Proteomics analysis of serum from thymoma patients

Thymoma is the most common malignant tumor in thymic epithelial tumors (TETS). This study aimed to identify the changes in serum proteomics in patients with thymoma. Proteins were extracted from twenty patients with thymoma serum and nine healthy controls and prepared for mass spectrometry (MS) analysis. Data independent acquisition (DIA) quantitative proteomics technique was used to examine the serum proteome. Differential proteins of abundance changes in the serum were identified. Bioinformatics was used to examine the differential proteins. Functional tagging and enrichment analysis were conducted using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. The string database was used to assess the interaction of different proteins. In all, 486 proteins were found in all samples. There were differences in 58 serum proteins between patients and healthy blood donors, 35 up-regulated and 23 down-regulated. These proteins are primarily exocrine and serum membrane proteins involved in controlling immunological responses and antigen binding, according to GO functional annotation. KEGG functional annotation showed that these proteins play a significant role in the complement and coagulation cascade and the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signal pathway. Notably, the KEGG pathway (complement and coagulation cascade) is enriched, and three key activators were up-regulated: von willebrand factor (VWF), coagulation factor v (F5) and vitamin k-dependent protein c (PC). Protein-protein interaction (PPI) analysis showed that six proteins ((VWF, F5, thrombin reactive protein 1 (THBS1), mannose-binding lectin-associated serine protease 2 (MASP2), apolipoprotein B (APOB), and apolipoprotein (a) (LPA)) were up-regulated and two proteins (Metalloproteinase inhibitor 1(TIMP1), ferritin light chain (FTL)) were down-regulated. The results of this study showed that several proteins involved in complement and coagulation cascades were up-regulated in the serum of patients.

Design, Synthesis, and Antifungal Activities of Phenylpyrrole Analogues Based on Alkaloid Lycogalic Acid

Plant diseases caused by pathogenic fungi seriously affect the yield and quality of crops, cause huge economic losses, and pose a considerable threat to global food security. Phenylpyrrole analogues were designed and synthesized based on alkaloid lycogalic acid. All target compounds were characterized by 1H NMR, 13C NMR, and HRMS. Their antifungal activities against seven kinds of phytopathogenic fungi were evaluated. The results revealed that most compounds had broad-spectrum fungicidal activities at 50 μg/mL; 14 compounds displayed more than 60% fungicidal activities against Rhizoctonia cerealis and Sclerotinia sclerotiorum, and in particular, the fungicidal activities of compounds 8g and 8h against Rhizoctonia cerealis were more than 90%, which could be further developed as lead agents for water-soluble fungicides. The molecular docking results indicate that compounds 8g and 8h can interact with 14α-demethylase (RcCYP51) through hydrogen bonding with strong affinity.

Characterization of the WRKY family transcription factors in Astragalus membranaceus and their expression under drought stress

Drought and other abiotic stressors exert significant impacts on plant growth, development, and yield. WRKY transcription factors (TFs) are pivotal in regulating plant responses to such stresses. This study conducted a genome-wide identification of the Astragalus membranaceus (A. membranaceus) WRKY TF family, aiming at providing essential stress-tolerance genes for molecular breeding in A. membranaceus. Using bioinformatics approaches, including phylogenetic analysis, gene structure analysis, protein conserved motif prediction, and promoter cis-acting element examination, we identified 76 WRKY TF family members unevenly distributed across eight chromosomes. Phylogenetic analysis categorized the 76 AmWRKY proteins into three major classes: 14 in Class I, 52 in Class II, and 10 in Class III. Analysis of conserved structural domains revealed that similarities among domains of the same class AmWRKYs, with a predominance of members containing the conserved "WRKYGQK" heptapeptide domain and zinc finger structure, despite a few members had conserved domain variants. Gene structure analysis demonstrated that AmWRKY genes include 1-6 exons and 1-5 introns. GO and KEGG analyses revealed the differentially expressed WRKY genes are primarily transcription regulators involved in stress response pathways, with significant enrichment in DNA-binding activities, nuclear localization, and plant-pathogen/MAPK signaling. Transcriptome and qRT-PCR analyses indicated that several WRKY TFs, including AmWRKY8, were involved in the response to drought stress. Furthermore, it was confirmed that AmWRKY8 is localized exclusively in the nucleus and possesses transcriptional activation activity. Protein interaction analysis revealed that AmWRKY8 coordinates drought stress responses by interacting with key regulators of hormone signaling (AtWRKY70, ERF6), mitochondrial stress (NAC017), and developmental processes (HBI1). These findings are useful in further investigations into the regulatory role of this this TF in abiotic stress responses.

