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Abstract Background Cholangiocarcinoma (CCA) is a biliary epithelial malignant tumor with an increasing incidence worldwide. Therefore, further understanding of the molecular mechanisms of CCA progression is required to identify new therapeutic targets. Methods The expression of RPL35A in CCA and para-carcinoma tissues was detected by immunohistochemical staining. IP-MS combined with Co-IP identified downstream proteins regulated by RPL35A. Western blot and Co-IP of CHX or MG-132 treated CCA cells were used to verify the regulation of HSPA8 protein by RPL35A. Cell experiments and subcutaneous tumorigenesis experiments in nude mice were performed to evaluate the effects of RPL35A and HSPA8 on the proliferation, apoptosis, cell cycle, migration of CCA cells and tumor growth in vivo. Results RPL35A was significantly upregulated in CCA tissues and cells. RPL35A knockdown inhibited the proliferation and migration of HCCC-9810 and HUCCT1 cells, induced apoptosis, and arrested the cell cycle in G1 phase. HSPA8 was a downstream protein of RPL35A and overexpressed in CCA. RPL35A knockdown impaired HSPA8 protein stability and increased HSPA8 protein ubiquitination levels. RPL35A overexpression promoted CCA cell proliferation and migration. HSPA8 knockdown inhibited CCA cell proliferation and migration, and reversed the promoting effect of RPL35A. Furthermore, RPL35A promoted tumor growth in vivo. In contrast, HSPA8 knockdown suppressed tumor growth, while was able to restore the effects of RPL35A overexpression. Conclusion RPL35A was upregulated in CCA tissues and promoted the progression of CCA by mediating HSPA8 ubiquitination.

The phases of high-entropy alloys (HEAs) are crucial to their material properties. Although meta-learning can recommend a desirable algorithm for materials designers, it does not utilize the optimal solution information of similar historical problems in the HEA field. To address this issue, a transferable meta-learning model (MTL-AMWO) based on an adaptive migration walrus optimizer is proposed to predict the phases of HEAs. Firstly, a transferable meta-learning algorithm frame is proposed, which consists of meta-learning based on adaptive migration walrus optimizer, balanced-relative density peaks clustering, and transfer strategy. Secondly, an adaptive migration walrus optimizer model is proposed, which adaptively migrates walruses according to the changes in the average fitness value of the population over multiple iterations. Thirdly, balanced-relative density peaks clustering is proposed to cluster the samples in the source and target domains into several clusters with similar distributions, respectively. Finally, the transfer strategy adopts the maximum mean discrepancy to find the most matching historical problem and transfer its optimal solution information to the target domain. The effectiveness of MTL-AMWO is validated on 986 samples from six datasets, including 323 quinary HEAs, 366 senary HEAs, and 297 septenary HEAs. The experimental results show that the MTL-AMWO achieves better performance than other algorithms.

The precise editing of genes mediated by CRISPR-Cas9 necessitates the application of donor DNA with appropriate lengths of homologous arms and fragment sizes. Our previous development, SSB/CRISPR-Cas9, has demonstrated high efficiency in homologous recombination and non-homologous end joining gene editing within bacteria. In this study, we optimized the lengths and sizes of homologous arms of the donor DNA within this system. Two sets of donor DNA constructs were generated: one set comprised donors with only 10–100 bp homologous arms, while the other set included donors with homologous arms ranging from 10–100 bp, between which was a tetracycline resistance expression cassette (1439 bp). These donor constructs were transformed into Escherichia coli MG1655 cells alongside pCas-SSB/pTargetF-lacZ. Notably, when the homologous arms ranged from 10 to 70 bp, the transformation efficiency of non-selectable donors was significantly higher than that of selectable donors. However, within the range of 10–100 bp homologous arm lengths, the homologous recombination rate of selectable donors was significantly higher than that of non-selectable donors, with the gap narrowing as the homologous arm length increased. For selectable donor DNA with homologous arm lengths of 10–60 bp, the homologous recombination rate increased linearly, reaching a plateau when the homologous arm length was between 60–100 bp. Conversely, for non-selectable donor DNA, the homologous recombination rate increased linearly with homologous arm lengths of 10–90 bp, plateauing at 90–100 bp. Editing two loci simultaneously with 100 bp homologous arms, whether selectable or non-selectable, showed no difference in transformation or homologous recombination rates. Editing three loci simultaneously with 100 bp non-selectable homologous arms resulted in a 45% homologous recombination rate. These results suggest that efficient homologous recombination gene editing mediated by SSB/CRISPR-Cas9 can be achieved using donor DNA with 90–100 bp non-selectable homologous arms or 60–100 bp selectable homologous arms.

