Identifying and validating MMP family members (MMP2, MMP9, MMP12, and MMP16) as therapeutic targets and biomarkers in kidney renal clear cell carcinoma (KIRC).

Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that carries a substantial risk of morbidity and mortality. The MMP family assumes a crucial role in tumor invasion and metastasis. This study aimed to uncover the mechanistic relevance of the MMP gene family as a therapeutic target and diagnostic biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) through a comprehensive approach encompassing both computational and molecular analyses. STRING, Cytoscape, UALCAN, GEPIA, OncoDB, HPA, cBioPortal, GSEA, TIMER, ENCORI, DrugBank, targeted bisulfite sequencing (bisulfite-seq), conventional PCR, Sanger sequencing, and RT-qPCR based analyses were used in the present study to analyze MMP gene family members to accurately determine a few hub genes that can be utilized as both therapeutic targets and diagnostic biomarkers for KIRC. By performing STRING and Cytohubba analyses of the 24 MMP gene family members, MMP2 (matrix metallopeptidase 2), MMP9 (matrix metallopeptidase 9), MMP12 (matrix metallopeptidase 12), and MMP16 (matrix metallopeptidase 16) genes were denoted as hub genes having highest degree scores. After analyzing MMP2, MMP9, MMP12, and MMP16 via various TCGA databases and RT-qPCR technique across clinical samples and KIRC cell lines, interestingly, all these hub genes were found significantly overexpressed at mRNA and protein levels in KIRC samples relative to controls. The notable effect of the up-regulated MMP2, MMP9, MMP12, and MMP16 was also documented on the overall survival (OS) of the KIRC patients. Moreover, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed that promoter hypomethylation pattern was associated with up-regulation of hub genes (MMP2, MMP9, MMP12, and MMP16). In addition to this, hub genes were involved in various diverse oncogenic pathways. The MMP gene family members (MMP2, MMP9, MMP12, and MMP16) may serve as therapeutic targets and prognostic biomarkers in KIRC.

Resting-state functional connectivity of the primary visual cortex in children with anisometropia amblyopia.

INTRODUCTION: This study aimed to explore the functional connectivity of the primary visual cortex (V1) in children with anisometropic amblyopia by using the resting-state functional connectivity (RSFC) analysis method and determine whether anisometropic amblyopia is associated with changes in brain function. METHODS: Functional magnetic resonance imaging (fMRI) data were obtained from 16 children with anisometropia amblyopia (CAA group) and 12 healthy children (HC group) during the resting state. The Brodmann area 17 (BA17) was used as the region of interest (ROI), and the functional connection (FC) of V1 was analyzed in both groups. A two-sample t-test was used to analyze the FC value between the two groups. Pearson's correlation was used to analyze the correlation between the mean FC value in the brain function change area of the CAA group and the best corrected visual acuity (BCVA) of amblyopia. P<0.05 was considered statistically significant. RESULTS: There were no significant differences in age and sex between the CAA and HC groups (p > 0.05). Compared to the HC group, the CAA group showed lower FC values in BA17 and the left medial frontal gyrus, as well as BA17 and the left triangle inferior frontal gyrus. Conversely, the CAA group showed higher FC values in BA17 and the left central posterior gyrus. Notably, BCVA in amblyopia did not correlate with the area of change in mean FC in the brain function of the CAA group. CONCLUSION: Resting-state fMRI-based functional connectivity analysis indicates a significant alteration in V1 of children with anisometropic amblyopia. These findings contribute additional insights into the neuropathological mechanisms underlying visual impairment in anisometropic amblyopia.

Leaky gut, circulating immune complexes, arthralgia, and arthritis in IBD: coincidence or inevitability?

