Postnatal development of rat retina: a continuous observation and comparison between the organotypic retinal explant model and in vivo development.

JOURNAL/nrgr/04.03/01300535-202503000-00033/figure1/v/2024-06-17T092413Z/r/image-tiff The organotypic retinal explant culture has been established for more than a decade and offers a range of unique advantages compared with in vivo experiments and cell cultures. However, the lack of systematic and continuous comparison between in vivo retinal development and the organotypic retinal explant culture makes this model controversial in postnatal retinal development studies. Thus, we aimed to verify the feasibility of using this model for postnatal retinal development studies by comparing it with the in vivo retina. In this study, we showed that postnatal retinal explants undergo normal development, and exhibit a consistent structure and timeline with retinas in vivo. Initially, we used SOX2 and PAX6 immunostaining to identify retinal progenitor cells. We then examined cell proliferation and migration by immunostaining with Ki-67 and doublecortin, respectively. Ki-67- and doublecortin-positive cells decreased in both in vivo and explants during postnatal retinogenesis, and exhibited a high degree of similarity in abundance and distribution between groups. Additionally, we used Ceh-10 homeodomain-containing homolog, glutamate-ammonia ligase (glutamine synthetase), neuronal nuclei, and ionized calcium-binding adapter molecule 1 immunostaining to examine the emergence of bipolar cells, Müller glia, mature neurons, and microglia, respectively. The timing and spatial patterns of the emergence of these cell types were remarkably consistent between in vivo and explant retinas. Our study showed that the organotypic retinal explant culture model had a high degree of consistency with the progression of in vivo early postnatal retina development. The findings confirm the accuracy and credibility of this model and support its use for long-term, systematic, and continuous observation.

Large Language Model-Based Natural Language Encoding Could Be All You Need for Drug Biomedical Association Prediction.

Analyzing drug-related interactions in the field of biomedicine has been a critical aspect of drug discovery and development. While various artificial intelligence (AI)-based tools have been proposed to analyze drug biomedical associations (DBAs), their feature encoding did not adequately account for crucial biomedical functions and semantic concepts, thereby still hindering their progress. Since the advent of ChatGPT by OpenAI in 2022, large language models (LLMs) have demonstrated rapid growth and significant success across various applications. Herein, LEDAP was introduced, which uniquely leveraged LLM-based biotext feature encoding for predicting drug-disease associations, drug-drug interactions, and drug-side effect associations. Benefiting from the large-scale knowledgebase pre-training, LLMs had great potential in drug development analysis owing to their holistic understanding of natural language and human topics. LEDAP illustrated its notable competitiveness in comparison with other popular DBA analysis tools. Specifically, even in simple conjunction with classical machine learning methods, LLM-based feature representations consistently enabled satisfactory performance across diverse DBA tasks like binary classification, multiclass classification, and regression. Our findings underpinned the considerable potential of LLMs in drug development research, indicating a catalyst for further progress in related fields.

Discovery of Biphenyl Derivatives to Target Hsp70-Bim Protein-Protein Interaction in Chronic Myeloid Leukemia by Scaffold Hopping Strategy.

Hsp70-Bim protein-protein interaction (PPI) is the most recently identified specific target in chronic myeloid leukemia (CML) therapy. Herein, we developed a new class of Hsp70-Bim PPI inhibitors via scaffold hopping of S1g-10, the most potent Hsp70-Bim PPI inhibitor thus far. Through structure-activity relationship (SAR) study, we obtained a biphenyl scaffold compound JL-15 with a 5.6-fold improvement in Hsp70-Bim PPI suppression (Kd = 123 vs 688 nM) and a 4-fold improvement in water solubility (29.42 vs 7.19 µg/mL) compared to S1g-10. It maintains comparable apoptosis induction capability with S1g-10 against both TKI-sensitive and TKI-resistant CML cell lines in an Hsp70-Bim-dependent manner. Additionally, through SAR, 1H-15N TRSOY-NMR, and molecular docking, we revealed that Lys319 is a "hot spot" in the Hsp70-Bim PPI interface. Collectively, these results provide a novel chemical scaffold and structural insights for the rational design of Hsp70-Bim PPI inhibitors.