Abstract Biomolecular condensates assembled through phase transitions regulate diverse aspects of plant growth, development, and stress responses. How biomolecular condensates control plant immunity is poorly understood. In Nature Plants, a new study (Zhou et al., Nat Plants 9:289–301, 2023) reveals how plants assemble translational condensates to balance tissue health and disease resistance.

Abstract Background Diabetic retinopathy (DR), a specific neuron-vascular complication of diabetes, is a major cause of vision loss among middle-aged people worldwide, and the number of DR patients will increase with the increasing incidence of diabetes. At present, it is limited in difficult detection in the early stages, limited treatment and unsatisfactory treatment effects in the advanced stages. Main body The pathogenesis of DR is complicated and involves epigenetic modifications, oxidative stress, inflammation and neovascularization. These factors influence each other and jointly promote the development of DR. DNA methylation is the most studied epigenetic modification, which has been a key role in the regulation of gene expression and the occurrence and development of DR. Thus, this review investigates the relationship between DNA methylation and other complex pathological processes in the development of DR. From the perspective of DNA methylation, this review provides basic insights into potential biomarkers for diagnosis, preventable risk factors, and novel targets for treatment. Conclusion DNA methylation plays an indispensable role in DR and may serve as a prospective biomarker of this blinding disease in its relatively early stages. In combination with inhibitors of DNA methyltransferases can be a potential approach to delay or even prevent patients from getting advanced stages of DR.

Low temperature inhibits the regeneration of amputated tails of Gekko japonicus by influencing the energy sensory Akt/mTOR pathway, which is also modulated by injury-induced Wnt signal.

Abstract To systematically evaluate the effects of metformin on tumors in experimental animal models of different types of cancer. Pubmed, Embase, Cochrane, and Web of Science databases were searched for studies on metformin used in various experimental animal tumor models from 2008 to 2022. Meta-analysis was performed using STATA 16.0 software after screening literature extraction data and methodological quality evaluation by inclusion and exclusion criteria. A total of 24 studies with 1108 model animals were included. Meta-analysis results showed that this study used meta-analysis for quantitative synthesis of study results and found that tumor model animals of different species showed different degrees of reduction in tumor volume, weight, and number after metformin intervention.

(1) Background: CREB-binding protein (CBP) is a key transcriptional coactivator of androgen receptors (AR). We conducted this study to investigate the effects of CBP on AR expression and proliferation in benign prostatic hyperplasia (BPH) prostate epithelial cells. (2) Methods: By analyzing a published data set, we found that CBP was closely related to the gene expression of AR in prostate cells. We enrolled 20 BPH patients who underwent transurethral resection of the prostate (TURP) in Peking University First Hospital in 2022, and analyzed the expressions of CBP and AR in BPH prostate tissues. Then, we used ICG-001 and shRNA to inhibit CBP in prostate epithelial cells (BPH-1 cells and RWPE-1 cells), and conducted immunofluorescence, cell viability assay, flow cytometry analysis, and Western blot to analyze the effects of CBP on AR expression and proliferation in prostate epithelial cells. We also studied the interaction between CBP and AR through a co-immunoprecipitation assay. (3) Results: CBP is consistent with AR in expression intensity in prostate tissues. Inhibiting CBP decreases AR expression, and induces proliferation inhibition, apoptosis, and cell cycle arrest in BPH prostate epithelial cells. The co-immunoprecipitation assay showed that CBP binds with AR to form transcription complexes in prostate epithelial cells. (4) Conclusions: Inhibiting CBP decreases AR expression and inhibits proliferation in benign prostate epithelial cells. CBP may be a potential target to affect AR expression and the proliferation of prostate epithelial cells in BPH.