Most host-microbiota interactions occur within the intestinal barrier, which is essential for separating the intestinal epithelium from toxins, microorganisms, and antigens in the gut lumen. Gut inflammation allows pathogenic bacteria to enter the blood stream, forming immune complexes which may deposit on organs. Despite increased circulating immune complexes (CICs) in patients with inflammatory bowel disease (IBD) and discussions among IBD experts regarding their potential pathogenic role in extra-intestinal manifestations, this phenomenon is overlooked because definitive evidence demonstrating CIC-induced extra-intestinal manifestations in IBD animal models is lacking. However, clinical observations of elevated CICs in newly diagnosed, untreated patients with IBD have reignited research into their potential pathogenic implications. Musculoskeletal symptoms are the most prevalent extra-intestinal IBD manifestations. CICs are pivotal in various arthritis forms, including reactive, rheumatoid, and Lyme arthritis and systemic lupus erythematosus. Research indicates that intestinal barrier restoration during the pre-phase of arthritis could inhibit arthritis development. In the absence of animal models supporting extra-intestinal IBD manifestations, this paper aims to comprehensively explore the relationship between CICs and arthritis onset via a multifaceted analysis to offer a fresh perspective for further investigation and provide novel insights into the interplay between CICs and arthritis development in IBD.

Unlocking PD-1 antibody resistance: The MUC1 DNA vaccine augments CD8+ T cell infiltration and attenuates tumour suppression.

In light of increasing resistance to PD1 antibody therapy among certain patient populations, there is a critical need for in-depth research. Our study assesses the synergistic effects of a MUC1 DNA vaccine and PD1 antibody for surmounting PD1 resistance, employing a murine CT26/MUC1 colon carcinoma model for this purpose. When given as a standalone treatment, PD1 antibodies showed no impact on tumour growth. Additionally, there was no change observed in the intra-tumoural T-cell ratios or in the functionality of T-cells. In contrast, the sole administration of a MUC1 DNA vaccine markedly boosted the cytotoxicity of CD8+ T cells by elevating IFN-γ and granzyme B production. Our compelling evidence highlights that combination therapy more effectively inhibited tumour growth and prolonged survival compared to either monotherapy, thus mitigating the limitations intrinsic to single-agent therapies. This enhanced efficacy was driven by a significant alteration in the tumour microenvironment, skewing it towards pro-immunogenic conditions. This assertion is backed by a raised CD8+/CD4+ T-cell ratio and a decrease in immunosuppressive MDSC and Treg cell populations. On the mechanistic front, the synergistic therapy amplified expression levels of CXCL13 in tumours, subsequently facilitating T-cell ingress into the tumour setting. In summary, our findings advocate for integrated therapy as a potent mechanism for surmounting PD1 antibody resistance, capitalizing on improved T-cell functionality and infiltration. This investigation affords critical perspectives on enhancing anti-tumour immunity through the application of innovative therapeutic strategies.

MicroRNA-542-3p targets Pten to inhibit the myoblasts proliferation but suppresses myogenic differentiation independent of targeted Pten.

BACKGROUND: Non-coding RNA is a key epigenetic regulation factor during skeletal muscle development and postnatal growth, and miR-542-3p was reported to be conserved and highly expressed in the skeletal muscle among different species. However, its exact functions in the proliferation of muscle stem cells and myogenesis remain to be determined. METHODS: Transfection of proliferative and differentiated C2C12 cells used miR-542-3p mimic and inhibitor. RT-qPCR, EdU staining, immunofluorescence staining, cell counting kit 8 (CCK-8), and Western blot were used to evaluate the proliferation and myogenic differentiation caused by miR-542-3p. The dual luciferase reporter analysis and rescued experiment of the target gene were used to reveal the molecular mechanism. RESULTS: The data shows overexpression of miR-542-3p downregulation of mRNA and protein levels of proliferation marker genes, reduction of EdU+ cells, and cellular vitality. Additionally, knocking it down promoted the aforementioned phenotypes. For differentiation, the miR-542-3p gain-of-function reduced both mRNA and protein levels of myogenic genes, including MYOG, MYOD1, et al. Furthermore, immunofluorescence staining immunized by MYHC antibody showed that the myotube number, fluorescence intensity, differentiation index, and myotube fusion index all decreased in the miR-542-3p mimic group, compared with the control group. Conversely, these phenotypes exhibited an increased trend in the miR-542-3p inhibitor group. Mechanistically, phosphatase and tensin homolog (Pten) was identified as the bona fide target gene of miR-542-3p by dual luciferase reporter gene assay, si-Pten combined with miR-542-3p inhibitor treatments totally rescued the promotion of proliferation by loss-function of miR-542-3p. CONCLUSIONS: This study indicates that miR-542-3p inhibits the proliferation and differentiation of myoblast and Pten is a dependent target gene of miR-542-3p in myoblast proliferation, but not in differentiation.

