhibiting NPR3 and activating p38-MAPK signaling. Our results imply that MRCCAT1 could serve as a prognostic biomarker and therapeutic target for ccRCC.

Bioprosthetic heart valve (BHV), the most widely and commonly used valves in clinical practice, are susceptible to fatigue damage. Biological valves are always in one or fewer body postures before sampling in pigs and bovines. Nevertheless, human body positions are far more than them. Variations in body position significantly affect the intrinsic environment of blood pressure (BP), heart rate (HR), and peripheral resistance (PR). Such boundary condition changes will inevitably affect the implanted biological valve. In this paper, the immersed boundary method was used to simulate the motion of the aortic valve during the entire cardiac cycle in five postural blood flow environments: upright, sitting, prone, supine and orthostatic hypotension (OH). Several hemodynamic and biomechanical parameters, including the transvalvular pressure gradient and valve displacement, were evaluated. The results showed that the OH group exhibited the worst performance of the valves, accompanied by the greatest regurgitation and high-frequency flutter, predisposing patients to thrombosis and fatigue calcification. For BHVs to serve longer, patients implanted with BHV should avoid OH in their daily routine.

Background Whether serum lactate dehydrogenase-to-albumin ratio (LAR) influenced the outcomes of colorectal cancer (CRC) patients after radical surgery remained unclear. Therefore, this study sought to examine how LAR influences the short-term and long-term outcomes of CRC patients who have undergone radical surgery. Methods This study retrospectively included CRC patients who underwent radical resection between January 2011 and January 2020. We compared short-term outcomes, as well as overall survival (OS) and disease-free survival (DFS), among various groups. Both univariate and multivariate logistic regression analyses were utilized to pinpoint independent risk factors associated with overall complications and major complications. Moreover, Cox regression analysis were conducted for OS and DFS. Odds ratio (OR) and Hazard ratio (HR) were adjusted. Results This study encompassed a cohort of 3868 patients. 3440 patients were in the low LAR group and 428 patients constituted the high LAR group. In the high LAR group, patients experienced significantly longer operative times (p < 0.01), larger intraoperative blood loss (p < 0.01), and extended postoperative hospital stays (p < 0.01). Additionally, the incidence of both overall complications (p < 0.01) and major complications (p < 0.01) was higher in the high LAR group compared to the low LAR group. Furthermore, LAR was emerged as an independent prognostic factor for overall complications [OR/95% CI: (1.555/1.237 to 1.954), p < 0.01] and major complications [OR/95% CI: (2.178/1.279 to 3.707), p < 0.01]. As for long-term survival, the high LAR group had worse OS in stage II (p < 0.01) and stage III (p < 0.01). In both stage II (p < 0.01) and stage III (p < 0.01), the high LAR group exhibited poorer DFS. Additionally, according to Cox regression analysis, LAR was identified as an independent predictor for both OS [HR/95% CI: (1.930/1.554 to 2.398), p < 0.01] and DFS [HR/95% CI: (1.750/1.427 to 2.146), p < 0.01]. Conclusion LAR emerged as an independent predictor not only for overall complications and major complications but also for both OS and DFS, highlighting its significance and deserving the attention of surgeons.

The radio occultation technique provides stable atmospheric measurements that can work as a benchmark for calibrating and validating satellite-sounding data. Launched on 25 June 2019, the Constellation Observing System for Meteorology, Ionosphere, and Climate 2 and Formosa Satellite Mission 7 (COSMIC-2/FORMOSAT-7) are expected to produce about 5000 high-quality RO observations daily over the tropics and subtropics. COSMIC-2 constellation consists of 6 Low Earth Orbit (LEO) satellites in 24° inclination orbits at 720 km altitude and distributed mainly between 45°N to 45°S. The COSMIC-2 observations have uniform temporal coverage between 30°N to 30°S. This paper presents an independent inversion algorithm to invert COSMIC-2 geometry and phase data to bending angle and refractivity. We also investigate the quality of Global Navigation Satellite System (GNSS) and LEO position vectors derived from the UCAR COSMIC Data Analysis and Archive Center (CDAAC). The GNSS and LEO position vectors are stable with LEO position variations < 1.4 mm/s. The signal-to-noise ratio (SNR) on the L1 band ranges from 300–2600 v/v with a mean of 1600 v/v. The inversion algorithm developed at NOAA Center for Satellite Applications and Research (STAR) uses the Full Spectrum Inversion (FSI) method to invert COSMIC-2 geometry and phase data to bending angle and refractivity profiles. The STAR COSMIC-2 bending angle and refractivity profiles are compared with in situ radiosonde, the current COSMIC-2 products derived from CDAAC, and the collocated European Center for Medium-Range Weather Forecasts (ECMWF) climate reanalysis data ERA5. The mean bias at 8–40 km altitude among the UCAR, ERA5, and STAR is <0.1% for both bending and refractivity, with a standard deviation in the range of 1.4–2.3 and 0.9–1.1% for bending angles refractivity, respectively. In the lowest 2 km, the RO bias relative to ERA-5 shows a strong latitudinal and SNR dependence.

Radiosonde observations (RAOBs) have provided the only long-term global in situ temperature measurements in the troposphere and lower stratosphere since 1958. In this study, we use consistently reprocessed Global Positioning System (GPS) radio occultation (RO) temperature data derived from the COSMIC and Metop-A/GRAS missions from 2006 to 2014 to characterize the inter-seasonal and interannual variability of temperature biases in the upper troposphere and lower stratosphere for different radiosonde sensor types. The results show that the temperature biases for different sensor types are mainly due to (i) uncorrected solar-zenith-angle-dependent errors and (ii) change of radiation correction. The mean radiosonde–RO global daytime temperature difference in the layer from 200 to 20 hPa for Vaisala RS92 is equal to 0.20 K. The corresponding difference is equal to −0.06 K for Sippican, 0.71 K for VIZ-B2, 0.66 K for Russian AVK-MRZ, and 0.18 K for Shanghai. The global daytime trend of differences for Vaisala RS92 and RO temperature at 50 hPa is equal to 0.07 K/5 yr. Although there still exist uncertainties for Vaisala RS92 temperature measurement over different geographical locations, the global trend of temperature differences between Vaisala RS92 and RO from June 2006 to April 2014 is within ±0.09 K/5 yr. Compared with Vaisala RS80, Vaisala RS90, and sondes from other manufacturers, the Vaisala RS92 seems to provide the most accurate RAOB temperature measurements, and these can potentially be used to construct long-term temperature climate data records (CDRs). Results from this study also demonstrate the feasibility of using RO data to correct RAOB temperature biases for different sensor types.

China has the largest afforested area in the world (∼62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 ± 0.5 °C (mean ± 1 SD) and to increase nighttime LST by about 0.2 ± 0.5 °C, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.