BTK and YKL-40 Levels and Their Association with Acute AQP4-IgG-Positive Neuromyelitis Optica Spectrum Disorder

This study investigated the potential correlation between BTK/YKL-40 levels and the severity of AQP4-IgG + NMOSD, aiming to identify biomarkers for disease monitoring and treatment assessment. Plasma YKL-40 expression was measured in 135 AQP4-IgG + NMOSD patients using ELISA. Patients were categorized into pre- and post-IVMP treatment acute phases, as well as during remission, with a healthy control group included. BTK and NF-κB mRNA levels in PBMCs were detected via q-PCR, and BTK/P-BTK protein expression was assessed using Western blotting. Disability was evaluated using the EDSS score, and clinical characteristics were evaluated alongside laboratory tests. Acute-phase NMOSD patients receiving pre-IVMP therapy presented significantly elevated plasma YKL-40 concentrations compared with those of post-treatment patients, patients in remission, and healthy controls. Additionally, these patients presented significantly higher levels of PBMC BTK mRNA, NF-κB mRNA, BTK, and P-BTK protein expression than remission patients and healthy controls. Plasma YKL-40 levels and PBMC BTK/P-BTK protein levels were positively correlated with EDSS scores. The plasma YKL-40 concentration significantly contributes to disease severity and serves as an independent risk factor for acute NMOSD. Elevated BTK, P-BTK, NF-κB, and YKL-40 levels were observed in acute-phase AQP4-IgG + NMOSD patients. These biomarkers are related to disease activity and may predict treatment efficacy. There is a connection among YKL-40, BTK, and P-BTK levels and disease severity, suggesting their potential involvement in the pathogenic mechanism of AQP4-IgG + NMOSD.

Identification of Anoikis-Related Genes in Gastric Cancer: Bioinformatics and Experimental Validation

INTRODUCTION

Distant metastasis is the main reason for the poor prognosis of gastric cancer, and anoikis refers to the cell death caused when cells detach from the extracellular matrix or adhere in incorrect locations, playing an important role in the distant metastasis of gastric cancer.

METHODS

Download the TCGA-STAD dataset and the anoikis gene set, and filter out the differentially expressed anoikis genes. Perform consensus clustering of gastric cancer samples, and conduct Weighted Gene Correlation Network Analysis (WGCNA), enrichment analysis, and immune infiltration analysis for the expression characteristics of each subtype, while also filtering the genes with differential expression between subtypes. Additionally, through COX survival analysis, identify anoikis genes related to gastric cancer prognosis and establish a nomogram. Finally, validate the differentially expressed gene CYP1B1 in vivo and in vitro through clinical samples, cell culture, and the establishment of an anoikis model.

RESULTS

Three subtypes of gastric cancer with anoikis genes were identified, each exhibiting different expression characteristics, biological pathways, and immune cell infiltration. The abundance of activated NK cells, memory B cells, and M2 macrophages showed significant differences among the three subtypes. We screened four differentially expressed gene sets and five genes (CYP1B1, EQTN, NRXN2, TBC1D3E, TCEAL5) among the three subtypes. Through survival analysis, we identified 33 independent prognostic genes and constructed a nomogram, with calibration curves indicating good consistency. Finally, we selected CYP1B1 for experimental validation, and in vivo and in vitro experiments demonstrated that CYP1B1 is highly expressed in gastric cancer, participates in the resistance to cell death in gastric cancer cells, and promotes the invasion, migration, and tumor progression of gastric cancer cells.