Multi-hierarchy Network Configuration Can Predict Brain States and Performance.

The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we proposed an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules, and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.

Metformin and risk of hematological cancers in patients with diabetes: a systematic review and meta-analysis.

FUNDING: No external funding.

Multi-Stimulus Least-Squares Transformation With Online Adaptation Scheme to Reduce Calibration Effort for SSVEP-Based BCIs.

Steady-state visual evoked potential (SSVEP), one of the most popular electroencephalography (EEG)-based brain-computer interface (BCI) paradigms, can achieve high performance using calibration-based recognition algorithms. As calibration-based recognition algorithms are time-consuming to collect calibration data, the least-squares transformation (LST) has been used to reduce the calibration effort for SSVEP-based BCI. However, the transformation matrices constructed by current LST methods are not precise enough, resulting in large differences between the transformed data and the real data of the target subject. This ultimately leads to the constructed spatial filters and reference templates not being effective enough. To address these issues, this paper proposes multi-stimulus LST with online adaptation scheme (ms-LST-OA). METHODS: The proposed ms-LST-OA consists of two parts. Firstly, to improve the precision of the transformation matrices, we propose the multi-stimulus LST (ms-LST) using cross-stimulus learning scheme as the cross-subject data transformation method. The ms-LST uses the data from neighboring stimuli to construct a higher precision transformation matrix for each stimulus to reduce the differences between transformed data and real data. Secondly, to further optimize the constructed spatial filters and reference templates, we use an online adaptation scheme to learn more features of the EEG signals of the target subject through an iterative process trial-by-trial. RESULTS: ms-LST-OA performance was measured for three datasets (Benchmark Dataset, BETA Dataset, and UCSD Dataset). Using few calibration data, the ITR of ms-LST-OA achieved 210.01±10.10 bits/min, 172.31±7.26 bits/min, and 139.04±14.90 bits/min for all three datasets, respectively. CONCLUSION: Using ms-LST-OA can reduce calibration effort for SSVEP-based BCIs.

Peritoneal B1 and B2 cells respond differently to LPS and IL-21 stimulation.

Peritoneal B cells can be divided into B1 cells (CD11b+CD19+) and B2 cells (CD11b-CD19+) based on CD11b expression. B1 cells play a crucial role in the innate immune response by producing natural antibodies and cytokines. B2 cells share similar traits with B1 cells, influenced by the peritoneal environment. However, the response of both B1 and B2 cells to the same stimuli in the peritoneum remains uncertain. We isolated peritoneal B1 and B2 cells from mice and assessed differences in Interleukin-10(IL-10) secretion, apoptosis, and surface molecule expression following exposure to LPS and Interleukin-21(IL-21). Our findings indicate that B1 cells are potent IL-10 producers, possessing surface molecules with an IgMhiCD43+CD21low profile, and exhibit a propensity for apoptosis in vitro. Conversely, B2 cells exhibit lower IL-10 production and surface markers characterized as IgMlowCD43-CD21hi, indicative of some resistance to apoptosis. LPS stimulates MAPK phosphorylation in B1 and B2 cells, causing IL-10 production. Furthermore, LPS inhibits peritoneal B2 cell apoptosis by enhancing Bcl-xL expression. Conversely, IL-21 has no impact on IL-10 production in these cells. Nevertheless, impeding STAT3 phosphorylation permits IL-21 to increase IL-10 production in peritoneal B cells. Moreover, IL-21 significantly raises apoptosis levels in these cells, a process independent of STAT3 phosphorylation and possibly linked to reduced Bcl-xL expression. This study elucidates the distinct functional and response profiles of B1 and B2 cells in the peritoneum to stimuli like LPS and IL-21, highlighting their differential roles in immunological responses and B cell diversity.

Improvement on wheat bread quality by in situ produced dextran-A comprehensive review from the viewpoint of starch and gluten.