The aim of our study is to reveal the hub genes related to the pathogenesis of chronic rhinosinusitis with nasal polyps (CRSwNP) and their association with immune cell infiltration through bioinformatics analysis combined with experimental validation. In this study, through differential gene expression analysis, 1,516 upregulated and 1,307 downregulated DEG were obtained from dataset GSE136825 of the GEO database. We identified 14 co-expressed modules using weighted gene co-expression network analysis (WGCNA), among which the most significant positive and negative correlations were MEgreen and MEturquoise modules, containing 1,540 and 3,710 genes respectively. After the intersection of the two modules and DEG, two gene sets—DEG-MEgreen and DEG-MEturquoise—were obtained, containing 395 and 1,168 genes respectively. Through GO term analysis, it was found that immune response and signal transduction are the most important biological processes. We found, based on KEGG pathway enrichment analysis, that osteoclast differentiations, cytokine–cytokine receptor interactions, and neuroactive ligand–receptor interactions are the most important in the two gene sets. Through PPI network analysis, we listed the top-ten genes for the concentrated connectivity of the two gene sets. Next, a few genes were verified by qPCR experiments, and FPR2, ITGAM, C3AR1, FCER1G, CYBB in DEG-MEgreen and GNG4, NMUR2, and GNG7 in DEG-MEturquoise were confirmed to be related to the pathogenesis of CRSwNP. NP immune cell infiltration analysis revealed a significant difference in the proportion of immune cells between the NP group and control group. Finally, correlation analysis between target hub genes and immune cells indicated that FPR2 and GNG7 had a positive or negative correlation with some specific immune cells. In summary, the discoveries of these new hub genes and their association with immune cell infiltration are of great significance for uncovering the specific pathogenesis of CRSwNP and searching for disease biomarkers and potential therapeutic targets.

In various engineering fields, the fusion of infrared and visible images has important applications. However, in the current process of fusing infrared and visible images, there are problems with unclear texture details in the fused images and unbalanced displays of infrared targets and texture details, resulting in information loss. In this article, we propose an improved generative adversarial network (GAN) fusion model for fusing infrared and visible images. In the generator and discriminator network structure, we introduce densely connected blocks to connect the features between layers, improve network efficiency, enhance the network’s ability to extract source image information, and construct a content loss function using four losses, including an infrared gradient, visible intensity, infrared intensity, and a visible gradient, to maintain a balance between infrared radiation information and visible texture details, enabling the fused image to achieve ideal results. The effectiveness of the fusion method is demonstrated through ablation experiments on the TNO dataset, and compared with four traditional fusion methods and three deep learning fusion methods. The experimental results show that our method achieves five out of ten optimal evaluation indicators, with a significant improvement compared to other methods.

Abstract Background As core units of organ tissues, cells of various types play their harmonious rhythms to maintain the homeostasis of the human body. It is essential to identify the characteristics of cells in human organs and their regulatory networks for understanding the biological mechanisms related to health and disease. However, a systematic and comprehensive single-cell transcriptional profile across multiple organs of a normal human adult is missing. Results We perform single-cell transcriptomes of 84,363 cells derived from 15 tissue organs of one adult donor and generate an adult human cell atlas. The adult human cell atlas depicts 252 subtypes of cells, including major cell types such as T, B, myeloid, epithelial, and stromal cells, as well as novel COCH + fibroblasts and FibSmo cells, each of which is distinguished by multiple marker genes and transcriptional profiles. These collectively contribute to the heterogeneity of major human organs. Moreover, T cell and B cell receptor repertoire comparisons and trajectory analyses reveal direct clonal sharing of T and B cells with various developmental states among different tissues. Furthermore, novel cell markers, transcription factors, and ligand-receptor pairs are identified with potential functional regulations in maintaining the homeostasis of human cells among tissues. Conclusions The adult human cell atlas reveals the inter- and intra-organ heterogeneity of cell characteristics and provides a useful resource in uncovering key events during the development of human diseases in the context of the heterogeneity of cells and organs.

CD30-directed chimeric antigen receptors (CARs) with single chain antibody fragment (scFv)-binding domains from murine HRS3 show strong cytotoxicity to Hodgkin’s Lymphoma cells and have been used in clinical trials. However, murine scFv in CAR might induce specific rejective immune responses in patients, which compromises the therapeutic effects. The use of human or humanized antibody fragments for CAR construction, rather than those derived from mouse antibodies, can reduce the immunogenicity of the CAR. Importantly, this strategy might simultaneously decrease the risk of cytokine-mediated toxicities and improve CAR T cell persistence. Murine HRS3 antibody has been successfully humanized by grafting the complementarity-determining regions (CDRs) from the mouse antibody framework onto human immunoglobulin consensus sequences, followed by an in vitro evolutionary strategy to select functional Fab fragments with the same affinity as murine sources. In this study, humanized scFvs were utilized to construct a CD30-directed CAR (hHRS3-CAR), and its effectiveness was compared with that of HRS3-CAR. The hHRS3-CAR-T cells specifically kill CD30-positive tumor cell lines in vitro and eliminate lymphoma xenografts in immunodeficient mice with comparable efficiency to HRS3-CAR. The hHRS-CAR-T could be used in clinical trials based on the previously reported advantages of humanized CARs, such as the reduction of immune rejection and better persistence of cells.

