Morphological and molecular response mechanisms of the root system of different Hemarthria compressa species to submergence stress.

Introduction: The severity of flood disasters is increasing due to climate change, resulting in a significant reduction in the yield and quality of forage crops worldwide. This poses a serious threat to the development of agriculture and livestock. Hemarthria compressa is an important high-quality forage grass in southern China. In recent years, frequent flooding has caused varying degrees of impacts on H. compressa and their ecological environment. Methods: In this study, we evaluated differences in flooding tolerance between the root systems of the experimental materials GY (Guang Yi, flood-tolerant) and N1291 (N201801291, flood-sensitive). We measured their morphological indexes after 7 d, 14 d, and 21 d of submergence stress and sequenced their transcriptomes at 8 h and 24 h, with 0 h as the control. Results: During submergence stress, the number of adventitious roots and root length of both GY and N1291 tended to increase, but the overall growth of GY was significantly higher than that of N1291. RNA-seq analysis revealed that 6046 and 7493 DEGs were identified in GY-8h and GY-24h, respectively, and 9198 and 4236 DEGs in N1291-8h and N1291-24h, respectively, compared with the control. The GO and KEGG enrichment analysis results indicated the GO terms mainly enriched among the DEGs were oxidation-reduction process, obsolete peroxidase reaction, and other antioxidant-related terms. The KEGG pathways that were most significantly enriched were phenylpropanoid biosynthesis, plant hormone signal transduction etc. The genes of transcription factor families, such as C2H2, bHLH and bZIP, were highly expressed in the H. compressa after submergence, which might be closely related to the submergence adaptive response mechanisms of H. compressa. Discussion: This study provides basic data for analyzing the molecular and morphological mechanisms of H. compressa in response to submergence stress, and also provides theoretical support for the subsequent improvement of submergence tolerance traits of H. compressa.

Unraveling molecular networks in thymic epithelial tumors: deciphering the unique signatures.

Thymic epithelial tumors (TETs) are a rare and diverse group of neoplasms characterized by distinct molecular signatures. This review delves into the complex molecular networks of TETs, highlighting key aspects such as chromosomal abnormalities, molecular subtypes, aberrant gene mutations and expressions, structural gene rearrangements, and epigenetic changes. Additionally, the influence of the dynamic tumor microenvironment on TET behavior and therapeutic responses is examined. A thorough understanding of these facets elucidates TET pathogenesis, offering avenues for enhancing diagnostic accuracy, refining prognostic assessments, and tailoring targeted therapeutic strategies. Our review underscores the importance of deciphering TETs' unique molecular signatures to advance personalized treatment paradigms and improve patient outcomes. We also discuss future research directions and anticipated challenges in this intriguing field.

Manipulation of crystallization nucleation and thermal degradation of PLA films by multi-morphologies CNC-ZnO nanoparticles.

Currently, the quest for more renewable and biodegradable materials is a scientific priority to address the problems of petroleum-based plastics are difficult to degrade. In this work, cellulose nanocrystals (CNC) have been used as a template and four morphologies of CNC-ZnO nanocomposites were prepared via a hydrothermal method, and CNC-ZnO/polylactic acid (PLA) composite films were obtained by solution casting. We find that CNC-ZnO nanocomposites as heterogeneous nucleating agents improved the crystallinity and the film with flower-like CNC-ZnO was improved by 2.4 %. Ea required for thermal degradation of the PLA films decreased to 66-81 % of that of neat PLA, calculated by the Kissinger method, the Friedman method, and the Flynn-Wall-Ozawa (FWO) method. The R2 model was the solid degradation mechanism of the PLA films, analyzed through the Coats-Redfern method and the Criado method. The H-bond content of the composite films was significantly reduced after thermal aging at 150 °C. We found that three-dimensional CNC-ZnO (ZnO-3) made more prominent contributions to the crystallization, thermal degradation, and thermal aging of PLA films than other dimensional. The thermal properties can be regulated by the dimension, size, and apparent morphology of CNC-ZnO nanoparticles.

