Nutrient scarcity is pervasive for natural microbial communities, affecting species reproduction and co-existence. However, it remains unclear whether there are general rules of how microbial species abundances are shaped by biotic and abiotic factors. Here we show that the ribosomal RNA gene operon (rrn) copy number, a genomic trait related to bacterial growth rate and nutrient demand, decreases from the abundant to the rare biosphere in the nutrient-rich coastal sediment but exhibits the opposite pattern in the nutrient-scarce pelagic zone of the global ocean. Both patterns are underlain by positive correlations between community-level rrn copy number and nutrients. Furthermore, inter-species co-exclusion inferred by negative network associations is observed more in coastal sediment than in ocean water samples. Nutrient manipulation experiments yield effects of nutrient availability on rrn copy numbers and network associations that are consistent with our field observations. Based on these results, we propose a “hunger games” hypothesis to define microbial species abundance rules using the rrn copy number, ecological interaction, and nutrient availability.

Anthropogenic climate change threatens ecosystem functioning. Soil biodiversity is essentialfor maintaining the health of terrestrial systems, but how climate change affects the richness and abundance of soil microbial communities remains unresolved. We examined the effects of warming, altered precipitation and annual biomass removal on grassland soil bacterial, fungal and protistan communities over 7 years to determine how these representative climate changes impact microbial biodiversity and ecosystem functioning. We show that experimental warming and the concomitant reductions in soil moisture played the predominant role in shaping microbial biodiversity by decreasing the richness of bacteria (9.6%), fungi (14.5%), and protists (7.5%). Our results also show positive associations between microbial biodiversity and ecosystem functional processes such as gross primary productivity and microbial biomass. We conclude that the detrimental effects of biodiversity loss might be more severe in a warmer world. MAINBiodiversity, the variety of genes, species, and ecosystems which constitute life on our planet 1 , is dramatically affected by human alterations of global environment 2 . Biodiversity underscores healthy ecosystem functions and assures the production of essential goods, services, and benefits to society, such as climate regulation, landscape stability, fibers, and food production 1 . However, such benefits are threatened by the unprecedented biodiversity loss 3,4 caused by anthropogenic global environmental changes like climate warming, altered precipitation patterns, and land use changes 5 . Studies demonstrate that biodiversity loss impairs the functioning of natural ecosystems * *

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Gefitinib has been widely used in the first‐line treatment of advanced EGFR‐mutated non‐small‐cell lung cancer (NSCLC). However, many NSCLC patients will acquire resistance to gefitinib after 9‐14 months of treatment. This study revealed that Krüppel‐like factor 4 (KLF4) contributes to the formation of gefitinib resistance in c‐Met‐overexpressing NSCLC cells. We observed that KLF4 was overexpressed in c‐Met‐overexpressing NSCLC cells and tissues. Knockdown of KLF4 increased tumorigenic properties in gefitinib‐resistant NSCLC cell lines without c‐Met overexpression, but it reduced tumorigenic properties and increased gefitinib sensitivity in gefitinib‐resistant NSCLC cells with c‐Met overexpression, whereas overexpression of KLF4 reduced gefitinib sensitivity in gefitinib‐sensitive NSCLC cells. Furthermore, Western blot analysis revealed that KLF4 contributed to the formation of gefitinib resistance in c‐Met‐overexpressing NSCLC cells by inhibiting the expression of apoptosis‐related proteins under gefitinib treatment and activating the c‐Met/Akt signaling pathway by decreasing the inhibition of β‐catenin on phosphorylation of c‐Met to prevent blockade by gefitinib. In summary, this study's results suggest that KLF4 is a promising candidate molecular target for both prevention and therapy of NSCLC with c‐Met overexpression.

The Full-disk vectorMagnetoGraph (FMG) instrument will carry out polarization observations at one wavelength position of the Fe I 5324.179 °A spectral line. This paper describes how to choose this single wavelength position, the relevant data-processing and the magnetic field calibrations based on the measured polarization signals at one single wavelength position. It is found that solar radial Doppler velocity, which can cause the spectral line to shift, is a disadvantageous factor for the linear calibration at one wavelength position. Observations at two symmetric wavelength positionsmay significantly reduce the wavelength shift effect (∼ 75%), but simulations show that such polarization signals located at the solar limbs (e.g., beyond the longitude range of ±30°) are not free from the effect completely. In future work, we plan to apply machine learning techniques to calibrate vector magnetic fields, or employ full Stokes parameter profile inversion techniques to obtain accurate vector magnetic fields, in order to complement the linear calibration at the single wavelength position.

The paper presents a reliable method using deep learning to recognize solar filaments in Hα full-disk solar images automatically. This method cannot only identify filaments accurately but also minimize the effects of noise points of the solar images. Firstly, a raw filament dataset is set up, consisting of tens of thousands of images required for deep learning. Secondly, an automated method for solar filament identification is developed using the U-Net deep convolutional network. To test the performance of the method, a dataset with 60 pairs of manually corrected Hα images is employed. These images are obtained from the Big Bear Solar Observatory/Full-Disk H-alpha Patrol Telescope (BBSO/FDHA) in 2013. Cross-validation indicates that the method can efficiently identify filaments in full-disk Hα images.

Background The roles of Polypyrimidine tract-binding protein 3 (PTBP3) in regulating lung squamous cell carcinoma (LUSC) cells progression is unclear. The aim of this study was to investigate the role of PTBP3 in LUSC. Methods Expression and survival analysis of PTBP3 was firstly investigated using TCGA datasets. Quantitative reverse transcription PCR and Western blot were performed to detect PTBP3 expression in clinical samples. Moreover, cell counting kit 8 (CCK-8) assays, colony formation assays and in vivo tumor formation assays were used to examine the effects of PTBP3 on LUSC cell proliferation. RNA-sequence and analysis explores pathways regulated by PTBP3.Flow cytology was used analyzed cell cycle. Cell cycle-related markers were analyzed by Western blot. Results PTBP3 was found to be overexpressed in LUSC tissues compared with normal tissues. High PTBP3 expression was significantly correlated with poor prognosis. In vitro and vivo experiments demonstrated that PTBP3 knockdown caused a significant decrease in the proliferation rate of cells. Bioinformatics analysis showed that PTBP3 involved in cell cycle pathway regulation in LUSC. Furthermore, PTBP3 knockdown arrested cell cycle progression at S phase via decreasing CDK2/Cyclin A2 complex. In addition, downregulation of PTBP3 significantly decreased the expression of CDC25A. Conclusions Our results suggest that PTBP3 regulated LUSC cell proliferation via cell cycle and might be a potential target for molecular therapy of LUSC.

Osimertinib is a third-generation, irreversible epidermal growth factor RTK inhibitor (EGFR-TKI) that selectively suppresses both EGFRsensitizing mutations and the T790M resistance mutation. 1 A recent clinical trial demonstrated that, compared with first-generation EGFR-TKIs in first-line clinical treatment of EGFR mutation-positive NSCLC patients, osimertinib was associated with a longer progression-free survival and promising overall survival. 1 Based on the encouraging results of the FLAURA trial, first-line treatment with osimertinib has become a favorable standard in therapies for NSCLC patients who carry the EGFR-positive mutation. Nevertheless, acquired resistance to osimertinib is also inevitable. Based on preclinical and clinical studies, various mechanisms of osimertinib resistance