Cadherins play an important role in tissue homeostasis, as they are responsible for cell-cell adhesion during embryogenesis, tissue morphogenesis, and differentiation. In this study, we identified Cadherin-12 (CDH12), which encodes a type II classical cadherin, as a gene that promotes neurite outgrowth in an in vitro model of neurons with differentiated intrinsic growth ability. First, the effects of CDH12 on neurons were evaluated via RNA interference, and the results indicated that the knockdown of CDH12 expression restrained the axon extension of E18 neurons. The transcriptome profile of neurons with or without siCDH12 treatment revealed a set of pathways positively correlated with the effect of CDH12 on neurite outgrowth. We further revealed that CDH12 affected Rac1/Cdc42 phosphorylation in a PKA-dependent manner after testing using H-89 and 8-Bromo-cAMP sodium salt. Moreover, we investigated the expression of CDH12 in the brain, spinal cord, and dorsal root ganglia (DRG) during development using immunofluorescence staining. After that, we explored the effects of CDH12 on neurite outgrowth in vivo. A zebrafish model of CDH12 knockdown was established using the NgAgo-gDNA system, and the vital role of CDH12 in peripheral neurogenesis was determined. In summary, our study is the first to report the effect of CDH12 on axonal extension in vitro and in vivo, and we provide a preliminary explanation for this mechanism.

Scenes are important carriers of cultural expression. Cultural landscapes reveal specific cultural connotations through various scenes, and people understand and give things cultural connotations through scenes. In recent years, new techniques for visualizing cultural landscape heritage have been made possible by the advent of mapping and geographic information technology. The Beijing-Hangzhou Grand Canal’s culture is a “living” cultural legacy. As one of the key links in the canal’s cultural chain, Qingjiangpu is crucial to reproducing its cultural landscape. This paper first discusses the relationship between scene theory and the cultural landscape. Starting from the five elements of scene theory, through the collection of online text data and the corresponding data obtained from questionnaire research, the paper analyzed the scene constructed by the cultural landscape and the urban spirituality embodied by the scene. Through the deep excavation of cultural landscape and its historical context, the theoretical framework of “node-neighbor-city” cultural landscape reproduction is proposed. Taking the ancient city of Qingjiangpu as an example, the cultural landscape has been reproduced at different scales and in different dimensions through various technical means. This study can provide a theoretical basis and practical reference for the research of cultural landscape reproduction.

Protein S-nitrosylation is a reversible protein modification implicated in both physiological and pathophysiological regulation of protein function. However, the relationship between dysregulated S-nitrosylation homeostasis and diabetic vascular complications remains incompletely understood. Here, we demonstrate that basic fibroblast growth factor (bFGF) is a key regulatory link between S-nitrosylation homeostasis and inflammation, and alleviated endothelial dysfunction and angiogenic defects in diabetes. Subjecting human umbilical vein endothelial cells (HUVECs) to hyperglycemia and hyperlipidemia significantly decreased endogenous S-nitrosylated proteins, including S-nitrosylation of inhibitor kappa B kinase β (IKKβC179) and transcription factor p65 (p65C38), which was alleviated by bFGF co-treatment. Pretreatment with carboxy-PTIO (c-PTIO), a nitric oxide scavenger, abolished bFGF-mediated S-nitrosylation increase and endothelial protection. Meanwhile, nitrosylation-resistant IKKβC179S and p65C38S mutants exacerbated endothelial dysfunction in db/db mice, and in cultured HUVECs subjected to hyperglycemia and hyperlipidemia. Mechanistically, bFGF-mediated increase of S-nitrosylated IKKβ and p65 was attributed to synergistic effects of increased endothelial nitric oxide synthase (eNOS) and thioredoxin (Trx) activity. Taken together, the endothelial protective effect of bFGF under hyperglycemia and hyperlipidemia can be partially attributed to its role in suppressing inflammation via the S-nitrosylation pathway.