Construction of an interface interaction in a g-C3N4/CdS/NiS for photoreforming of plastic and clean hydrogen regeneration.

Converting plastics into organic matter by photoreforming is an emerging way to deal with plastic pollution and produce valuable organic matter. Water shortage can be alleviated by using seawater resources. To solve these problems, we synthesize a ternary heterostructure composite g-C3N4/CdS/NiS. Heterojunctions are formed between graphitized carbon nitride (g-C3N4), cadmium sulfide (CdS) and nickel sulfide (NiS), which effectively improve the problem of fast charge recombination of pure g-C3N4 and CdS. The results of the g-C3N4/CdS/NiS photocatalytic tests show that the hydrogen production rates in seawater and pure water for 5 h are 30.44 and 25.79 mmol/g/h, respectively. In stability test, the hydrogen production rate of the g-C3N4/CdS/NiS in seawater and pure water is similar. This suggests that seawater can replace pure water as a source of hydrogen. While H2 is generated, the lactate obtained by polylactic acid (PLA) hydrolysis is oxidized to form small organic compounds such as formate, acetate and pyruvate. Our study shows that g-C3N4/CdS/NiS can not only use seawater as a hydrogen source to produce H2, but also photoreformate plastics dissolved in seawater into valuable small organic molecules. This has a positive impact on the production and use of clean energy, as well as on plastic pollution and water scarcity.

TG-Net: Using text prompts for improved skin lesion segmentation.

Automatic skin segmentation is an efficient method for the early diagnosis of skin cancer, which can minimize the missed detection rate and treat early skin cancer in time. However, significant variations in texture, size, shape, the position of lesions, and obscure boundaries in dermoscopy images make it extremely challenging to accurately locate and segment lesions. To address these challenges, we propose a novel framework named TG-Net, which exploits textual diagnostic information to guide the segmentation of dermoscopic images. Specifically, TG-Net adopts a dual-stream encoder-decoder architecture. The dual-stream encoder comprises Res2Net for extracting image features and our proposed text attention (TA) block for extracting textual features. Through hierarchical guidance, textual features are embedded into the process of image feature extraction. Additionally, we devise a multi-level fusion (MLF) module to merge higher-level features and generate a global feature map as guidance for subsequent steps. In the decoding stage of the network, local features and the global feature map are utilized in three multi-scale reverse attention modules (MSRA) to produce the final segmentation results. We conduct extensive experiments on three publicly accessible datasets, namely ISIC 2017, HAM10000, and PH2. Experimental results demonstrate that TG-Net outperforms state-of-the-art methods, validating the reliability of our method. Source code is available at https://github.com/ukeLin/TG-Net.

Water Injection Into Coal Seams for Outburst Prevention: The Coupling Effect of Gas Displacement and Desorption Inhibition.

Gassy coal seams generally have low permeability and dry coal bodies, which are susceptible to coal and gas outburst hazards in the process of mining. Water injection into coal seams can significantly alter the gas release rate and flow behavior. However, water has dual effects on coal seams: gas displacement and water-locking, and the coupling mechanism of these two effects is not clear in the whole process of coal seam water injection. By measuring high-pressure gas adsorption isotherms and gas diffusion initial velocity, it was found that both the Langmuir adsorption constant a and gas diffusion initial velocity ΔP decrease with the increase of water content, which would reduce outburst risks. Through the self-developed integrated experimental device of "gas adsorption + water injection displacement + gas desorption″, the changing rules of gas displacement amount, desorption amount, and water lock amount under different water injection conditions were studied. The results show that when the water injection ratio increases from 6 to 25%, the gas displacement would increase from 0.62 to 1.16 mL/g, with an increase of 87.09%. Also, at the same time, the gas desorption capacity would decrease from 4.86 to 4.05 mL/g after pressure relief, with a decrease of 16.67%. The amount of water-locking increased from 0.11 to 0.38 mL/g. The effect of water injection to control coal and gas outburst occurs in two different water injection stages. In the process of water injection, water plays a major role in gas displacement, which is conducive to reducing the gas content of the coal seam. After the completion of water injection, the static water pressure remaining in the coal seam can reduce the gas emission rate. The combination of these two effects can effectively reduce the risk of outbursts.