CONCLUSION

The expression patterns of subtypes based on differentially expressed genes related to anoikis in gastric cancer vary, providing theoretical support for the future of personalized treatment for gastric cancer.

The association between DNA methylation and human height and a prospective model of DNA methylation-based height prediction

As a vital anthropometric characteristic, human height information not only helps to understand overall developmental status and genetic risk factors, but is also important for forensic DNA phenotyping. We utilized linear regression analysis to test the association between each CpG probe and the height phenotype. Next, we designed a methylation sequencing panel targeting 959 CpGs and subsequent height inference models were constructed for the Chinese population. A total of 11,730 height-associated sites were identified. By employing KPCA and deep neural networks, a prediction model was developed, of which the cross-validation RMSE, MAE and R2 were 5.62 cm, 4.45 cm and 0.64, respectively. Genetic factors could explain 39.4% of the methylation level variance of sites used in the height inference models. Collectively, we demonstrated an association between height and DNA methylation status through an EWAS analysis. Targeted methylation sequencing of only 959 CpGs combined with deep learning techniques could provide a model to estimate human height with higher accuracy than SNP-based prediction models.

AtVQ25 promotes salicylic acid-related leaf senescence by fine-tuning the self-repression of AtWRKY53

Most mechanistic details of chronologically ordered regulation of leaf senescence are unknown. Regulatory networks centered on AtWRKY53 are crucial for orchestrating and integrating various senescence-related signals. Notably, AtWRKY53 binds to its own promoter and represses transcription of AtWRKY53, but the biological significance and mechanism underlying this self-repression remain unclear. In this study, we identified the VQ motif-containing protein AtVQ25 as a cooperator of AtWRKY53. The expression level of AtVQ25 peaked at mature stage and was specifically repressed after the onset of leaf senescence. AtVQ25-overexpressing plants and atvq25 mutants displayed precocious and delayed leaf senescence, respectively. Importantly, we identified AtWRKY53 as an interacting partner of AtVQ25. We determined that interaction between AtVQ25 and AtWRKY53 prevented AtWRKY53 from binding to W-box elements on the AtWRKY53 promoter and thus counteracted the self-repression of AtWRKY53. In addition, our RNA-sequencing data revealed that the AtVQ25-AtWRKY53 module is related to the salicylic acid (SA) pathway. Precocious leaf senescence and SA-induced leaf senescence in AtVQ25-overexpressing lines were inhibited by an SA pathway mutant, atsid2, and NahG transgenic plants; AtVQ25-overexpressing/atwrky53 plants were also insensitive to SA-induced leaf senescence. Collectively, we demonstrated that AtVQ25 directly attenuates the self-repression of AtWRKY53 during the onset of leaf senescence, which is substantially helpful for understanding the timing of leaf senescence onset modulated by AtWRKY53.

Quantitative calculation of static load in deep main roadway and its application in dynamic prevention and control of rockburst

In order to solve the problem of rockburst in deep coal mining roadway, the pattern of how the static load impacts the rockburst disaster was studied, and the occurrence mechanism of rockburst was revealed after analyzing relevant cases in mining roadway in recent years. The mechanical model for calculating the strength of coal pillar between roadways, coal pillar between roadway and stop mining line, and surrounding rocks is set up. A method for regulating, controlling and preventing the rockburst in deep roadway is proposed based on the static load calculation. The results show that the possibility of the deep shaft impact can be reduced after decreasing surrounding rock stress by the static load regulation and increasing the surrounding rock strength by the roadway position control. The research results have been applied to a certain mine in Shaanxi. According to the factors causing the ground pressure disasters in the mine road, adjustments were made to the position, direction, and protection pillars of the panel roadway at the design stage, which effectively prevented the rockburst from happening and ensured the safe production of the mine.