Deterioration of bread quality, characterized by the staling of bread crumb, the softening of bread crust and the loss of aroma, has caused a huge food waste and economic loss, which is a bottleneck restriction to the development of the breadmaking industry. Various bread improvers have been widely used to alleviate the issue. However, it is noteworthy that the sourdough technology has emerged as a pivotal factor in this regard. In sourdough, the metabolic breakdown of carbohydrates, proteins, and lipids leads to the production of exopolysaccharides, organic acids, aroma compounds, or prebiotics, which contributes to the preeminent ability of sourdough to enhance bread attributes. Moreover, sourdough exhibits a "green-label" feature, which satisfies the consumers' increasing demand for additive-free food products. In the past two decades, there has been a significant focus on sourdough with in situ produced dextran due to its exceptional performance. In this review, the behaviors of bread crucial compositions (i.e., starch and gluten) during dough mixing, proofing, baking and bread storing, as well as alterations induced by the acidic environment and the presence of dextran are systemically summarized. From the viewpoint of starch and gluten, results obtained confirm the synergistic amelioration on bread quality by the coadministration of acidity and dextran, and also highlight the central role of acidification. This review contributes to establishing a theoretical foundation for more effectively enhancing the quality of wheat breads through the application of in situ produced dextran.

A selective Fibroblast Growth Factor Receptor 1/2 PROTAC degrader with antitumor activity.

The aberrant activation of fibroblast growth factor receptor (FGFR) acts as a potent driver of multiple types of human cancers. Despite the development of several conventional small-molecular FGFR inhibitors, their clinical efficacy is largely compromised due to low selectivity and side effects. Here, we report the selective FGFR1/2-targeting proteolysis targeting chimeric (PROTAC), BR-cpd7 that displays significant isoform specificity to FGFR1/2 with DC50 values around 10 nM, while sparing FGFR3. The following mechanistic investigation reveals the reduced FGFR signaling, through which BR-cpd7 induces cell cycle arrest and consequently blocks the proliferation of multiple FGFR1/2-dependent tumor cells. Importantly, BR-cpd7 has almost no anti-proliferative activity against cancer cells without FGFR aberrations, furtherly supporting its selectivity. In vivo, BR-cpd7 exhibits robust antitumor effects in FGFR1-dependent lung cancer at well-tolerated dose schedules, accompanied by complete FGFR1 depletion. Overall, we identify BR-cpd7 as a promising candidate for developing a selective FGFR1/2-targeted agent, thereby offering a new therapeutic strategy for human cancers in which FGFR1/2 plays a critical role.

Application Value of CYFRA21-1 Combined with NSE, CEA, and SCC-Ag in Lung Cancer.

BACKGROUND: This study aims to investigate the application value of serum cytokeratin 19 fragment (CYFRA21-1) combined with nerve-specific enolase (NSE), carcinoembryonic antigen (CEA), and squamous cell carcinoma antigen (SCC-Ag) in the diagnosis of lung cancer (LC). METHODS: A total of 831 cases of LC, 360 cases of benign lung disease (BLD) and 102 healthy controls, were enrolled. The data were processed using SPSS, GraphPad Prism, and MedCalc software. RESULTS: The tumor marker (TM) levels in the LC and BLD groups were significantly higher than those in the control group; the CYFRA21-1, NSE, and CEA levels in the patients with LC were higher than in those with BLD. In particular, the increase was predominantly observed for the levels of CEA and CYFRA21-1 in adenocarcinoma (LUAD), CYFRA21-1 and SCC-Ag in squamous cell carcinoma (LUSC), and NSE in small cell carcinoma (SCLC). The CYFRA21-1, NSE, and CEA levels were significantly higher in stage IV than in other stages in LC. Univariate binary logistic analysis showed that increased levels of all four TMs were risk factors for BLD and LC. The area under the curve (AUC) of CYFRA21-1 was most effective in distinguishing patients with BLD or LC from the controls and in distinguishing patients with BLD and LC. The AUCs of combined CYFRA21-1, NSE, and CEA were increased to 0.755, 0.922, and 0.783, respectively, with no significant difference with the AUC of the four combined tests. In the histological classification, the best predictors were CEA, for LUAD, CYFRA21-1 for LUSC, and NSE for SCLC. Moreover, the expression levels of CYFRA21-1, NSE, and CEA significantly decreased after each treatment course. CONCLUSIONS: The combined assay of CYFRA21-1, NSE, and CEA addresses the aspects of accuracy, sensitivity, specificity, and economic cost and should be considered as a potential diagnostic test in LC.