A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts.

Background: Extensive research has established the significant correlations between cancer-associated fibroblasts (CAFs) and various stages of cancer development, including initiation, angiogenesis, progression, and resistance to therapy. In this study, we aimed to investigate the characteristics of CAFs in lung adenocarcinoma (LUAD) and develop a risk signature to predict the prognosis of patients with LUAD. Methods: We obtained single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the public database. The Seurat R package was used to process the scRNA-seq data and identify CAF clusters based on several biomarkers. CAF-related prognostic genes were further identified using univariate Cox regression analysis. To reduce the number of genes, Lasso regression was performed, and a risk signature was established. A novel nomogram that incorporated the risk signature and clinicopathological features was developed to predict the clinical applicability of the model. Additionally, we conducted immune landscape and immunotherapy responsiveness analyses. Finally, we performed in vitro experiments to verify the functions of EXO1 in LUAD. Results: We identified 5 CAF clusters in LUAD using scRNA-seq data, of which 3 clusters were significantly associated with prognosis in LUAD. A total of 492 genes were found to be significantly linked to CAF clusters from 1731 DEGs and were used to construct a risk signature. Moreover, our immune landscape exploration revealed that the risk signature was significantly related to immune scores, and its ability to predict responsiveness to immunotherapy was confirmed. Furthermore, a novel nomogram incorporating the risk signature and clinicopathological features showed excellent clinical applicability. Finally, we verified the functions of EXP1 in LUAD through in vitro experiments. Conclusions: The risk signature has proven to be an excellent predictor of LUAD prognosis, stratifying patients more appropriately and precisely predicting immunotherapy responsiveness. The comprehensive characterization of LUAD based on the CAF signature can predict the response of LUAD to immunotherapy, thus offering fresh perspectives into the management of LUAD patients. Our study ultimately confirms the role of EXP1 in facilitating the invasion and growth of tumor cells in LUAD. Nevertheless, further validation can be achieved by conducting in vivo experiments.

A fibroblast-associated signature predicts prognosis and immunotherapy in esophageal squamous cell cancer.

Background: Current paradigms of anti-tumor therapies are not qualified to evacuate the malignancy ascribing to cancer stroma's functions in accelerating tumor relapse and therapeutic resistance. Cancer-associated fibroblasts (CAFs) has been identified significantly correlated with tumor progression and therapy resistance. Thus, we aimed to probe into the CAFs characteristics in esophageal squamous cancer (ESCC) and construct a risk signature based on CAFs to predict the prognosis of ESCC patients. Methods: The GEO database provided the single-cell RNA sequencing (scRNA-seq) data. The GEO and TCGA databases were used to obtain bulk RNA-seq data and microarray data of ESCC, respectively. CAF clusters were identified from the scRNA-seq data using the Seurat R package. CAF-related prognostic genes were subsequently identified using univariate Cox regression analysis. A risk signature based on CAF-related prognostic genes was constructed using Lasso regression. Then, a nomogram model based on clinicopathological characteristics and the risk signature was developed. Consensus clustering was conducted to explore the heterogeneity of ESCC. Finally, PCR was utilized to validate the functions that hub genes play on ESCC. Results: Six CAF clusters were identified in ESCC based on scRNA-seq data, three of which had prognostic associations. A total of 642 genes were found to be significantly correlated with CAF clusters from a pool of 17080 DEGs, and 9 genes were selected to generate a risk signature, which were mainly involved in 10 pathways such as NRF1, MYC, and TGF-Beta. The risk signature was significantly correlated with stromal and immune scores, as well as some immune cells. Multivariate analysis demonstrated that the risk signature was an independent prognostic factor for ESCC, and its potential in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the CAF-based risk signature and clinical stage was developed, which exhibited favorable predictability and reliability for ESCC prognosis prediction. The consensus clustering analysis further confirmed the heterogeneity of ESCC. Conclusion: The prognosis of ESCC can be effectively predicted by CAF-based risk signatures, and a comprehensive characterization of the CAF signature of ESCC may aid in interpreting the response of ESCC to immunotherapy and offer new strategies for cancer treatment.