Comparison study between nitrate and sulfate aerosols and their coating effect on the scattering properties of mineral aerosol

The existing numerical models generally employ sulfate instead of nitrate to simulate the scattering properties of aerosol, the corresponding radiative deviation needs to be evaluated urgently. Moreover, the sophisticated mixture of nitrate, sulfate, and mineral particles is formed through a series of chemical reactions, which makes it extremely challenging to understand the scattering properties of atmospheric aerosols. In this study, the core-shell ellipsoid model is used to flexibly characterize the morphology and mixed structures of nitrate, sulfate, and mineral in the fine mode radius range. The T-matrix method is used to compare the scattering properties of nitrate, sulfate, and mineral within different morphologies and mixing states at four selected wavelengths (0.44, 0.675, 0.87, and 1.02 μm). The results show that the difference of mean extinction efficiency factor (< Qe >) and mean single scattering albedo (< ω >) between nitrate and sulfate-containing particles is very small, mainly within 2%. However, their mean scattering phase function P11(θ) is quite different. The difference of forward scattering phase function P11(0) is up to 7%, while the difference of backward scattering phase function P11(π) can reach more than 25%. Overall, particle morphology and incident wavelength regulate the value of the optical parameters, whereas the coatings on the mineral play a more important role in drifting, but the differences between nitrate- and sulfate-containing particles are still very pronounced.

The effectiveness of vasodilators on chronic obstructive pulmonary disease: A systematic review and meta-analysis

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a complex progressive disease. Some vasodilators have been reported with therapeutic potential to protect vascular function therefore may delay the progression of COPD.

METHODS

We searched PubMed, Embase, Cochrane Library, Web of Science, OVID and Clinicaltrials.gov database for eligible randomized controlled trials (RCTs) published before January 1, 2024. RCTs which treatment with vasodilators to COPD patients were included. Gas-blood exchange indicators were the primary outcomes, and ventilation function and quality of life indicators were the secondary outcomes. Mean differences with 95% confidence intervals were extracted. Subgroup analysis of vasodilator category and COPD complicated with or without pulmonary hypertension (PH) were performed. The risk of bias was assessed using Cochrane risk of bias tool, and the meta-analysis was conducted.

RESULTS

Twenty studies with a total sample size of 986 were included. The results showed that the 2 types of drugs in vasodilators included PDE-5 inhibitors could improve DLCO (MD = 6.56 [95% CI (1.74, 11.39)], P = .008) and iNO could reduce PaCO2 (MD = -0.10 [95% CI (-0.17, -0.03)], P = .006). Vasodilators could reduce PaCO2 in COPD complicated with PH (COPD-PH) (MD = -0.10 [95% CI (-0.17, -0.03)], P = .006). There were no statistically significant differences in FEV1 (MD = 0.02 [95% CI (-0.11, 0.16)], P = .74), FEV1% predicted (MD = 0.07 [95% CI (-1.90, 2.05)], P = .94), FEV1/FVC (MD = 0.70 [95% CI (-4.02, 5.42)], P = .77) and VE/VCO2 (MD = -0.17 [95% CI (-2.39, 2.05)], P = .88) levels. The total SGRQ score was significantly lower in vasodilator groups (MD = -5.53 [95% CI (-9.81, -1.24)], P = .01).

CONCLUSIONS

The therapeutic effects of vasodilators for COPD are controversial. In this meta-analysis, vasodilators have benefits in improving gas-blood exchange function and quality of life in COPD patients. However, vasodilators may have a limited capacity to improve pulmonary function.