METTL3-dependent m6A modification of PSEN1 mRNA regulates craniofacial development through the Wnt/ß-catenin signaling pathway.

Craniofacial malformations, often associated with syndromes, are prevalent birth defects. Emerging evidence underscores the importance of m6A modifications in various bioprocesses such as stem cell differentiation, tissue development, and tumorigenesis. Here, in vivo, experiments with zebrafish models revealed that mettl3-knockdown embryos at 144 h postfertilization exhibited aberrant craniofacial features, including altered mouth opening, jaw dimensions, ethmoid plate, tooth formation and hypoactive behavior. Similarly, low METTL3 expression inhibited the proliferation and migration of BMSCs, HEPM cells, and DPSCs. Loss of METTL3 led to reduced mRNA m6A methylation and PSEN1 expression, impacting craniofacial phenotypes. Co-injection of mettl3 or psen1 mRNA rescued the level of Sox10 fusion protein, promoted voluntary movement, and mitigated abnormal craniofacial phenotypes induced by mettl3 knockdown in zebrafish. Mechanistically, YTHDF1 enhanced the mRNA stability of m6A-modified PSEN1, while decreased METTL3-mediated m6A methylation hindered ß-catenin binding to PSEN1, suppressing Wnt/ß-catenin signaling. Pharmacological activation of the Wnt/ß-catenin pathway partially alleviated the phenotypes of mettl3 morphant and reversed the decreases in cell proliferation and migration induced by METTL3 silencing. This study elucidates the pivotal role of METTL3 in craniofacial development via the METTL3/YTHDF1/PSEN1/ß-catenin signaling axis.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis.

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

Personalized anti-tumor drug efficacy prediction based on clinical data.

Anti-tumor drug efficacy prediction poses an unprecedented challenge to realizing personalized medicine. This paper proposes to predict personalized anti-tumor drug efficacy based on clinical data. Specifically, we encode the clinical text as numeric vectors featured with hidden topics for patients using Latent Dirichlet Allocation model. Then, to classify patients into two classes, responsive or non-responsive to a drug, drug efficacy predictors are established by machine learning based on the Latent Dirichlet Allocation topic representation. To evaluate the proposed method, we collected and collated clinical records of lung and bowel cancer patients treated with platinum. Experimental results on the data sets show the efficacy and effectiveness of the proposed method, suggesting the potential value of clinical data in cancer precision medicine. We hope that it will promote the research of drug efficacy prediction based on clinical data.

Development of a Risk Prediction Model for Infection After Kidney Transplantation Transmitted from Bacterial Contaminated Preservation Solution.

Background: The risk of transplant recipient infection is unknown when the preservation solution culture is positive. Methods: We developed a prediction model to evaluate the infection in kidney transplant recipients within microbial contaminated preservation solution. Univariate logistic regression was utilized to identify risk factors for infection. Both stepwise selection with Akaike information criterion (AIC) was used to identify variables for multivariate logistic regression. Selected variables were incorporated in the nomograms to predict the probability of infection for kidney transplant recipients with microbial contaminated preservation solution. Results: Age, preoperative creatinine, ESKAPE, PCT, hemofiltration, and sirolimus had a strongest association with infection risk, and a nomogram was established with an AUC value of 0.72 (95% confidence interval, 0.64-0.80) and Brier index 0.20 (95% confidence interval, 0.18-0.23). Finally, we found that when the infection probability was between 20% and 80%, the model oriented antibiotic strategy should have higher net benefits than the default strategy using decision curve analysis. Conclusion: Our study developed and validated a risk prediction model for evaluating the infection of microbial contaminated preservation solutions in kidney transplant recipients and demonstrated good net benefits when the total infection probability was between 20% and 80%.

Precisely modulating the chromatin tracker via substituent engineering: reporting pathological oxidative stress during mitosis.