AlphaFold-guided redesign of a plant pectin methylesterase inhibitor for broad-spectrum disease resistance.

Plant cell walls are a critical site where plants and pathogens continuously struggle for physiological dominance. Here we show that dynamic remodeling of pectin methylesterification of plant cell walls is a component of the physiological and co-evolutionary struggles between hosts and pathogens. A Phytophthora sojae secreted pectin methylesterase (PsPME1) decreases the degree of pectin methylesterification, thus synergizing with an endo-polygalacturonase (PsPG1) to weaken plant cell walls. To counter PsPME1-mediated susceptibility, a plant-derived pectin methylesterase inhibitor protein, GmPMI1, protects pectin to maintain a high methylesterification status. GmPMI1 protects plant cell walls from enzymatic degradation by inhibiting both soybean and P. sojae pectin methylesterases during infection. However, constitutive expression of GmPMI1 disrupted the tradeoff between host growth and defense responses. So, we used AlphaFold structure tools to design a modified form of GmPMI1 (GmPMI1R) which specifically targets and inhibits pectin methylesterases secreted from pathogens but not from the plants. Transient expression of GmPMI1R enhanced plant resistance to oomycetes and fungal pathogens. In summary, our work highlights biochemical modification of the cell wall as an important focal point in the physiological and co-evolutionary conflict between the hosts and microbes and serves as an important proof-of-concept for how rapid advancements in AI-driven structure-based tools can accelerate the prediction of new strategies for plant protection.

Bioinformatic Analysis of the Significance of the KIR2DL4 Gene in Recurrent Implantation Failure.

Related studies have pointed out that Killer immunoglobulin-like receptor 2DL4 (KIR2DL4) was associated with vascular remodeling in early pregnancy, and it might play an important role in immunity. In this study, recurrent implantation failure (RIF)-related GSE58144 dataset was extracted from the Gene Expression Omnibus (GEO) database. Firstly, the immune micro-environment analyses were conducted to analyze the pathogenesis of KIR2DL4 in RIF. Then, the gene set enrichment analysis (GSEA) was performed to investigate the function of KIR2DL4. Moreover, the TF-mRNA-miRNA and the co-expression networks were constructed to reveal the potential regulation of KIR2DL4. Furthermore, the genes that were associated with KIR2DL4 and differentially expressed in RIF were obtained and defined as key genes, and the functions of these genes were further explored. KIR2DL4 could be used for clinical diagnosis of RIF, and it was correlated with the changes in the immune micro-environment in RIF. From the perspective of function, KIR2DL4 was associated with complement and coagulation cascades, natural killer cell-mediated cytotoxicity, etc. Moreover, the TF-mRNA-miRNA regulatory network was constructed with KIR2DL4, 9 TFs, and 29 miRNAs. Furthermore, KIR2DL4, ACSM1, IL2RB, and PTPN11 were screened as key genes, which were associated with immune-related functions. This study deeply analyzed the function of KIR2DL4 and its role in RIF, and we found that STAT1 might up-regulate KIR2DL4 by INF-γ/JAK2/STAT1 signaling pathway. Besides, over-expressed KIR2DL4 in the mid-luteal endometrium might influence embryo implantation by affecting the embryo implantation microenvironment, which might help deepen the understanding of the molecular mechanism of RIF.

LJCD-Net: Cross-Domain Jamming Generalization Diagnostic Network Based on Deep Adversarial Transfer.

