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Abstract Accelerating perovskite solid solution discovery and sustainable synthesis is crucial for addressing challenges in wireless communication and biosensors. However, the vast array of chemical compositions and their dependence on factors such as crystal structure, and sintering temperature require time-consuming manual processes. To overcome these constraints, we introduce an automated materials discovery approach encompassing machine learning (ML) assisted material screening, robotic synthesis, and high-throughput characterization. Our proposed platform for rapid sintering and dielectric analysis streamlines the characterization of perovskites and the discovery of disordered materials. The setup has been successfully validated, demonstrating processing materials within minutes, in stark contrast to conventional procedures that can take hours or days. Following setup validation with established samples, we showcase synthesizing single-phase solid solutions within the barium family, such as (BaxSr1-x)CeO3, identified through ML-guided chemistry.

AIM: To explore the current status, research hotspots, and trends of global uveitis research to provide a theoretical basis and references for researchers in the field of uveitis, and promote further development in this area.METHODS: Relevant literatures on uveitis were retrieved from the China National Knowledge Infrastructure(CNKI)database, Wanfang database, and Web of Science core collection database since their establishment until 24 August 2023. The country/publishing institutions, research authors, high-frequency keywords, and burst keywords were visual analyzed by using software such as GraphPad Prism 9, CiteSpace 6.2. R2, and VOSviewer.RESULTS: Research teams for uveitis have been formed in various countries globally. The top three countries in terms of publications are the United States of America(7 585 papers), the United Kingdom(2 412 papers)and Germany(1 679 papers). The top three foreign institutions in terms of publications are Harvard University, Oregon Health & Science University, and Moorfields Eye Hospital, while the top three domestic institutions are Affiliated Eye Hospital of Shandong University of Traditional Chinese Medicine, Chongqing Medical University, and Zhongshan Ophthalmic Center, Sun Yat-sen University. The analysis of high-frequency keywords and burst keywords in Chinese and English shows that research hotspots mainly focus on exploring pathogenesis and different treatment methods for uveitis. The research hotspots related to uveitis treatment are transitioning to molecular biology-related research topics, such as molecular biological signaling pathways(NF-κB signaling pathway with a strength value of 22.89), biological agents(adalimumab with a strength value of 32.21), and tumor necrosis factor(with a strength value of 48.44). Related research is also expanding to basic experiments on relevant rats.CONCLUSIONS: In recent years, the research hotspots and trends of global uveitis mainly focus on precise diagnosis, pathogenesis, and more effective treatment methods. It is important for more scholars to dedicate themselves to uveitis-related research in the future to make breakthroughs and progress in the field. More large-scale and multicenter clinical studies on uveitis can provide high-quality research evidence.

Summary: The integrated stress response (ISR) is activated in response to intrinsic and extrinsic stimuli, playing a role in tumor progression and drug resistance. The regulatory role and mechanism of ISR in liver cancer, however, remain largely unexplored. Here, we demonstrate that OTU domain-containing protein 3 (OTUD3) is a deubiquitylase of eukaryotic initiation factor 2α (eIF2α), antagonizing ISR and suppressing liver cancer. OTUD3 decreases interactions between eIF2α and the kinase EIF2ΑK3 by removing K27-linked polyubiquitylation on eIF2α. OTUD3 deficiency in mice leads to enhanced ISR and accelerated progression of N-nitrosodiethylamine-induced hepatocellular carcinoma. Additionally, decreased OTUD3 expression associated with elevated eIF2α phosphorylation correlates with the progression of human liver cancer. Moreover, ISR activation due to decreased OTUD3 expression renders liver cancer cells resistant to sorafenib, while the combined use of the ISR inhibitor ISRIB significantly improves their sensitivity to sorafenib. Collectively, these findings illuminate the regulatory mechanism of ISR in liver cancer and provide a potential strategy to counteract sorafenib resistance.