Vascular complications of diabetes are a serious challenge in clinical practice, and effective treatments are an unmet clinical need. Acidic fibroblast growth factor (aFGF) has potent anti-oxidative properties and therefore has become a research focus for the treatment of diabetic vascular complications. However, the specific mechanisms by which aFGF regulates these processes remain unclear. The purpose of this study was to investigate whether aFGF alleviates diabetic endothelial dysfunction by suppressing mitochondrial oxidative stress. We found that aFGF markedly decreased mitochondrial superoxide generation in both db/db mice and endothelial cells incubated with high glucose (30 mM) plus palmitic acid (PA, 0.1 mM), and restored diabetes-impaired Wnt/β-catenin signaling. Pretreatment with the Wnt/β-catenin signaling inhibitors IWR-1-endo (IWR) and ICG-001 abolished aFGF-mediated attenuation of mitochondrial superoxide generation and endothelial protection. Furthermore, the effects of aFGF on endothelial protection under diabetic conditions were suppressed by c-Myc knockdown. Mechanistically, c-Myc knockdown triggered mitochondrial superoxide generation, which was related to decreased expression and subsequent impaired mitochondrial localization of hexokinase 2 (HXK2). The role of HXK2 in aFGF-mediated attenuation of mitochondrial superoxide levels and EC protection was further confirmed by si-Hxk2 and a cell-permeable form of hexokinase II VDAC binding domain (HXK2VBD) peptide, which inhibits mitochondrial localization of HXK2. Taken together, these findings suggest that the endothelial protective effect of aFGF under diabetic conditions could be partly attributed to its role in suppressing mitochondrial superoxide generation via HXK2, which is mediated by the Wnt/β-catenin/c-Myc axis.

In the aerospace field, lightweight design is a never-ending pursuit. By integrating structural bionics and structural optimization, the vertical bracket of a wide angle auroral imager is designed and manufactured by additive manufacturing technology in this work. Initially, the classical topology optimization is utilized for the vertical bracket to find the optimal material layout and primary load carrying paths. Drawing on the width-to-diameter ratio and the bone mineral density distribution of human femur, the vertical support is designed as a bionic structure with a solid middle section and thin wall in other parts. Afterwards, size optimization is maintained for the bionic design model to obtain the optimal model. The simulation results show that the three-way eigenfrequencies of bionic optimized structure are 320 Hz, 303 Hz, and 765 Hz, respectively, which are closely approximate to the original structure. However, the mass of bionic optimized structure is reduced by 23%. Benefiting from Selective laser melting, the complex optimized design can be rapidly manufactured. The three-way eigenfrequencies of the optimized structure measured by the 0.2 g sweep tests are 307 Hz, 292 Hz, and 736 Hz, respectively. The vibration test of bionic optimized structure verifies the accuracy of the simulation results. This study indicates that the combination of structural bionics and structural optimization provides a powerful tool kit to the design of similar support structure for space applications.

Inflammation and proinflammatory cytokines have been implicated in the progression of benign prostatic hyperplasia (BPH). Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine. Our previous study found that MIF is highly expressed in BPH epithelium. It has been reported that there is a correlation between MIF and clinical BPH progression. However, whether MIF has an effect on BPH epithelial cells is not clear. The aim of this study was to explore whether MIF has a role in BPH. Our results showed that immunohistochemistry (IHC) showed that MIF is highly expressed in the epithelium and that MIF and PCNA expression levels are higher in BPH samples than in control. CCK8 and flow cytometry assays showed that recombinant human MIF (rMIF) promoted the proliferation of BPH-1 and PWR-1E cells, while ISO-1 partially reversed this effect on proliferation. JC-1 assays showed that rMIF inhibited the apoptosis of BPH-1 and PWR-1E cells, and ISO-1 could partially reverse this inhibition. Moreover, western blotting indicated that rMIF downregulated P53 and upregulated COX-2. Furthermore, MIF-induced proliferation could be inhibited by celecoxib in the CCK8 and flow cytometry assay. MIF-inhibited apoptosis could be partially reversed by celecoxib in the JC-1 assay. Western blotting showed that celecoxib could partially reverse MIF-induced COX-2 upregulation and P53 downregulation. Together, MIF is highly expressed in BPH epithelium. In vitro, MIF promoted BPH epithelial cell growth by regulating COX-2 and P53 signaling. Targeting MIF may provide a new option for the improved treatment of BPH in the future.

During the fieldwork of hydraulic engineering, practical engineers normally document geological information manually. Although there are some GIS-based digital tools for geology, they are not perfectly applicable to hydraulic engineering. As a result, the current work mode is ineffective, unmanageable, error-prone, and not conducive to subsequent analysis. To address this problem, we developed a digital tool which enables geological recording and quick modeling based on 3D real scenes in the field of hydropower projects. There are three modules in the surface tool: object recording, image interpretation, and field analysis. The object recording module is to mark geological points (e.g., drills and shafts), lines (e.g., faults, stratigraphic boundaries), and surfaces (e.g., slope and stocking yard) on a 3D scene and then store them in the database. The image interpretation is to interpret the 2D information in images to 3D models loaded in 3D software for further studies, such as GOCAD. The field analysis includes surface fitting, stability analysis of blocks, occurrences calculating, rock recognition, and 69/sketching. The tool is helpful for recording data, drawing geological boundaries, and building a preliminary model in the geological survey.

