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Tumor-initiating cells (TICs) play an important role in tumorigenesis and development for many various tissue origin cancers including non-small cell lung cancer (NSCLC). However, the mechanism to maintain TICs in NSCLC is still largely unknown. Here, we evaluated differences of mRNA expression between parental and oncosphere cells that enriched TICs. We found that N-myc downstream regulated gene 1(NDRG1) was upregulated in oncosphere cells derived from human NSCLC cell lines and primary NSCLC cells. NDRG1 promoted stem-like properties of LTICs in NSCLC including iPSC (induced pluripotent stem cell) factors (OCT4, SOX2, KLF4, and C-MYC), the spheres-forming ability and the tumorigenicity of NSCLC. NDRG1 prevented the degradation of c-Myc through Skp2-mediated ubiquitination. NDRG1 directly interacted with Skp2, and decreased phosphorylation of Skp2 through inactivation of CDK2. Finally, we confirmed that NDRG1 was negatively correlated with survival and prognosis. Thus, our findings indicate that NDRG1 is a potential target for eradicating TICs in NSCLC. [ABSTRACT FROM AUTHOR]

After the publication of this work [1], [ABSTRACT FROM AUTHOR]

• The global features are extracted to help local features from different receptive fields for efficient feature alignment. • The interactive attention mechanism is introduced to local branch to alleviate ghosting artifacts. • The band representation network is proposed to better repair missing areas from coarse to fine. • Multiscale loss function is used to help network gradually learn to reconstruction without artifact. • The network is robust and able to produce faithful information in the regions with missing content. Ghosting artifacts due to misaligned imaging and missing content of the moving regions are major challenges of synthesizing high dynamic range (HDR) images from multiple low-dynamic range (LDR) with different exposures in dynamic scenes. Therefore, it hopes the HDR reconstruction model can align the LDRs' features and restore the missing content without artifacts. In the paper, a new dual-branch recursive band reconstruction network for high dynamic range (DRBR-HDR) is proposed to generate credible result in missing content regions, which not only uses global features as supplementary information to help local features from different receptive fields for efficient feature alignment but also designs a series of coarse-to-fine band representation to better repair missing areas in the process of recursion. In addition, we introduce an interactive attention mechanism for local branches to alleviate ghosting artifacts. The experimental results demonstrate that DRBR-HDR achieves state-of-the-art performance compared with that of the prevailing HDR reconstruction methods in various challenging scenes. Index Terms— inverse tone mapping, band reconstruction, global features, high dynamic range images. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1007/s10528-021-10182-4. Correection to: Biochemical Genetics (2022) 60:1298-1312 https://doi.org/10.1007/s10528-021-1... In this article, the tube formation assays of Figs. [Extracted from the article]

Cancer-associated fibroblasts (CAFs) play an important role in tumor formation and development by serving as the most influential stromal cells within the tumor microenvironment (TME). The communication between tumor cells and CAFs, along with the resulting impact, is more important than originally anticipated. Numerous studies have demonstrated that microRNAs (miRNAs) play an essential role in this crosstalk, and related evidence continues to emerge and advance. In addition, exosomes containing miRNAs have been found as a crucial mode of interaction between these two types of cells, with a more direct and precise role. Under the influence of exosomal miRNAs, normal fibroblasts are converted into CAFs. By doing so, CAFs can greatly promote tumor progression. Additionally, through exosomal miRNAs, activated CAFs may alter the genetic expression in tumor cells, affecting the TME and promoting malignant biological processes. Learning more about exosomal miRNAs in tumor cells and CAFs, and the intricate molecular networks that link CAFs to cancer cells, may help researchers develop more sensitive and effective cancer treatments targeting miRNAs, exosomes and CAFs, thereby giving hope to cancer patients. A comprehensive search of the literature was conducted through PubMed databases. The keywords entered for the search included: exosomes, cancer-associated fibroblasts, microRNA and cancer. This search provided information about articles published in peer-reviewed journals until 2022. Information from these articles was collected and analyzed in this review. Exosomal miRNAs can act as tumor inhibitors or tumor inducers by affecting several targets and molecular signaling pathways. MiRNAs and exosomes involved in crosstalk could have promising applications in cancer diagnosis, prognosis, and therapy. This finding about the crosstalk can help find and develop innovative miRNA-based approaches towards diagnosis, prognosis, and anti-cancer treatments. [ABSTRACT FROM AUTHOR]