Three parts of the experiment were mainly carried out in this research: the effect of Ca on inclusions in 38CrMoAl high aluminum steel under atmospheric pressure, the effect of pressure on the solubility of Ca in pure iron under pressurized conditions, and the effect of Ca on inclusions in 38CrMoAl high aluminum steel under pressurized conditions. The results indicated that Ca can significantly transform the inclusions such as Al2O3 and MgO·Al2O3 with high melting points into calcium aluminate inclusions with low melting points. It was found that the pressure condition can significantly improve the solubility of Ca in pure iron and molten steel, which provided reliable data reference and guidance for popularizing Ca treatment of steel under pressure conditions in the future. Finally, the mechanism of inclusion transformation after Ca treatment was put forward. In this study, the theoretical calculation of thermodynamics was closely compared with the experimental data. It was proposed that to modify the inclusions in high aluminum steel into calcium aluminate inclusions with low melting points, it is necessary to accurately control Ca in the target region.

Cardiovascular research has heavily relied on studies using patient samples and animal models. However, patient studies often miss the data from the crucial early stage of cardiovascular diseases, as obtaining primary tissues at this stage is impracticable. Transgenic animal models can offer some insights into disease mechanisms, although they usually do not fully recapitulate the phenotype of cardiovascular diseases and their progression. In recent years, a promising breakthrough has emerged in the form of in vitro three-dimensional (3D) cardiovascular models utilizing human pluripotent stem cells. These innovative models recreate the intricate 3D structure of the human heart and vessels within a controlled environment. This advancement is pivotal as it addresses the existing gaps in cardiovascular research, allowing scientists to study different stages of cardiovascular diseases and specific drug responses using human-origin models. In this review, we first outline various approaches employed to generate these models. We then comprehensively discuss their applications in studying cardiovascular diseases by providing insights into molecular and cellular changes associated with cardiovascular conditions. Moreover, we highlight the potential of these 3D models serving as a platform for drug testing to assess drug efficacy and safety. Despite their immense potential, challenges persist, particularly in maintaining the complex structure of 3D heart and vessel models and ensuring their function is comparable to real organs. However, overcoming these challenges could revolutionize cardiovascular research. It has the potential to offer comprehensive mechanistic insights into human-specific disease processes, ultimately expediting the development of personalized therapies.

Abstract Background Osteosarcoma (OS) is one of the most common aggressive bone malignancy tumors in adolescents. With the application of new chemotherapy regimens, finding new and effective anti-OS drugs to coordinate program implementation is urgent for the patients of OS. Oridonin had been proved to mediate anti-tumor effect on OS cells, but its mechanism has not been fully elucidated. Methods The effects of oridonin on the viability, clonal formation and migration of 143B and U2OS cells were detected by CCK-8, colony formation assays and wound-healing test. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was used to explore the mechanism of oridonin on OS. Western blot (WB), real-time quantitative PCR (qRT-PCR) were used to detect the expression levels of apoptosis and ferroptosis-relative proteins and genes. Annexin V-FITC apoptosis detection kit and flow cytometry examination were used to detect the level of apoptosis. Iron assay kit was used to evaluate the relative Fe2+ content. The levels of mitochondrial membrane potential and lipid peroxidation production was determined by mitochondrial membrane potential detection kit and ROS assay kit. Results Oridonin could effectively inhibit the survival, clonal formation and metastasis of OS cells. The KEGG results indicated that oridonin is associated with the malignant phenotypic signaling pathways of proliferation, migration, and drug resistance in OS. Oridonin was capable of inhibiting expressions of BAX, cl-caspase3, SLC7A11, GPX4 and FTH1 proteins and mRNA, while promoting the expressions of Bcl-2 and ACSL4 in 143B and U2OS cells. Additionally, we found that oridonin could promote the accumulation of reactive oxygen species (ROS) and Fe2+ in OS cells, as well as reduce mitochondrial membrane potential, and these effects could be significantly reversed by the ferroptosis inhibitor ferrostatin-1 (Fer-1). Conclusion Oridonin can trigger apoptosis and ferroptosis collaboratively in OS cells, making it a promising and effective agent for OS therapy.