To understand the effects of diet and age on the rumen bacterial community and function, forty-eight dairy cattle at 1.5 (M1.5), 6 (M6), 9 (M9), 18 (M18), 23 (M23), and 27 (M27) months old were selected. Rumen fermentation profile, enzyme activity, and bacteria community in rumen fluid were measured. The acetate to propionate ratio (A/P) at M9, M18, and M23 was higher than other ages, and M6 was the lowest (p < 0.05). The total volatile fatty acid (TVFA) at M23 and M27 was higher than at other ages (p < 0.05). The urease at M18 was lower than at M1.5, M6, and M9, and the xylanase at M18 was higher than at M1.5, M23, and M27 (p < 0.05). Thirty-three bacteria were identified as biomarkers of the different groups based on the linear discriminant analysis (LDA) when the LDA score >4. The variation partitioning approach analysis showed that the age and diet had a 7.98 and 32.49% contribution to the rumen bacteria community variation, respectively. The richness of Succinivibrionaceae_UCG-002 and Fibrobacter were positive correlated with age (r > 0.60, p < 0.01) and positively correlated with TVFA and acetate (r > 0.50, p < 0.01). The Lachnospiraceae_AC2044_group, Pseudobutyrivibrio, and Saccharofermentans has a positive correlation (r > 0.80, p < 0.05) with diet fiber and a negative correlation (r < −0.80, p < 0.05) with diet protein and starch, which were also positively correlated with the acetate and A/P (r > 0.50, p < 0.01). The genera of Lachnospiraceae_AC2044_group, Pseudobutyrivibrio, and Saccharofermentans could be worked as the target bacteria to modulate the rumen fermentation by diet; meanwhile, the high age correlated bacteria such as Succinivibrionaceae_UCG-002 and Fibrobacter also should be considered when shaping the rumen function.

The oxygen evolution reaction (OER) is the efficiency-determining half-reaction process of high-demand, electricity-driven water splitting due to its sluggish four-electron transfer reaction. Tremendous effects on developing OER catalysts with high activity and strong acid-tolerance at high oxidation potentials have been made for proton-conducting polymer electrolyte membrane water electrolysis (PEMWE), which is one of the most promising future hydrogen-fuel-generating technologies. This review presents recent progress in understanding OER mechanisms in PEMWE, including the adsorbate evolution mechanism (AEM) and the lattice-oxygen-mediated mechanism (LOM). We further summarize the latest strategies to improve catalytic performance, such as surface/interface modification, catalytic site coordination construction, and electronic structure regulation of catalytic centers. Finally, challenges and prospective solutions for improving OER performance are proposed.

Plant immunity is tightly regulated to ensure proper defense against surrounding microbial pathogens without triggering autoimmunity, which negatively impacts plant growth and development. Immune receptor levels are intricately controlled by RNA processing and post-translational modification events, such as ubiquitination. It remains unknown whether, and if yes, how, plant immune receptor homeostasis is regulated at the translational level. From a mutant, snc1-enhancing (muse) forward genetic screen, we identified MUSE11/EXA1, which negatively regulates nucleotide-binding leucine-rich repeat (NLR) receptor mediated defence. EXA1 contains an evolutionarily conserved glycine-tyrosine-phenylalanine (GYF) domain that binds proline-rich sequences. Genetic and biochemical analysis revealed that loss of EXA1 leads to heightened NLR accumulation and enhanced resistance against virulent pathogens. EXA1 also associates with eIF4E initiation factors and the ribosome complex, likely contributing to the proper translation of target proteins. In summary, our study reveals a previously unknown mechanism of regulating NLR homeostasis through translational repression by a GYF protein.

The effects of water vapor ionization on the nonlinear propagation of femtosecond laser pulses with a 248 nm wavelength are numerically investigated in this paper. It is found that ionization of H2O molecules plays a significant role in air ionization, which seriously affects the dynamic and energy deposition of filamentation. The propagation of femtosecond pulses in air with different humidity levels are compared. The total number of electrons and total deposited pulse energy increase with the humidity increases. However, they tend to be saturated in high humidity conditions. Results presented here are conducive to characterizing the long-range propagation of filaments under atmospheric conditions.