Foxtail millet is not only a very useful experimental crop, hut also a fodder crop and a staple food of people who live on the marginal agricultural lands, and it supplies high-quality protein for food products and industrial materials. However, leaf rust greatly reduces foxtail millet yields in susceptible varieties when weather conditions favor rust spread and development. Therefore, it is necessary to use molecular markers detecting and marking resistance genes. Compared with other molecular markers, AFLP maker is more efficient and powerful in the study of foxtail millet. In this study, A KIP analysis of 131 F2 individuals was performed and three AFLP makers were found to he linked to the rust resistance gene, with the genetic distances of 9. 2, 9. 8 and 12.4 cM, respectively. Cloning of rust resistance genes is of great importance and meaning in studying rust resistance of foxtail millet in the future. Furthermore, we may convert specific AFLP markers into single locus PCK markers, such as sequence characterised amplified region (SCAR) market's or cleaved amplified polymorphic site (CAPS) markers. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are short, non-coding RNAs (∼22 nt) that play important roles in the pathogenesis of human diseases by negatively regulating numerous target genes at posttranscriptional level. However, the role of microRNAs in lung cancer, particularly non-small-cell lung cancer (NSCLC), has remained elusive. In this study, two microRNAs, miR-1271 and miR-628, and their predicted target genes were identified differentially expressed in NSCLC by analyzing the miRNA and mRNA expression data from NSCLC tissues and their matching normal controls. miR-1271 and its target gene HOXA5 were selected for further investigation. CCK-8 proliferation assay showed that the cell proliferation was promoted by miR-1271 in NSCLC cells, while miR-1271 inhibitor could significantly inhibited the proliferation of NSCLC cells. Interestingly, migration and invasion assay indicated that overexpression of miR-1271 could significantly promoted the migration and invasion of NSCLC cells, whereas miR-1271 inhibitor could inhibited both cell migration and invasion of NSCLC cells. Western blot showed that miR-1271 suppressed the protein level of HOXA5, and luciferase assays confirmed that miR-1271 directly bound to the 3'untranslated region of HOXA5. This study indicated indicate that miR-1271 regulates NSCLC cell proliferation and invasion, via the down-regulation of HOXA5. Thus, miR-1271 may represent a potential therapeutic target for NSCLC intervention. [ABSTRACT FROM AUTHOR]

The impact of extreme climate change on terrestrial ecosystems continues to intensify. This study was conducted to understand extreme climate–vegetation interactions under exacerbated frequency, severity, and duration of extreme climatic events. The Inner Mongolian Plateau (IMP) was selected due to its sensitive natural location, which is particularly vulnerable to climate change. Based on the Normalized Difference Vegetation Index (NDVI) and daily meteorological station data from 1982 to 2020, changes in the patterns of vegetation and extreme climate in the three ecological zones (forest, steppe, and desert steppe) of the IMP were identified. Furthermore, the effects of extreme climate on vegetation were quantified using correlation analysis and a geographical detector. The results showed that the annual NDVI of 95.1%, 50.6%, and 19.5% of the area increased significantly in the forest, steppe, and desert steppe, respectively. The Tx90p (warm days) and Tn90p (warm nights) increased significantly at the rate of 0.21 and 0.235 day·yr−1, respectively, while the Tx10p (cold days) and Tn10p (cold nights) showed a significantly decreasing trend at the rate of −0.105 and −0.117 day·yr−1. An extreme warming phenomenon was observed in all extreme temperature indices on the IMP. The results of both the correlation analysis and factor detector indicated that extreme temperature intensity and frequency greatly affected forest vegetation. In contrast, extreme precipitation intensity and frequency were relatively more important to the vegetation of the desert steppe. The lag in NDVI response to extreme temperature intensity was not less than three months in the IMP; however, extreme precipitation intensity exhibited a two-month time lag in the NDVI. This study can improve our understanding of extreme climate–vegetation interactions, provide theoretical support for disaster mitigation, and aid in understanding the ecological environment of the IMP. [ABSTRACT FROM AUTHOR]

In recent years, removing rain streaks from a single image has been a significant issue for outdoor vision tasks. In this paper, we propose a novel recursive residual atrous spatial pyramid pooling network to directly recover the clear image from rain image. Specifically, we adopt residual atrous spatial pyramid pooling (ResASPP) module which is constructed by alternately cascading a ResASPP block with a residual block to exploit multi-scale rain information. Besides, taking the dependencies of deep features across stages into consideration, a recurrent layer is introduced into ResASPP to model multi-stage processing procedure from coarse to fine. For each stage in our recursive network we concatenate the stage-wise output with the original rainy image and then feed them into the next stage. Furthermore, the negative SSIM loss and perceptual loss are employed to train the proposed network. Extensive experiments on both synthetic and real-world rainy datasets demonstrate that the proposed method outperforms the state-of-the-art deraining methods. • We propose a recursive residual atrous spatial pyramid pooling network for single image deraining. • ResASPP module is introduced to utilize the multi-scale features of rainy image, which can enlarge the receptive field. • Recursive learning is used to strengthen the model capability by multi-stage deraining processing from coarse to fine while maintain the model parameters. • Extensive experiments on both real-world and synthetic datasets demonstrate that our approach significantly outperforms state-of-the-art in image deraining task. [ABSTRACT FROM AUTHOR]