Global Navigation Satellite Systems (GNSS) offer comprehensive position, navigation, and timing (PNT) estimates worldwide. Given the growing demand for reliable location awareness in both indoor and outdoor contexts, the advent of fifth-generation mobile communication technology (5G) has enabled expansive coverage and precise positioning services. However, the power received by the signal of interest (SOI) at terminals is notably low. This can lead to significant jamming, whether intentional or unintentional, which can adversely affect positioning receivers. The diagnosis of jamming types, such as classification, assists receivers in spectrum sensing and choosing effective mitigation strategies. Traditional jamming diagnosis methodologies predominantly depend on the expertise of classification experts, often demonstrating a lack of adaptability for diverse tasks. Recently, researchers have begun utilizing convolutional neural networks to re-conceptualize a jamming diagnosis as an image classification issue, thereby augmenting recognition performance. However, in real-world scenarios, the assumptions of independent and homogeneous distributions are frequently violated. This discrepancy between the source and target distributions frequently leads to subpar model performance on the test set or an inability to procure usable evaluation samples during training. In this paper, we introduce LJCD-Net, a deep adversarial migration-based cross-domain jamming generalization diagnostic network. LJCD-Net capitalizes on a fully labeled source domain and multiple unlabeled auxiliary domains to generate shared feature representations with generalization capabilities. Initially, our paper proposes an uncertainty-guided auxiliary domain labeling weighting strategy, which estimates the multi-domain sample uncertainty to re-weight the classification loss and specify the gradient optimization direction. Subsequently, from a probabilistic distribution standpoint, the spatial constraint imposed on the cross-domain global jamming time-frequency feature distribution facilitates the optimization of collaborative objectives. These objectives include minimizing both the source domain classification loss and auxiliary domain classification loss, as well as optimizing the inter-domain marginal probability and conditional probability distribution. Experimental results demonstrate that LJCD-Net enhances the recognition accuracy and confidence compared to five other diagnostic methods.

Suzuki-Miyaura Cross-Coupling Reaction Catalyzed by Al12M (M = Be, Al, C, and P) Superatoms with Different Numbers of Valence Electrons.

The exploration of low-cost, efficient, environmentally safe, and selective catalysts for the activation of carbon-halogen bonds has become an important and challenging topic in modern chemistry. With the help of density functional theory (DFT), it is found that phenyl bromide (PhBr) can be efficiently chemisorbed by the Al12M (M = Be, Al, C, and P) superatoms via forming highly polarized Al-Br covalent bonds, where the C-Br bonds of PhBr can be effectively activated through the electron transfer from Al12M. The different electronic structures of these four Al12M superatoms pose a substantial effect on their performances on the activation of PhBr and the catalytic mechanisms of the Suzuki-Miyaura (SM) reaction. Among them, the alkali-metal-like superatom Al12P exhibits the best performance for the activation of PhBr. In particular, Al13 and Al12P with open-shell electronic structures exhibit catalytic performances comparable to those of previously reported catalysts for this coupling reaction. Hence, it is highly expected that Al13 and Al12P could be used as novel superatom catalysts for C-C coupling reactions and, therefore, open up new possibilities to use nonprecious superatoms in catalyzing the activation and transformation of carbon-halogen bonds.

The Effect of High-Temperature Deformation on the Mechanical Properties and Corrosion Resistance of the 2024 Aluminum Alloy Joint after Friction Stir Welding.

The 2024 aluminum alloy is one of the high-quality lightweight materials. Friction stir welding (FSW) has shown advantages in reducing welding defects and improving welding quality in 2024 aluminum alloys. Currently, the research regarding FSW joint corrosion performance is mainly about the joint without plastic deformation. However, FSW joints often need to be formed into complex shapes by plastic deformation. The influence of plastic deformation on the corrosion performance of FSW joints is the focus of scientific research. To address this problem, the effect of high-temperature deformation on the mechanical properties and corrosion behavior of 2024 aluminum alloy joints was researched. The exfoliation corrosion test, scanning electron microscopy, energy-dispersive spectroscopy, and transmission electron microscopy were employed to analyze the corrosion mechanism and microstructure. The results show that high-temperature deformation of the weld nugget zone greatly affects the mechanical properties and corrosion behavior of the FSW joint. Compared with the 0% deformation specimen, the hardness and tensile strength of the 20% deformation FSW joint increased by 32% and 21%, respectively. The FSW joint with 20% deformation shows the best mechanical properties and corrosion resistance. The number of precipitated S' phases of the FSW joint increases when the deformation increases to 20%, and the shape of the S' phase is a regular round particle shape. The dislocation density of the FSW joint increases continuously during deformation, which provides a favorable nucleation location for the S' phase.