Light scattering by non-spherical particles is an important factor influencing atmospheric radiative transfer. To accurately simulate the scattering properties of non-spherical particles, the Invariant Imbedded T-matrix method (IIM T-Matrix) is developed by combining the Lorenz−Mie theory and invariant imbedding technique. In this model, the non-spherical particle is regarded as an inhomogeneous sphere and discretized into multiple spherical layers in the spherical coordinate system. The T-matrix of the inscribed sphere is firstly calculated by the Lorenz−Mie theory, and then taking it as the initial value, the T-matrix is updated layer by layer by using the invariant imbedding technique. To improve the computational efficiency, the model is further parallelized by the OpenMP technique. To verify the simulation accuracy of the IIM T-Matrix method, the results of the model are compared with those of the EBCM (Extended Boundary Condition Method) T-Matrix method, DDA (Discrete Dipole Approximation) and MRTD (Multi-Resolution Time Domain). The results show that the scattering phase matrix simulated by the IIM T-Matrix method closely agrees with that of the well-tested models, indicating that the IIM T-Matrix method is a powerful tool for the light scattering simulation of non-spherical particles. Since the IIM T-Matrix method is derived from the volume integral equation, compared to the T-Matrix method which is based on surface integral principles (i.e., “EBCM” or the “null field method”), it can be applied to the scattering calculations of particle with arbitrary shapes and inhomogeneous compositions, which can greatly expand the application scope of the T-Matrix method.

The learning speed of online sequential extreme learning machine (OS-ELM) algorithms is much higher than that of convolutional neural networks (CNNs) or recurrent neural network (RNNs) on regression and simple classification datasets. However, the general feature extraction of OS-ELM makes it difficult to conveniently and effectively perform classification on some large and complex datasets, e.g., CIFAR. In this paper, we propose a flexible OS-ELM-mixed neural network, termed as fnnmOS-ELM. In this mixed structure, the OS-ELM can replace a part of fully connected layers in CNNs or RNNs. Our framework not only exploits the strong feature representation of CNNs or RNNs, but also performs at a fast speed in terms of classification. Additionally, it avoids the problem of long training time and large parameter size of CNNs or RNNs to some extent. Further, we propose a method for optimizing network performance by splicing OS-ELM after CNN or RNN structures. Iris, IMDb, CIFAR-10, and CIFAR-100 datasets are employed to verify the performance of the fnnmOS-ELM. The relationship between hyper-parameters and the performance of the fnnmOS-ELM is explored, which sheds light on the optimization of network performance. Finally, the experimental results demonstrate that the fnnmOS-ELM has a stronger feature representation and higher classification performance than contemporary methods.

Hammering rocks of different strengths can make different sounds. Geological engineers often use this method to approximate the strengths of rocks in geology surveys. This method is quick and convenient but subjective. Inspired by this problem, we present a new, non-destructive method for measuring the surface strengths of rocks based on deep neural network (DNN) and spectrogram analysis. All the hammering sounds are transformed into spectrograms firstly, and a clustering algorithm is presented to filter out the outliers of the spectrograms automatically. One of the most advanced image classification DNN, the Inception-ResNet-v2, is then re-trained with the spectrograms. The results show that the training accurate is up to 94.5%. Following this, three regression algorithms, including Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF) are adopted to fit the relationship between the outputs of the DNN and the strength values. The tests show that KNN has the highest fitting accuracy, and SVM has the strongest generalization ability. The strengths (represented by rebound values) of almost all the samples can be predicted within an error of [−5, 5]. Overall, the proposed method has great potential in supporting the implementation of efficient rock strength measurement methods in the field.

Phycocyanin, derived from Spirulina platensis, is a type of natural antineoplastic marine protein. It is known that phycocyanin exerts anticancer effects on non-small-cell lung cancer (NSCLC) cells, but its underlying mechanism has not been elucidated. Herein, the antitumor function and regulatory mechanism of phycocyanin were investigated in three NSCLC cell lines for the first time: H358, H1650, and LTEP-a2. Cell phenotype experiments suggested that phycocyanin could suppress the survival rate, proliferation, colony formation, and migration abilities, as well as induce apoptosis of NSCLC cells. Subsequently, transcriptome analysis revealed that receptor-interacting serine/threonine-protein kinase 1 (RIPK1) was significantly down-regulated by phycocyanin in the LTEP-a2 cell, which was further validated by qRT-PCR and Western blot analysis in two other cell lines. Interestingly, similar to phycocyanin-treated assays, siRNA knockdown of RIPK1 expression also resulted in growth and migration inhibition of NSCLC cells. Moreover, the activity of NF-κB signaling was also suppressed after silencing RIPK1 expression, indicating that phycocyanin exerted anti-proliferative and anti-migratory function through down-regulating RIPK1/NF-κB activity in NSCLC cells. This study proposes a mechanism of action for phycocyanin involving both NSCLC apoptosis and down regulation of NSCLC genes.