\nIntroduction: Hereditary angioedema (HAE) is a rare genetic disorder caused by deficiency or dysfunction of C1-esterase inhibitor that is characterized by recurrent episodes of bradykinin-mediated edema. Lanadelumab has been the only available first-line therapy for long-term prophylaxis (LTP) of HAE in China since its approval in 2020. The present study aimed to investigate the clinical efficacy and safety of lanadelumab for LTP in Chinese patients. Methods: A retrospective clinical data were collected for the 6 patients and used to examine the frequency of attack symptoms, disease-related loss of work days, and quality of life before and after LTP with lanadelumab. Health-related quality of life was assessed using the Dermatology Life Quality Index (DLQI) and the Angioedema Quality of Life Questionnaire (AE-QoL). Results: Lanadelumab led to reductions of 97.8% and 98.5% in the attack rate and treated attack rate, respectively. All patients exhibited significant improvements in AE-QoL and DLQI scores (100% reduction rates) during the early treatment period (4 weeks and 2 weeks, respectively) and in missed work days/year (98.9% reduction rate). The efficacy of lanadelumab remained stable during COVID-19 vaccination and infection. No serious/severe treatment-emergent adverse events occurred during lanadelumab treatment. Conclusion: This study is the first report that demonstrates the clinical efficacy of lanadelumab and safety of LTP in HAE patients from Chinese mainland. A reasonable dosage plan can ensure a quick and long-lasting protective role of lanadelumab against HAE attacks, during COVID-19 pandemic period. Hereditary angioedema (HAE) is a rare genetic disease characterized by recurring episodes of painful swelling of the subcutaneous and submucosal tissue, and its pathogenesis is due to the deficiency or dysfunction C1-esterase inhibitors. HAE attacks can affect many areas of the body, but most frequently involve the extremities, gastrointestinal tract, genitals, face, and upper airway. Swelling of the larynx can occur, with potentially fatal consequences owing to asphyxiation. Since 2020, China has had the only first-line treatment drug that can prevent HAE attacks – lanadelumab. Our study evaluated the efficacy and safety of lanadelumab by observing the 6 patients in China mainland who were the first to use it. Our research showed that lanadelumab can prevent the attack of HAE, greatly improve the quality of life of patients, and has good safety. A reasonable dosage plan can ensure stable therapeutic effects of lanadelumab. In addition, the efficacy of lanadelumab remained stable during COVID-19 vaccination and infection. [ABSTRACT FROM AUTHOR]

Background: Multi-omics technology provides a good tool to analyze the protein toxin composition and search for the potential pathogenic factors of Solenopsis invicta, under the great harm of the accelerated invasion in southern China. Methods: Species collection, functional annotation, toxin screening, and 3D modeling construction of three interested toxins were performed based on the successfully constructed transcriptome and proteome of S. invicta. Results: A total of 33,231 unigenes and 721 proteins were obtained from the constructed transcriptome and proteome, of which 9,842 (29.62%) and 4,844 (14.58%) unigenes, as well as 469 (65.05%) and 71 (99.45%) proteins were annotated against the databases of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, respectively. After comparing with the uniprot toxin database, a total of 316 unigenes and 47 proteins (calglandulin, venom allergen 3, and venom prothrombin activator hopsarin-D, etc.) were successfully screened. Conclusions: The update of annotations at the transcriptome and proteome levels presents a progression in the comprehension of S. invicta in China. We also provide a protein toxin list that could be used for further exploration of toxicity as well as its antagonistic strategy by S. invicta. [ABSTRACT FROM AUTHOR]

Saliency prediction can be regarded as the human spontaneous activity. The most effective saliency model should highly approximate the response of viewers to the perceived information. In the paper, we exploit the perception response for saliency detection and propose a heuristic framework to predict salient region. First, to find the perceptually meaningful salient regions, an orientation selectivity based local feature and a visual Acuity based global feature are proposed to jointly predict candidate salient regions. Subsequently, to further boost the accuracy of saliency map, we introduce a visual error sensitivity based operator to activate the meaningful salient regions from a local and global perspective. In addition, an adaptive fusion method based on free energy principle is designed to combine the sub-saliency maps from each image channel to obtain the final saliency map. Experimental results on five natural and emotional datasets demonstrate the superiority of the proposed method compared to twelve state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]