Case Report: A rare case of non-small cell lung cancer with STRN-ALK fusion in a patient in very poor condition treated with first-line ensartinib

Several cases of STRN-ALK fusion have been reported, and some anaplastic lymphoma kinase (ALK) inhibitors have been shown to be effective for treatment. Nevertheless, no cases of COVID-19 leading to heart failure and respiratory failure have been reported in people older than 70 years treated with ALK inhibitors. The present case report describes a 70-year-old patient with usual chronic obstructive pulmonary disease, diabetes, depression, and carotid plaque disease. Next-generation sequencing of tissue obtained by puncture biopsy revealed a STRN-ALK mutation accompanied by a TP53 mutation. The patient was treated with ensartinib and developed COVID-19 leading to heart failure and respiratory failure; nevertheless, he had a good clinical outcome and exhibited high treatment tolerability

Efficient photocatalytic hydrogen evolution over carbon supported antiperovskite cobalt zinc nitride

Photocatalytic solar to chemical energy conversion is an important energy conversion process but suffer from low efficiency. Thus, development of efficient photocatalytic system using earth-abundant elements with low costs is highly desirable. Here, antiperovskite cobalt zinc nitride has been synthesized and coupled with carbon black (Co3ZnN/C) for visible light driven hydrogen production in an Eosin Y-sensitized system. Replacement of cobalt atom by zinc atom leads to an improved charge transfer kinetics and catalytic properties compared with Co4N. Density functional theory (DFT) calculations further reveal the adjusted electronic structure of Co3ZnN by zinc atom introducing. The lower antibonding energy states of Co3ZnN are beneficial for the hydrogen desorption. Moreover, carbon black as support effectively reduces the particle size of Co3ZnN and benefits to the electron storage and adsorption capabilities. The optimal Co3ZnN/C catalysts exhibit the H-2 evolution rate of 15.4 mu mol mg(-1) h(-1),which is over 6 times higher than that of monometallic Co4N. It is even greater than those of most of Eosin Y-sensitized systems

Near infrared spectroscopy coupled with radial basis function neural network for at-line monitoring of Lactococcus lactis subsp. fermentation

AbstractIn our previous work, partial least squares (PLSs) were employed to develop the near infrared spectroscopy (NIRs) models for at-line (fast off-line) monitoring key parameters of Lactococcus lactis subsp. fermentation. In this study, radial basis function neural network (RBFNN) as a non-linear modeling method was investigated to develop NIRs models instead of PLS. A method named moving window radial basis function neural network (MWRBFNN) was applied to select the characteristic wavelength variables by using the degree approximation (Da) as criterion. Next, the RBFNN models with selected wavelength variables were optimized by selecting a suitable constant spread. Finally, the effective spectra pretreatment methods were selected by comparing the robustness of the optimum RBFNN models developed with pretreated spectra. The results demonstrated that the robustness of the optimal RBFNN models were better than the PLS models for at-line monitoring of glucose and pH of L. lactis subsp. fermentation

Tuning the Magnetism in Ultrathin CrxTey Films by Lattice Dimensionality

Two-dimensional (2D) magnetic transition metal compounds with atomic thickness exhibit intriguing physics in fundamental research and great potential for device applications. Understanding the correlations between their macrosopic magnetic properties and the dimensionality of microscopic magnetic exchange interactions are valuable for the designing and applications of 2D magnetic crystals. Here, using spin-polarized scanning tunneling microscopy, magnetization and magneto-transport measurements, we identify the zigzag-antiferromagnetism in monolayer CrTe2, incipient ferromagnetism in bilayer CrTe2, and robust ferromagnetism in bilayer Cr3Te4 films. Our density functional theory calculations unravel that the magnetic ordering in ultrathin CrTe2 is sensitive to the lattice parameters, while robust ferromagnetism with large perpendicular magnetic anisotropy in Cr3Te4 is stabilized through its anisotropic 3D magnetic exchange interactions

Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery

Real-time monitoring of canopy chlorophyll content is significant in understanding crop growth status and guiding precision agricultural management. Remote sensing methods have demonstrated great potential in this regard. However, the spatiotemporal heterogeneity of chlorophyll content within crop canopies poses challenges to the accuracy and stability of remote sensing estimation models. Hence, this study aimed to develop a novel method for estimating canopy chlorophyll content (represented by SPAD values) in maize (Zea mays L.) canopies. Firstly, we investigated the spatiotemporal distribution patterns of maize canopy SPAD values under varying nitrogen application rates and different growth stages. The results revealed a non-uniform, “bell-shaped” curve distribution of maize canopy SPAD values in the vertical direction. Nitrogen application significantly influenced the distribution structure of SPAD values within the canopy. Secondly, we achieved satisfactory results by fitting the Lorentz peak distribution function to the SPAD values of different leaf positions in maize. The fitting performance, evaluated using R2 and RMSE, ranged from 0.69 to 0.98 and 0.45 to 3.59, respectively, for the year 2021, and from 0.69 to 0.77 and 2.38 to 6.51, respectively, for the year 2022.Finally, based on the correlation between canopy SPAD values and vegetation indices (VIs) at different growth stages, we identified the sensitive leaf positions for the selected CCCI (Canopy Chlorophyll Index) in each growth stage. The 6th (r = 0.662), 4th (r = 0.816), 12th (r = 0.722), and 12th (r = 0.874) leaf positions exhibited the highest correlations. Compared to the estimation model using canopy wide SPAD values, the model based on sensitive leaf positions showed improved accuracy, with increases of 34%, 3%, 20%, and 3% for each growth stage, respectively. In conclusion, the findings of this study contribute to the enhancement of chlorophyll content estimation models in crop canopies and provide valuable insights for the integration of crop growth models with remote sensing methods

Highly Stable Garnet Fe2Mo3O12 Cathode Boosts the Lithium–Air Battery Performance Featuring a Polyhedral Framework and Cationic Vacancy Concentrated Surface

Lithium–air batteries (LABs), owing to their ultrahigh theoretical energy density, are recognized as one of the next-generation energy storage techniques. However, it remains a tricky problem to find highly active cathode catalyst operating within ambient air. In this contribution, a highly active Fe2Mo3O12 (FeMoO) garnet cathode catalyst for LABs is reported. The experimental and theoretical analysis demonstrate that the highly stable polyhedral framework, composed of FeO octahedrons and MO tetrahedrons, provides a highly effective air catalytic activity and long-term stability, and meanwhile keeps good structural stability. The FeMoO electrode delivers a cycle life of over 1800 h by applying a simple half-sealed condition in ambient air. It is found that surface-rich Fe vacancy can act as an O2 pump to accelerate the catalytic reaction. Furthermore, the FeMoO catalyst exhibits a superior catalytic capability for the decomposition of Li2CO3. H2O in the air can be regarded as the main contribution to the anode corrosion and the deterioration of LAB cells could be attributed to the formation of LiOH·H2O at the end of cycling. The present work provides in-depth insights to understand the catalytic mechanism in air and constitutes a conceptual breakthrough in catalyst design for efficient cell structure in practical LABs

Investigating the genetic basis of maize ear characteristics: a comprehensive genome-wide study utilizing high-throughput phenotypic measurement method and system

The morphology of maize ears plays a critical role in the breeding of new varieties and increasing yield. However, the study of traditional ear-related traits alone can no longer meet the requirements of breeding. In this study, 20 ear-related traits, including size, shape, number, and color, were obtained in 407 maize inbred lines at two sites using a high-throughput phenotypic measurement method and system. Significant correlations were found among these traits, particularly the novel trait ear shape (ES), which was correlated with traditional traits: kernel number per row and kernel number per ear. Pairwise comparison tests revealed that the inbred lines of tropical-subtropical were significantly different from other subpopulations in row numbers per ear, kernel numbers per ear, and ear color. A genome-wide association study identified 275, 434, and 362 Single nucleotide polymorphisms (SNPs) for Beijing, Sanya, and best linear unbiased prediction scenarios, respectively, explaining 3.78% to 24.17% of the phenotypic variance. Furthermore, 58 candidate genes with detailed functional descriptions common to more than two scenarios were discovered, with 40 genes being associated with color traits on chromosome 1. After analysis of haplotypes, gene expression, and annotated information, several candidate genes with high reliability were identified, including Zm00001d051328 for ear perimeter and width, zma-MIR159f for ear shape, Zm00001d053080 for kernel width and row number per ear, and Zm00001d048373 for the blue color channel of maize kernels in the red-green-blue color model. This study emphasizes the importance of researching novel phenotypic traits in maize by utilizing high-throughput phenotypic measurements. The identified genetic loci enrich the existing genetic studies related to maize ears

Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma

BackgroundN6-methyladenosine (m6A) RNA modification is vital for cancers because methylation can alter gene expression and even affect some functional modification. Our study aimed to analyze m6A RNA methylation regulators and m6A-related genes to understand the prognosis of early lung adenocarcinoma.MethodsThe relevant datasets were utilized to analyze 21 m6A RNA methylation regulators and 5,486 m6A-related genes in m6Avar. Univariate Cox regression analysis, random survival forest analysis, Kaplan–Meier analysis, Chi-square analysis, and multivariate cox analysis were carried out on the datasets, and a risk prognostic model based on three feature genes was constructed.ResultsRespectively, we treated GSE31210 (n = 226) as the training set, GSE50081 (n = 128) and TCGA data (n = 400) as the test set. By performing univariable cox regression analysis and random survival forest algorithm in the training group, 218 genes were significant and three prognosis-related genes (ZCRB1, ADH1C, and YTHDC2) were screened out, which could divide LUAD patients into low and high-risk group (P < 0.0001). The predictive efficacy of the model was confirmed in the test group GSE50081 (P = 0.0018) and the TCGA datasets (P = 0.014). Multivariable cox manifested that the three-gene signature was an independent risk factor in LUAD. Furthermore, genes in the signature were also externally validated using the online database. Moreover, YTHDC2 was the important gene in the risk score model and played a vital role in readers of m6A methylation.ConclusionThe findings of this study suggested that associated with m6A RNA methylation regulators and m6A-related genes, the three-gene signature was a reliable prognostic indicator for LUAD patients, indicating a clinical application prospect to serve as a potential therapeutic target

Weighted Gene Co-expression Network Analysis for RNA-Sequencing Data of the Varicose Veins Transcriptome

ObjectiveVaricose veins are a common problem worldwide and can cause significant impairments in health-related quality of life, but the etiology and pathogenesis remain not well defined. This study aims to elucidate transcriptomic regulations of varicose veins by detecting differentially expressed genes, pathways and regulator genes.MethodsWe harvested great saphenous veins (GSV) from patients who underwent coronary artery bypass grafting (CABG) and varicose veins from conventional stripping surgery. RNA-Sequencing (RNA-Seq) technique was used to obtain the complete transcriptomic data of both GSVs from CABG patients and varicose veins. Weighted Gene Co-expression network analysis (WGCNA) and further analyses were then carried out with the aim to elucidate transcriptomic regulations of varicose veins by detecting differentially expressed genes, pathways and regulator genes.ResultsFrom January 2015 to December 2016, 7 GSVs from CABG patients and 13 varicose veins were obtained. WGCNA identified 4 modules. In the brown module, gene ontology (GO) analysis showed that the biological processes were focused on response to stimulus, immune response and inflammatory response, etc. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that the biological processes were focused on cytokine-cytokine receptor interaction and TNF signaling pathway, etc. In the gray module, GO analysis showed that the biological processes were skeletal myofibril assembly related. The immunohistochemistry staining showed that the expression of ASC, Caspase-1 and NLRP3 were increased in GSVs from CABG patients compared with varicose veins. Histopathological analysis showed that in the varicose veins group, the thickness of vascular wall, tunica intima, tunica media and collagen/smooth muscle ratio were significantly increased, and that the elastic fiber/internal elastic lamina ratio was decreased.ConclusionThis study shows that there are clear differences in transcriptomic information between varicose veins and GSVs from CABG patients. Some inflammatory RNAs are down-regulated in varicose veins compared with GSVs from CABG patients. Skeletal myofibril assembly pathway may play a crucial role in the pathogenesis of varicose veins. Characterization of these RNAs may provide new targets for understanding varicose veins diagnosis, progression, and treatment