It is meaningful to study the geological structures exposed on the Earth’s surface, which is paramount to engineering design and construction. In this research, we used 2206 images with 12 labels to identify geological structures based on the Inception-v3 model. Grayscale and color images were adopted in the model. A convolutional neural network (CNN) model was also built in this research. Meanwhile, K nearest neighbors (KNN), artificial neural network (ANN) and extreme gradient boosting (XGBoost) were applied in geological structures classification based on features extracted by the Open Source Computer Vision Library (OpenCV). Finally, the performances of the five methods were compared and the results indicated that KNN, ANN, and XGBoost had a poor performance, with the accuracy of less than 40.0%. CNN was overfitting. The model trained using transfer learning had a significant effect on a small dataset of geological structure images; and the top-1 and top-3 accuracy of the model reached 83.3% and 90.0%, respectively. This shows that texture is the key feature in this research. Transfer learning based on a deep learning model can extract features of small geological structure data effectively, and it is robust in geological structure image classification.

Phycocyanin (PC), derived from cyanobacteria and Spirulina cells, is a type of natural antineoplastic marine protein. It has been reported that phycocyanin exerts an antitumor function in non-small cell lung cancer (NSCLC) cells, but the underlying mechanism has not been elucidated. In this research, a transcriptome study was performed to investigate the regulatory mechanisms of phycocyanin on human NSCLC A549 cells. The survival rate and proliferation ability of A549 cells were markedly reduced by phycocyanin, along with abnormal morphologic changes. The transcriptome analysis showed that 2970 genes were differentially expressed after phycocyanin treatment in A549 cells, including 1431 down-regulated and 1539 up-regulated genes. Gene ontology and KEGG analysis suggested that some classical pathways, such as Wnt, NF-κB, and PI3K-AKT signaling, were significantly enriched. Strikingly, protein⁻protein interaction (PPI) analysis showed that ubiquitin-C (UBC) occupied the highest degree (the highest number of interactions) in differential genes, indicating that it might play a key role in the phycocyanin-mediated regulatory process in A549 cells. Moreover, qRT-PCR results showed consistent expression trends of differential genes with transcriptome analysis. Consequently, this study has provided a theoretical basis for regulation of phycocyanin in A549 cells, which lays a foundation for the treatment of NSCLC.

Phycocyanin, a type of functional food colorant, is shown to have a potent anti-cancer property. Non-small cell lung cancer (NSCLC) is one of the most aggressive form of cancers with few effective therapeutic options. Previous studies have demonstrated that phycocyanin exerts a growth inhibitory effect on NSCLC A549 cells. However, its biological function and underlying regulatory mechanism on other cells still remain unknown. Here, we investigated the in vitro function of phycocyanin on three typical NSCLC cell lines, NCI-H1299, NCI-H460, and LTEP-A2, for the first time. The results showed that phycocyanin could significantly induce apoptosis, cell cycle arrest, as well as suppress cell migration, proliferation, and the colony formation ability of NSCLC cells through regulating multiple key genes. Strikingly, phycocyanin was discovered to affect the cell phenotype through regulating the NF-κB signaling of NSCLC cells. Our findings demonstrated the anti-neoplastic function of phycocyanin and provided valuable information for the regulation of phycocyanin in NSCLC cells.

The under-actuated foot rotation that the heel of the stance leg lifts off the ground and the body rotates around the stance toe is an important feature in human walking. However, it is absent in the realized walking gait for the majority of biped robots because of the difficulty and complexity in the control it brings about. In this paper, a hybrid control approach aiming to integrate the main characteristics of human walking into a simulated seven-link biped robot is presented and then verified with simulations. The bipedal robotic gait includes a fully actuated single support phase with the stance heel supporting the body, an under-actuated single support phase, with the stance toe supporting the body, and an instantaneous double support phase when the two legs exchange their roles. The walking controller combines virtual force control and foot placement control, which are applied to the stance leg and the swing leg, respectively. The virtual force control assumes that there is a virtual force which can generate the desired torso motion on the center of mass of the torso link, and then the virtual force is applied through the real torques on each actuated joint of the stance leg to create the same effect that the virtual force would have created. The foot placement control uses a path tracking controller to follow the predefined trajectory of the swing foot when walking forward. The trajectories of the torso and the swing foot are generated based on the cart-cable model. Co-simulations in Adams and MATLAB show that the desired gait is achieved with a biped robot under the action of the proposed method.