Vortex beams carrying orbital angular momentum (OAM) are considered to hold significant prospects in fields such as super-resolution imaging, high-capacity communications, and quantum optics. Therefore, the techniques of vortex beam generation have attracted extensive studies, in which the development of metasurfaces brings new vigor and vitality to it. However, the generation of reconfigurable vortex beams by metasurfaces at the incidence of arbitrary polarized electromagnetic (EM) waves holds challenges. In this study, an efficient and reconfigurable strategy utilizing PB phase-modulated circularly polarized waves and dynamic phase-modulated linearly polarized waves is proposed, enabling a polarization-locked fully polarization vortex beams generator. Based on this strategy, we designed and fabricated a prototype of the vortex beam generator for full polarization, which verifies the rotating Doppler effect and generates a time-varying vortex beam. All the results have been verified by simulation and measurements. In addition, the proposed strategy can be easily extended to other frequency regions and holds potential in areas such as information encryption, biosensing, and OAM multiplexing communication.

The interaction mechanism between coal and rock masses with supporting materials is significant in roadway control, especially in deep underground mining situations where dynamic hazards frequently happened due to high geo-stress and strong disturbed effects. This paper is to investigate the strain energy evolution in the interaction between coal and rock masses with self-designed energy-absorbing props and rock bolts by numerical modeling with the finite difference method. The interaction between rock and rock bolt/prop is accomplished by the cables element and the interface between the inner and outer props. Roadway excavation and coal extraction conditions in deep mining are numerically employed to investigate deformation, plastic zone ranges, strain energy input, accumulation, dissipation, and release. The effect on strain energy input, accumulation, dissipation, and release with rock deformation, and the plastic zone is addressed. A ratio of strain energy accumulation, dissipation, and release with energy input α, β, γ is to assess the dynamic hazards. The effects on roadway excavation and coal extraction steps of α, β, γ are discussed. The results show that: (1) In deep high geo-stress roadways, the energy-absorbing support system plays a dual role in resisting deformation and reducing the scope of plastic zones in surrounding rock, as well as absorbing energy release in the surrounding rock, especially in the coal extraction state to mitigate disturbed effects. (2) The strain energy input, accumulation is dependent on roadway deformation, the strain energy dissipation is relied on plastic zone area and disturbed effects, and strain energy release density is the difference among the three. The function of energy-absorbing rock bolts and props play a key role to mitigate strain energy release density and amount, especially in coal extraction condition, with a peak density value from 4×104 to 1×104 J/m3, and amount value from 3.57×108 to 1.90×106 J. (3) When mining is advanced in small steps, the strain energy accumulation is dominated. While in a large step, the released energy is dominant, thus a more dynamic hazards proneness. The energy-absorbing rock bolt and prop can reduce three times strain energy release amount, thus reducing the dynamic hazards. The results suggest that energy-absorbing props and rock bolts can effectively reduce the strain energy in the coal and rock masses, and prevent rock bursts and other hazards. The numerical model developed in this study can also be used to optimize the design of energy-absorbing props and rock bolts for specific mining conditions.

Seawater desalination is one of the effective means to efficiently consume renewable energy and to improve the flexibility of system control in the new power system. In the optimal operation of new power systems, seawater desalination is usually considered as an entirety, and a motor equivalent model is used to simulate the overall external characteristics of seawater desalination. The characteristics of multiple sets of motors with multiple equipment processes inside the seawater desalination are neglected, which makes operation control characteristics inaccurate. In order to solve the above-mentioned problems, this paper firstly studies a seawater desalination system composed of 12 motors, and introduces the specific parameters of these 12 motors in detail. Secondly, after comprehensively considering the constraints of water flow, water pressure, and other factors, three control strategies are proposed for the 12 motors, respectively. Then, a detailed mathematical model of seawater desalination units and an optimal operation model of a new power system with seawater desalination are established. The optimization model aims at the minimum operating cost of seawater desalination, and considers the constraints of practical problems comprehensively such as motor power requirements and water storage capacity. Finally, the grey wolf optimization algorithm (GWO) is used in this paper to solve the optimization problem. The simulation results show that the model proposed in this paper can precisely control each unit in the seawater desalination system and improve the economic benefits of the system. Compared with the Particle Swarm Optimization algorithm (PSO) and the Moth-flame Optimization algorithm (MFO), the algorithm used in this paper can find the global optimal solution, and has both faster convergence speed and wider practicability.