Tracking the Dissolution Surface Kinetics of a Single Fluorescent Cyclodextrin Metal-Organic Framework by Confocal Laser Scanning Microscopy.

The understanding of the dissolution processes of solids is important for the design and synthesis of solids in a controlled and precise manner and for predicting their fate in the aquatic environment. We report herein single-particle-based confocal laser scanning microscopy (CLSM) for tracking the dissolution surface kinetics of a single fluorescent cyclodextrin metal-organic framework (CD-MOF). As a proof of concept, CD-MOF containing fluorescein, named as CD-MOF⊃FL, was synthesized by encapsulating fluorescein into the interior of CD-MOF via a vapor diffusion method and used as a single-particle dissolution model because of its high FL efficiency and unique structure. The morphology of CD-MOF⊃FL and the distribution of fluorescein within CD-MOF⊃FL were characterized. The growth and dissolution processes of CD-MOF⊃FL at the single-particle level were visualized and quantified for the first time by recording the change of the fluorescence emission. Three processes, including nucleation, germination growth, and saturation stage, were found in the growth of CD-MOF⊃FL, and the growth kinetics followed Avrami's model. The dissolution rate at the face of a single CD-MOF⊃FL crystal was slower than that of its arris, and the dissolution rate of the CD-MOF⊃FL crystal was increased with the increase of the water amount in methanol solution. The dissolution process of the CD-MOF⊃FL crystal was a competitive process of erosion and diffusion in different methanol aqueous solutions, and the dissolution kinetics followed the Korsmeyer-Peppas model. These results offer new insights into the nature of dissolution kinetics of CD-MOF⊃FL and provide new venues for the quantitative analysis of solid dissolution and growth at the single-particle level.

By integrating single-cell RNA-seq and bulk RNA-seq in sphingolipid metabolism, CACYBP was identified as a potential therapeutic target in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is a heterogeneous disease with a dismal prognosis for advanced tumors. Immune-associated cells in the microenvironment substantially impact LUAD formation and progression, which has gained increased attention in recent decades. Sphingolipids have a profound impact on tumor formation and immune infiltration. However, few researchers have focused on the utilization of sphingolipid variables in the prediction of LUAD prognosis. The goal of this work was to identify the major sphingolipid-related genes (SRGs) in LUAD and develop a valid prognostic model based on SRGs. Methods: The most significant genes for sphingolipid metabolism (SM) were identified using the AUCell and WGCNA algorithms in conjunction with single-cell and bulk RNA-seq. LASSO and COX regression analysis was used to develop risk models, and patients were divided into high-and low-risk categories. External nine provided cohorts evaluated the correctness of the models. Differences in immune infiltration, mutation landscape, pathway enrichment, immune checkpoint expression, and immunotherapy were also further investigated in distinct subgroups. Finally, cell function assay was used to verify the role of CACYBP in LUAD cells. Results: A total of 334 genes were selected as being most linked with SM activity for further investigation, and a risk model consisting of 11 genes was established using lasso and cox regression. According to the median risk value, patients were split into high- and low-risk groups, and the high-risk group had a worse prognosis. The low-risk group had more immune cell infiltration and higher expression of immune checkpoints, which illustrated that the low-risk group was more likely to benefit from immunotherapy. It was verified that CACYBP could increase the ability of LUAD cells to proliferate, invade, and migrate. Conclusion: The eleven-gene signature identified in this research may help physicians create individualized care plans for LUAD patients. CACYBP may be a new therapeutic target for patients with advanced LUAD.

Cuproptosis-related lncRNA signatures: Predicting prognosis and evaluating the tumor immune microenvironment in lung adenocarcinoma.