Multimode Fiber Specklegram Sensor for Multi-Position Loads Recognition Using Traversal Occlusion

Since an MMF-based distributed sensor requires the simultaneous measurement of multiple perturbation positions and their intensities, the collection of a large amount of specklegram data is time consuming and challenging for recognizing multiple perturbations. To address this issue, we propose a novel approach to recognize multi-position load using an MMF specklegram sensor, supported by theoretical analysis and experimental verification. Our study introduces a construction method for a multi-variable, multi-class, one-shot specklegram dataset, significantly enhancing the sample diversity for more perturbation positions and intensities in an MMF-distributed sensor recognition model. We theoretically derive the mathematical model of total local intensity for each region and investigate its sensitivity to the external perturbations. Based on these theoretical analyses, this paper proposes a specklegram traversal occlusion data augmentation with a shallow convolutional neural network (CNN) model to mitigate overfitting in specklegram datasets. Experimental validation using a multi-position load-recognition MMF demonstrates that our approach achieves nearly 100% accuracy in simultaneously recognized load positions and its magnitudes across up to 1545 distinct load forms. Furthermore, the shallow CNN model exhibits superior training efficiency and stability compared with the existing MMF sensing models. This work provides a proof of concept of a distributed sensor based on an MMF specklegram sensor, highlighting its potential for high-resolution distributed measurements under the diverse external perturbations. Our method represents a significant advancement in this field, offering a cost-effective and efficient solution for distributed sensing applications.

Identification and validation of a novel predictive signature based on hepatocyte-specific genes in hepatocellular carcinoma by integrated analysis of single-cell and bulk RNA sequencing

BACKGROUND

Hepatocellular carcinoma represents a significant global burden in terms of cancer-related mortality, posing a substantial risk to human health. Despite the availability of various treatment modalities, the overall survival rates for patients with hepatocellular carcinoma remain suboptimal. The objective of this study was to explore the potential of novel biomarkers and to establish a novel predictive signature utilizing multiple transcriptome profiles.

METHODS

The GSE115469 and CNP0000650 cohorts were utilized for single cell analysis and gene identification. The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets were utilized in the development and evaluation of a predictive signature. The expressions of hepatocyte-specific genes were further validated using the GSE135631 cohort. Furthermore, immune infiltration results, immunotherapy response prediction, somatic mutation frequency, tumor mutation burden, and anticancer drug sensitivity were analyzed based on various risk scores. Subsequently, functional enrichment analysis was performed on the differential genes identified in the risk model. Moreover, we investigated the expression of particular genes in chronic liver diseases utilizing datasets GSE135251 and GSE142530.

RESULTS

Our findings revealed hepatocyte-specific genes (ADH4, LCAT) with notable alterations during cell maturation and differentiation, leading to the development of a novel predictive signature. The analysis demonstrated the efficacy of the model in predicting outcomes, as evidenced by higher risk scores and poorer prognoses in the high-risk group. Additionally, a nomogram was devised to forecast the survival rates of patients at 1, 3, and 5 years. Our study demonstrated that the predictive model may play a role in modulating the immune microenvironment and impacting the anti-tumor immune response in hepatocellular carcinoma. The high-risk group exhibited a higher frequency of mutations and was more likely to benefit from immunotherapy as a treatment option. Additionally, we confirmed that the downregulation of hepatocyte-specific genes may indicate the progression of hepatocellular carcinoma and aid in the early diagnosis of the disease.

CONCLUSION

Our research findings indicate that ADH4 and LCAT are genes that undergo significant changes during the differentiation of hepatocytes into cancer cells. Additionally, we have created a unique predictive signature based on genes specific to hepatocytes.

Genetic Associations of ACOX2 Gene with Milk Yield and Composition Traits in Chinese Holstein Cows