Exploring the causal effects of sleep characteristics on TMD-related pain: a two-sample Mendelian randomization study.

OBJECTIVES: The study was to explore the causal effects of sleep characteristics on temporomandibular disorder (TMD)-related pain using Mendelian randomization (MR) analysis. MATERIALS AND METHODS: Five sleep characteristics (short sleep, insomnia, chronotype, snoring, sleep apnea) were designated as exposure factors. Data were obtained from previous publicized genome-wide association studies and single nucleotide polymorphisms (SNPs) strongly associated with them were utilized as instrumental variables (IVs). TMD-related pain was designed as outcome variable and sourced from the FinnGens database. MR analysis was employed to explore the causal effects of the five sleep characteristics on TMD-related pain. The causal effect was analyzed using the inverse variance-weighted (IVW), weighted median, and MR-Egger methods. Subsequently, sensitivity analyses were conducted using Cochran's Q tests, funnel plots, leave-one-out analyses, and MR-Egger intercept tests. RESULTS: A causal effect of short sleep on TMD-related pain was revealed by IVW (OR: 1.60, 95% CI: 1.06-2.41, P = 0.026). No causal relationship was identified between other sleep characteristics (insomnia, chronotype, snoring, sleep apnea) and TMD-related pain. CONCLUSIONS: Our study suggests that short sleep may increase the risk of TMD-related pain, while there was no causal relationship between other sleep characteristics and TMD-related pain. Further studies are warranted to deepen and definitively clarify their relationship. CLINICAL RELEVANCE: These findings reveal that the short sleep may be a risk factor of TMD-related pain and highlight the potential therapeutical effect of extending sleep time on alleviating TMD-related pain.

Single-frequency orbital angular momentum switchable modes from a microchip laser.

We demonstrate the direct generation of single-frequency switchable orbital angular momentum (OAM) modes in a 1 µm wavelength range using a Nd:YVO4 microchip laser. The 808 nm laser diode pump beam is shaped into annular through an axicon associated with a lens. By adjusting the diameter and power of the annular pump beam, various OAM modes with different mode volumes can oscillate inside the Nd:YVO4 microchip. Moreover, a single-frequency output is also available due to the short cavity of the microchip. In the proof-of-principle experiment, single-frequency twofold multiplexed OAM modes | ± 1> and | ± 2> are generated, with experimentally measured fidelity higher than 96%. This work presents a compact and versatile single-frequency OAM source and will inspire multiple advanced scenarios ranging from classical to quantum photonics.

CTHRC1 is a prognostic biomarker correlated with immune infiltration in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common malignancy worldwide, characterized by high morbidity, high mortality, and poor prognosis. Collagen triple helix repeat containing 1 (CTHRC1) has been shown to be highly expressed in various cancers. However, its biological functions, potential role as a biomarker, and its relationship with immune infiltrates in HNSCC remain unclear. Our principal objective was to analyze CTHRC1 expression, its prognostic implications, biological functions, and its effects on the immune system in HNSCC patients using bioinformatics analysis. METHODS: The expression matrix was obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). CTHRC1 expression in HNSCC was analyzed between tumor and adjacent normal tissues, different stages were compared, and its impact on clinical prognosis was assessed using Kaplan-Meier analysis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Variation Analysis (GSVA) were employed for enrichment analysis. The Search Tool for the Retrieval of Interacting Genes database (STRING) was used to analyze protein-protein interactions. Pearson correlation tests were used to investigate the association between CTHRC1 expression and immune checkpoints. The correlation between CTHRC1 and immune infiltration was investigated using CIBERSORT, TIMER, and ESTIMATE. RESULTS: Compared to adjacent normal tissues, CTHRC1 was found to be highly overexpressed in tumors. Increased expression of CTHRC1 was more evident in the advanced stage of HNSCC and predicted a poor prognosis. Most genes related to CTHRC1 in HNSCC were enriched in physiological functions of Extracellular matrix(ECM) and tumor. Furthermore, several immune checkpoints, such as TNFSF4 and CD276 have been shown to be associated with CTHRC1 expression. Notably, the level of CTHRC1 expression correlated significantly with immune infiltration levels, particularly activated macrophages in HNSCC. CONCLUSIONS: High expression of CTHRC1 predicts poor prognosis and is associated with immune infiltration in HNSCC, confirming its utility as a tumor marker for HNSCC. TRIAL REGISTRATION: Not applicable. All data are from public databases and do not contain any clinical trials.