Background: Cuproptosis, a unique kind of cell death, has implications for cancer therapy, particularly lung adenocarcinoma (LUAD). Long non-coding RNAs (lncRNAs) have been demonstrated to influence cancer cell activity by binding to a wide variety of targets, including DNA, RNA, and proteins. Methods: Cuproptosis-related lncRNAs (CRlncRNAs) were utilized to build a risk model that classified patients into high-and low-risk groups. Based on the CRlncRNAs in the model, Consensus clustering analysis was used to classify LUAD patients into different subtypes. Next, we explored the differences in overall survival (OS), the tumor immune microenvironment (TIME), and the mutation landscape between different risk groups and molecular subtypes. Finally, the functions of LINC00592 were verified through in vitro experiments. Results: Patients in various risk categories and molecular subtypes showed statistically significant variations in terms of OS, immune cell infiltration, pathway activity, and mutation patterns. Cell experiments revealed that LINC00592 knockdown significantly reduced LUAD cell proliferation, invasion, and migration ability. Conclusion: The development of a trustworthy prediction model based on CRlncRNAs may significantly aid in the assessment of patient prognosis, molecular features, and therapeutic modalities and may eventually be used in clinical applications.

Study on the interaction of Zea mays L. centrin and melittin.

Zea mays L. centrin (Zmcen) is a 20 kDa calcium binding protein also known as caltractin. We used melittin as a simulated target peptide and examined its interaction with Zmcen to understand the structure of Zmcen and the mechanism of interaction with downstream target peptides. The circular dichroism spectrum was used to characterize the typical α-helix structure of Zmcen, and after combining with melittin, the α-helix content of Zmcen changed. Trp residues in melittin were used as fluorescent probes to monitor changes in the conformation of Zmcen upon melittin binding. The Trp residues in melittin gradually shifted from polar environments to nonpolar environments, fluorescence peaks were significantly blueshifted, and the intensity of the fluorescence peak increased. These results showed that Zmcen and melittin combined in a 1 : 1 ratio to form a new complex. The influence of metal ions on binding was also investigated. The combination of Ca2+ and Zmcen helped expose more hydrophobic regions of Zmcen and promoted the binding of Zmcen and melittin. In addition, 2-p-toluidinylnaphthalene-6-sulfonate (TNS) was used as a hydrophobic probe to bind to Zmcen and Zmcen occupied the hydrophobic area on the surface of Zmcen, thereby weakening the binding of Zmcen and melittin. The Biacore experiment was used to calculate the equilibrium constant (K D) for the dissociation of Zmcen and melittin. Melittin mainly binds to C-Zmcen but not to N-Zmcen, indicating that the binding site of melittin on Zmcen was mainly at the C-terminus of Zmcen.

Adsorption of dye from wastewater using chitosan-CTAB modified bentonites.

Dyeing wastewater removal is important for the water treatment, and adsorption is an efficient treatment process. In this study, three modified bentonites, chitosan modified bentonite (CTS-Bent), hexadecyl trimethyl ammonium bromide (CTAB) modified bentonite (CTAB-Bent), and both chitosan and hexadecyl trimethyl ammonium bromide modified bentonite (CTS-CTAB-Bent) were prepared and characterized by FTIR and XRD analysis. Batch experiments were conducted to evaluate the adsorptive removal of weak acid scarlet from aqueous phase using modified bentonites under different conditions. The results show that the adsorption capacity of weak acid scarlet onto natural bentonite was low (4.9%), but higher for 1CTS-Bent and 1CTS-10CTAB-Bent. The optimal conditions for weak acid scarlet adsorption were 1% chitosan, 10% CTAB, at 80°C and reaction time 2.5h. The best removal efficiency was ∼85%, and the adsorption capacity of weak acid scarlet was around 102.0mg g(-1), much higher than that of commercial activated carbon (27.2mg g(-1)). These results suggest that 1CTS-10CTAB-Bent is an excellent adsorbent for effective weak acid scarlet removal from water. The adsorption isotherms of weak acid scarlet were investigated. It was found that Langmuir and Temkin models fitted the data very well (R(2)>0.99).