In our previous studies on the liver proteome of Holstein cows, the acyl-CoA oxidase 2 (ACOX2) gene was identified as a promising candidate for milk traits, being involved in the processes of fatty acid metabolism and bile acid formation. Herein, we evaluated its genetic effects on milk production traits in 922 Chinese Holstein cows. By sequencing the entire coding region and 2000 bp of the 5' and 3' flanking sequences of the ACOX2 gene, we identified a total of five SNPs, including one SNP in the 5' UTR, one in intron 5, and three in the 3' flanking region. Using an animal model, we found that the SNPs rs109066086, rs109665171, and rs454339362 were significantly associated with at least one of the milk production traits, including 305-day milk yield, milk fat yield, milk protein yield, milk fat percentage, and milk protein percentage in the first lactation (p ≤ 4.03 × 10-2). And in the second lactation, all five SNPs were significantly associated with at least three of the milk production traits (p ≤ 1.17 × 10-2). We also found that in the second lactation, the SNP rs209677248 had a high phenotypic variance rate for milk protein percentage, with a value of 4.90%. With Haploview 4.2, it was observed that the four SNPs formed two haplotype blocks, which were significantly associated with the 305-day milk, fat, and protein yields (p ≤ 1.03 × 10-2; p ≤ 8.60 × 10-3; p ≤ 3.20 × 10-3). In addition, it was predicted that the T allele in the SNP rs109066086 created TFBSs for transcription factors NC2R2 and TFAP4, thereby potentially affecting ACOX2 expression. Overall, our results provide the first confirmation of the genetic effects of the ACOX2 gene on milk yield and composition traits in dairy cattle and revealed the referable molecular markers for genomic selection.

The study of an anoikis-related signature to predict glioma prognosis and immune infiltration

BACKGROUND

Gliomas are the most common highly aggressive primary malignant brain tumors in adults with different biological behaviors and clinically heterogeneous features. About the extremely poor prognosis of gliomas, the search for potential therapeutic modalities and targets is crucial.

METHOD

We extracted the anoikis-related genes (ARG) from GeneCards and obtained differentially expressed genes in normal and glioma tissues from the GSE4290 dataset to obtain intersect differentially expressed ARG in gliomas by differential analysis. KEGG and GO analyses were used to evaluate the potential pathways and molecular processes of these genes. Based on The Cancer Genome Atlas (TCGA) training cohort, we performed the Least Absolute Shrinkage and Selection Operator (LASSO) regression and Cox regression to construct an ARG prognostic model and validated them in the TCGA testing cohort and the Chinese Glioma Genome Atlas (CGGA) validation cohort. Subsequently, we further explored the differences in clinical characteristics, tumor mutation burden (TMB), and the immune microenvironment in the high- and low-risk groups. Univariate and multifactorial regression analyses and nomogram construction were also performed. Moreover, we evaluated the expression levels of key genes via public databases, qPCR analysis and IHC staining, and further assessed the clinical prognostic value.

RESULTS

The regulatory model based on quantitative ARG prognostic models showed that patients in the high-risk group were associated with poorer survival prognosis, poorer clinical characteristics, and higher TMB levels. Moreover, the high-risk group had high levels of immune infiltration and upregulated immune checkpoint gene expression. The ARG prognostic model and the Nomogram showed good predictive performance. Expression and survival analysis of five prognostic ARG signatures (ETV4, HMOX1, MYC, NFE2L2, and UBE2C) showed that these genes have potential prognostic value.

CONCLUSION

Our constructed ARG prognostic risk model provides a potential therapeutic target and theoretical basis for predicting the prognosis of glioma patients and guiding individualized immunotherapy.

Trans-Kingdom RNA Dialogues: miRNA and milRNA Networks as Biotechnological Tools for Sustainable Crop Defense and Pathogen Control

MicroRNAs (miRNAs) are a class of non-coding RNAs approximately 20-24 nucleotides in length, which play a crucial role during gene regulation in plant-pathogen interaction. They negatively regulate the expression of target genes, primarily at the transcriptional or post-transcriptional level, through complementary base pairing with target gene sequences. Recent studies reveal that during pathogen infection, miRNAs produced by plants and miRNA-like RNAs (milRNAs) produced by fungi can regulate the expression of endogenous genes in their respective organisms and undergo trans-kingdom transfer. They can thereby negatively regulate the expression of target genes in recipient cells. These findings provide novel perspectives for deepening our understanding of the regulatory mechanisms underlying plant-pathogen interactions. Here, we summarize and discuss the roles of miRNAs and milRNAs in mediating plant-pathogen interactions via multiple pathways, providing new insights into the functions of these RNAs and their modes of action. Collectively, these insights lay a theoretical foundation for the targeted management of crop diseases.