User-Friendly Replication-Competent MAdV-1 Vector System with a Cloning Capacity of 3.3 Kilobases.

Mouse adenoviruses (MAdV) play important roles in studying host-adenovirus interaction. However, easy-to-use reverse genetics systems are still lacking for MAdV. An infectious plasmid pKRMAV1 was constructed by ligating genomic DNA of wild-type MAdV-1 with a PCR product containing a plasmid backbone through Gibson assembly. A fragment was excised from pKRMAV1 by restriction digestion and used to generate intermediate plasmid pKMAV1-ER, which contained E3, fiber, E4, and E1 regions of MAdV-1. CMV promoter-controlled GFP expression cassette was inserted downstream of the pIX gene in pKMAV1-ER and then transferred to pKRMAV1 to generate adenoviral plasmid pKMAV1-IXCG. Replacement of transgene could be conveniently carried out between dual BstZ17I sites in pKMAV1-IXCG by restriction-assembly, and a series of adenoviral plasmids were generated. Recombinant viruses were rescued after transfecting linearized adenoviral plasmids to mouse NIH/3T3 cells. MAdV-1 viruses carrying GFP or firefly luciferase genes were characterized in gene transduction, plaque-forming, and replication in vitro or in vivo by observing the expression of reporter genes. The results indicated that replication-competent vectors presented relevant properties of wild-type MAdV-1 very well. By constructing viruses bearing exogenous fragments with increasing size, it was found that MAdV-1 could tolerate an insertion up to 3.3 kb. Collectively, a replication-competent MAdV-1 vector system was established, which simplified procedures for the change of transgene or modification of E1, fiber, E3, or E4 genes.

A MYB-related transcription factor regulates effector gene expression in an oomycete pathogen.

Phytophthora pathogens possess hundreds of effector genes that exhibit diverse expression patterns during infection, yet how the expression of effector genes is precisely regulated remains largely elusive. Previous studies have identified a few potential conserved transcription factor binding sites (TFBSs) in the promoters of Phytophthora effector genes. Here, we report a MYB-related protein, PsMyb37, in Phytophthora sojae, the major causal agent of root and stem rot in soybean. Yeast one-hybrid and electrophoretic mobility shift assays showed that PsMyb37 binds to the TACATGTA motif, the most prevalent TFBS in effector gene promoters. The knockout mutant of PsMyb37 exhibited significantly reduced virulence on soybean and was more sensitive to oxidative stress. Consistently, transcriptome analysis showed that numerous effector genes associated with suppressing plant immunity or scavenging reactive oxygen species were down-regulated in the PsMyb37 knockout mutant during infection compared to the wild-type P. sojae. Several promoters of effector genes were confirmed to drive the expression of luciferase in a reporter assay. These results demonstrate that a MYB-related transcription factor contributes to the expression of effector genes in P. sojae.

Identification and Verification of Endoplasmic Reticulum Stress-Related Genes as Novel Signatures for Osteoarthritis Diagnosis and Therapy: A Bioinformatics Analysis-Oriented Pilot Study.

