Prognostic markers of ferroptosis-related long non-coding RNA in lung adenocarcinomas

Ferroptosis is a recently established type of iron-dependent programmed cell death. Growing studies have focused on the function of ferroptosis in cancers, including lung adenocarcinoma (LUAD). However, the factors involved in the regulation of ferroptosis-related genes are not fully understood. In this study, we collected data from lung adenocarcinoma datasets of the Cancer Genome Atlas (TCGA-LUAD). The expression profiles of 60 ferroptosis-related genes were screened, and two differentially expressed ferroptosis subtypes were identified. We found the two ferroptosis subtypes can predict clinical outcomes and therapeutic responses in LUAD patients. Furthermore, key long non-coding RNAs (lncRNAs) were screened by single factor Cox and least absolute shrinkage and selection operator (LASSO) based on which co-expressed with the 60 ferroptosis-related genes. We then established a risk score model which included 13 LUAD ferroptosis-related lncRNAs with a multi-factor Cox regression. The risk score model showed a good performance in evaluating the outcome of LUAD. What’s more, we divided TCGA-LUAD tumor samples into two groups with high- and low-risk scores and further explored the differences in clinical characteristics, tumor mutation burden, and tumor immune cell infiltration among different LUAD tumor risk score groups and evaluate the predictive ability of risk score for immunotherapy benefit. Our findings provide good support for immunotherapy in LUAD in the future

Expression Analysis of Four Peroxiredoxin Genes from Tamarix hispida in Response to Different Abiotic Stresses and Exogenous Abscisic Acid (ABA)

Peroxiredoxins (Prxs) are a recently discovered family of antioxidant enzymes that catalyze the reduction of peroxides and alkyl peroxides. In this study, four Prx genes (named as ThPrxII, ThPrxIIE, ThPrxIIF, and Th2CysPrx) were cloned from Tamarix hispida. Their expression profiles in response to stimulus of NaCl, NaHCO3, PEG, CdCl2 and abscisic acid (ABA) in roots, stems and leaves of T. hispida were investigated using real-time RT-PCR. The results showed that the four ThPrxs were all expressed in roots, stems and leaves. Furthermore, the transcript levels of ThPrxIIE and ThPrxII were the lowest and the highest, respectively, in all tissue types. All the ThPrx genes were induced by both NaCl and NaHCO3 and reached their highest expression levels at the onset of stress in roots. Under PEG and CdCl2 stress, the expression patterns of these ThPrxs showed temporal and spatial specificity. The expressions of the ThPrxs were all differentially regulated by ABA, indicating that they are all involved in the ABA signaling pathway. These findings reveal a complex regulation of Prxs that is dependent on the type of Prx, tissue, and the signaling molecule. The divergence of the stress-dependent transcriptional regulation of the ThPrx gene family in T. hispida may provide an essential basis for the elucidation of Prx function in future work

Acute myocardial infarction after inactivated COVID-19 vaccination: a case report and literature review

A number of vaccines have been developed and deployed globally to restrain the spreading of the coronavirus disease 2019 (COVID-19). The adverse effect following vaccination is an important consideration. Acute myocardial infarction (AMI) is a kind of rare adverse event after COVID-19 vaccination. Herein, we present a case of an 83-year-old male who suffered cold sweat ten minutes after the first inactivated COVID-19 vaccination and AMI one day later. The emergency coronary angiography showed coronary thrombosis and underlying stenosis in his coronary artery. Type II Kounis syndrome might be a potential mechanism, which is manifested as coronary thrombosis secondary to allergic reactions in patients with underlying asymptomatic coronary heart disease. We also summarize the reported AMI cases post COVID-19 vaccination, as well as overview and discuss the proposed mechanisms of AMI after COVID-19 vaccination, thus providing insights for clinicians to be aware of the possibility of AMI following COVID-19 vaccination and potential underlying mechanisms

Expression Profiles of 12 Late Embryogenesis Abundant Protein Genes from Tamarix hispida in Response to Abiotic Stress

Twelve embryogenesis abundant protein (LEA) genes (named ThLEA-1 to -12) were cloned from Tamarix hispida. The expression profiles of these genes in response to NaCl, PEG, and abscisic acid (ABA) in roots, stems, and leaves of T. hispida were assessed using real-time reverse transcriptase-polymerase chain reaction (RT-PCR). These ThLEAs all showed tissue-specific expression patterns in roots, stems, and leaves under normal growth conditions. However, they shared a high similar expression patterns in the roots, stems, and leaves when exposed to NaCl and PEG stress. Furthermore, ThLEA-1, -2, -3, -4, and -11 were induced by NaCl and PEG, but ThLEA-5, -6, -8, -10, and -12 were downregulated by salt and drought stresses. Under ABA treatment, some ThLEA genes, such as ThLEA-1, -2, and -3, were only slightly differentially expressed in roots, stems, and leaves, indicating that they may be involved in the ABA-independent signaling pathway. These findings provide a basis for the elucidation of the function of LEA genes in future work

Built-Up Area Change Detection Using Multi-Task Network with Object-Level Refinement

The detection and monitoring of changes in urban buildings, as a major place for human activities, have been considered profoundly in the field of remote sensing. In recent years, comparing with other traditional methods, the deep learning-based methods have become the mainstream methods for urban building change detection due to their strong learning ability and robustness. Unfortunately, often, it is difficult and costly to obtain sufficient samples for the change detection method development. As a result, the application of the deep learning-based building change detection methods is limited in practice. In our work, we proposed a novel multi-task network based on the idea of transfer learning, which is less dependent on change detection samples by appropriately selecting high-dimensional features for sharing and a unique decoding module. Different from other multi-task change detection networks, with the help of a high-accuracy building mask, our network can fully utilize the prior information from building detection branches and further improve the change detection result through the proposed object-level refinement algorithm. To evaluate the proposed method, experiments on the publicly available WHU Building Change Dataset were conducted. The experimental results show that the proposed method achieves F1 values of 0.8939, 0.9037, and 0.9212, respectively, when 10%, 25%, and 50% of change detection training samples are used for network training under the same conditions, thus, outperforming other methods

Dry reforming of model biogas on a Ni/SiO2 catalyst: overall performance and mechanisms of sulfur poisoning and regeneration

Carbon-neutral application of renewable biogas to valuable chemical raw materials has received much attention in sustainable areas, while sulfur poisoning remains a big problem in biogas dry reforming process. In this work, sulfur deactivation and regeneration performance of a Ni/SiO catalyst in model biogas dry reforming and related mechanisms were studied. The effects of HS content (50 and 100 ppm) and reaction temperature (700-800 °C) on biogas dry reforming were investigated. Three regeneration methods (HS feeding cessation, temperature-programmed calcination (TPC), and O activation) were applied. The results showed that the presence of HS caused server deactivation in catalytic activity, and higher HS content led to faster deactivation. The deactivation was not reversed simply by stopping HS feeding and TPC, but O activation could totally recover deactivated catalysts. The formation of NiS, detected for the first time in biogas conditioning catalytic processes, confirmed by X-ray diffraction and X-ray photoelectron spectroscopy, led to sulfur poisoning, as well as catalyst sintering and carbon deposition. This work revealed that sulfur poisoning and regeneration mechanism is the formation and elimination of NiS, and concluded that oxygen activation was the most effective method for reviving the catalytic activity, preventing sintering, and reducing carbon deposition. These findings will contribute to the industrial application of syngas production from biogas dry reforming