An in-depth understanding of cancer-cell mitosis presents unprecedented advantages for solving metastasis and proliferation of tumors, which has aroused great interest in visualizing the behavior via a luminescence tool. We developed a fluorescent molecule CBTZ-yne based on substituent engineering to acquire befitting lipophilicity and electrophilicity for anchoring lipid droplets and the nucleus, in which the low polarity environment and nucleic acids triggered a "weak-strong" fluorescence and "short-long" fluorescence-lifetime response. Meaningfully, CBTZ-yne visualized chromatin condensation, alignment, pull-push, and separation as well as lipid droplet dynamics, for the first time, precisely unveiling the asynchronous cellular mitosis processes affected by photo-generation reactive oxygen species according to the subtle change of fluorescence-lifetime. Our work suggested a new guideline for tracking the issue of the proliferation of malignant tumors in photodynamic therapy.

Comparative transcriptome and coexpression network analysis reveals key pathways and hub candidate genes associated with sunflower (Helianthus annuus L.) drought tolerance.

BACKGROUND: Drought severely limits sunflower production especially at the seedling stage. To investigate the response mechanism of sunflowers to drought stress, we utilized two genotypes of sunflower materials with different drought resistances as test materials. The physiological responses were investigated under well-watered (0 h) and drought-stressed conditions (24 h, 48 h, and 72 h). RESULTS: ANOVA revealed the greatest differences in physiological indices between 72 h of drought stress and 0 h of drought stress. Transcriptome analysis was performed after 72 h of drought stress. At 0 h, there were 7482 and 5627 differentially expressed genes (DEGs) in the leaves of K55 and K58, respectively, and 2150 and 2527 DEGs in the roots of K55 and K58, respectively. A total of 870 transcription factors (TFs) were identified among theDEGs, among which the high-abundance TF families included AP2/ERF, MYB, bHLH,and WRKY. Five modules were screened using weighted gene coexpressionnetwork analysis (WGCNA), three and two of which were positively and negatively, respectively, related to physiological traits. KEGG analysis revealedthat under drought stress, "photosynthesis", "carotenoid biosynthesis", "starch and sucrose metabolism", "ribosome", "carotenoid biosynthesis", "starch and sucrose metabolism", "protein phosphorylation" and "phytohormone signaling" are six important metabolic pathways involved in the response of sunflower to drought stress. Cytoscape software was used to visualize the three key modules, and the hub genes were screened. Finally, a total of 99 important candidate genes that may be associated with the drought response in sunflower plants were obtained, and the homology of these genes was compared with that in Arabidopsis thaliana. CONCLUSIONS: Taken together, our findings could lead to a better understanding of drought tolerance in sunflowers and facilitate the selection of drought-tolerant sunflower varieties.

Easy conversion perovskite fluorides KCo1-xFexF3 for efficient oxygen evolution reaction.

Herein, we report an easily oxidized Co-Fe perovskite fluoride as an efficient catalyst for the oxygen evolution reaction (OER). In situ Raman spectroscopy showed that the presence of F promotes reconstruction to form highly active (Co3+Fe3+)OOH, and the current density of 10 mA cm-2 can be achieved at the overpotential of only 118 mV in 1 M KOH aqueous solution. This work helps to understand the role of fluoride during the OER.

Near-Field Terahertz Morphological Reconstruction Nanoscopy for Subsurface Imaging of Protein Layers.

Protein layers formed on solid surfaces have important applications in various fields. High-resolution characterization of the morphological structures of protein forms in the process of developing protein layers has significant implications for the control of the layer's quality as well as for the evaluation of the layer's performance. However, it remains challenging to precisely characterize all possible morphological structures of protein in various forms, including individuals, networks, and layers involved in the formation of protein layers with currently available methods. Here, we report a terahertz (THz) morphological reconstruction nanoscopy (THz-MRN), which can reveal the nanoscale three-dimensional structural information on a protein sample from its THz near-field image by exploiting an extended finite dipole model for a thin sample. THz-MRN allows for both surface imaging and subsurface imaging with a vertical resolution of ∼0.5 nm, enabling the characterization of various forms of proteins at the single-molecule level. We demonstrate the imaging and morphological reconstruction of single immunoglobulin G (IgG) molecules, their networks, a monolayer, and a heterogeneous double layer comprising an IgG monolayer and a horseradish peroxidase-conjugated anti-IgG layer. The established THz-MRN presents a useful approach for the label-free and nondestructive study of the formation of protein layers.