BACKGROUND AND PURPOSE: Endoplasmic reticulum stress (ERS) has been reported to be closely associated with the development of osteoarthritis (OA), but the underlying mechanisms are not fully delineated. The present study was designed to investigate the involvement of ERS-related genes in regulating OA progression. METHODS: The expression profiles of OA patients and normal people were downloaded from the gene expression omnibus (GEO) database. The differentially expressed genes (DEGs) in datasets GSE55457 and GSE55235 were screened and identified by R software with the construction of the protein-protein interaction (PPI) networks. Through the STRING and Venn diagram analysis, hub ERS-related genes were obtained. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed. Biomarkers with high diagnostic values of osteoarthritis (OA) were studied. The hematoxylin and eosin (H&E) staining and micro-CT were applied to evaluate the establishment of the OA model. The expression levels of biomarkers were validated with the use of reverse transcription­quantitative polymerase chain reaction (RT-qPCR) and western blot. Finally, we evaluated the correlations of hub ERS-related genes with the immune infiltration cells via the CIBERSORT algorithm. RESULTS: A total of 60 downregulated and 52 upregulated DEGs were identified, and the following GO and KEGG pathway analyses verified that those DEGs were mainly enriched in biological process (BP), cellular component (CC), molecular function (MF), and inflammation-associated signal pathways. Interestingly, among all the DEGs, six ER stress-associated genes, including activating transcription factor 3 (ATF3), DEAD-Box Helicase 3 X-Linked (DDX3X), AP-1 transcription factor subunit (JUN), eukaryotic initiation factor 4 (EIF4A1), KDEL endoplasmic reticulum protein retention receptor 3 (KDELR3), and vascular endothelial growth factor A (VEGFA), were found to be closely associated with OA progression, and the following RT-qPCR and Western Blot analysis confirmed that DDX3X, JUN, and VEGFA were upregulated, whereas KDELR3, EIF4A1, and ATF3 were downregulated in OA rats tissues compared to the normal tissues, which were in accordance with our bioinformatics findings. Furthermore, our receiver operating characteristic (ROC) curve analysis verified that the above six ER stress-associated genes could be used as ideal biomarkers for OA diagnosis and those genes also potentially regulated immune responses by influencing the biological functions of mast cells and macrophages. CONCLUSION: Collectively, the present study firstly identified six ER stress-associated genes (ATF3, DDX3X, JUN, EIF4A1, KDELR3, and VEGFA) that may play critical role in regulating the progression of OA.

Complete telomere-to-telomere genomes uncover virulence evolution conferred by chromosome fusion in oomycete plant pathogens.

Variations in chromosome number are occasionally observed among oomycetes, a group that includes many plant pathogens, but the emergence of such variations and their effects on genome and virulence evolution remain ambiguous. We generated complete telomere-to-telomere genome assemblies for Phytophthora sojae, Globisporangium ultimum, Pythium oligandrum, and G. spinosum. Reconstructing the karyotype of the most recent common ancestor in Peronosporales revealed that frequent chromosome fusion and fission drove changes in chromosome number. Centromeres enriched with Copia-like transposons may contribute to chromosome fusion and fission events. Chromosome fusion facilitated the emergence of pathogenicity genes and their adaptive evolution. Effectors tended to duplicate in the sub-telomere regions of fused chromosomes, which exhibited evolutionary features distinct to the non-fused chromosomes. By integrating ancestral genomic dynamics and structural predictions, we have identified secreted Ankyrin repeat-containing proteins (ANKs) as a novel class of effectors in P. sojae. Phylogenetic analysis and experiments further revealed that ANK is a specifically expanded effector family in oomycetes. These results revealed chromosome dynamics in oomycete plant pathogens, and provided novel insights into karyotype and effector evolution.

Preparation and characterization of cellulose fluorescent material: Experiment and simulation.

The extensive use of fossil based materials has caused serious pollution problems, the full utilization of biomass resources to prepare high value-added new materials is of great significance for the environmental protection and sustainable social development. For this purpose, this study explored the preparation process and molecular dynamics simulation of cellulose fluorescent materials. Firstly, bacterial cellulose was dissolved in a solution of NaOH and urea at low temperature, followed by a solution blending and hot pressing with hyperbranched polyamide. It was found that the addition of hyperbranched polyamide could effectively filled in the internal pores of cellulose hydrogel, thereby enhancing the fluorescence effects and tensile properties, especially the elongation at break of cellulose materials. The optimal amount of hyperbranched polyamide added was 5 wt%. Molecular dynamics simulation showed that the hydrogen bonds and interaction with cellulose increased as the concentration of hyperbranched polyamide increased.