Multifactorial diseases demand therapeutics that can modulate multiple targets for enhanced safety and efficacy, yet the clinical approval of multitarget drugs remains rare. The integration of machine learning (ML) and deep learning (DL) in drug discovery has revolutionized virtual screening. This study investigates the synergy between ML/DL methodologies, molecular representations, and data augmentation strategies. Notably, we found that SVM can match or even surpass the performance of state-of-the-art DL methods. However, conventional data augmentation often involves a trade-off between the true positive rate and false positive rate. To address this, we introduce Negative-Augmented PU-bagging (NAPU-bagging) SVM, a novel semi-supervised learning framework. By leveraging ensemble SVM classifiers trained on resampled bags containing positive, negative, and unlabeled data, our approach is capable of managing false positive rates while maintaining high recall rates. We applied this method to the identification of multitarget-directed ligands (MTDLs), where high recall rates are critical for compiling a list of interaction candidate compounds. Case studies demonstrate that NAPU-bagging SVM can identify structurally novel MTDL hits for ALK-EGFR with favorable docking scores and binding modes, as well as pan-agonists for dopamine receptors. The NAPU-bagging SVM methodology should serve as a promising avenue to virtual screening, especially for the discovery of MTDLs.

This research endeavors to characterize the primary factors that influence the formation of Ordovician karst caves in the Keping area of China. A 3D digital model of the cave structure and fracture sets was generated using an Unmanned Aerial Vehicle (UAV). The characterization of fracture and cavity development involved the examination of thin sections, fluid inclusion testing, and the analysis of C and O isotopes. Key parameters controlling karst development were identified through the application of multiple linear regressions and statistical analysis. The Ordovician limestone karst cave exhibited four distinct fracture sets. Set 1 consisted of partially filled fractures with a sub-horizontal orientation and a striking direction of SEE, interpreted to have formed during the Middle-Late Caledonian orogeny. Set 2 comprised inclined tensile-shear fractures with a striking direction of NEE, likely formed during the Early Hercynian orogeny. Set 3 included fully filled conjugate shear fractures with variable orientations, which developed during the Indo-Yanshanian orogeny. Set 4 comprised high-angle shear fractures with striking directions of NNE 20–40° and NEE 60–80°, formed during the Himalayan orogeny. Two stages of cave filling deposition were identified. Stage I coincided with the Middle-Late Caledonian Set 1 fractures and can be attributed to the circulation of freshwater fluid. Stage II occurred concurrently with the Early Hercynian Set 2 fractures and can be attributed to deep hydrothermal fluid circulation. The karst caves are interconnected and aligned along a fault zone. The Ordovician limestone possesses high permeability, which facilitates karst development. The lithologies in the Aksu area play a crucial role in cavity formation and dissolution. The development of cavities is influenced by the combined patterns of the fracture system, with larger fault and fracture zones resulting in larger cave sizes. As one moves away from the fault zone, limestone dissolution decreases, resulting in less pronounced karst development.

This paper aims to investigate the effectiveness and influencing factors of different machine learning algorithms on soccer footwork recognition. In this paper, we use inertial sensors to obtain the basic data of soccer players’ movements, then convert them into initial data of footwork using pose representation and pose-solving filtering. The value of K mainly influences the classification accuracy of KNN, and the highest accuracy of 67.23% is achieved when K is 5. The classification accuracy of SVM is related to the choice of the distance function. The accuracy of CNN is mainly affected by the size of the convolutional kernel and the convolutional step size, and the highest accuracy is 73.82%. The machine learning-based soccer step recognition can improve the recognition accuracy of traditional physical methods and provide scientific sports guidance for soccer players’ training.

Human metapneumovirus (HMPV) is a common virus associated with acute respiratory distress syndrome in pediatric patients. There are no HMPV vaccines or therapeutics that have been approved for prevention or treatment. In this study, we constructed a novel recombinant influenza virus carrying partial HMPV fusion protein (HMPV-F), termed rFLU-HMPV/F-NS, utilizing reverse genetics, which contained (HMPV-F) in the background of NS segments of influenza virus A/PuertoRico/8/34(PR8). The morphological characteristics of rFLU-HMPV/F-NS were consistent with the wild-type flu virus. Additionally, immunofluorescence results showed that fusion proteins in the chimeric rFLU-HMPV/F-NS could work well, and the virus could be stably passaged in SPF chicken embryos. Furthermore, intranasal immunization with rFLU-HMPV/F-NS in BALB/c mice induced robust humoral, mucosal and Th1-type dominant cellular immune responses in vivo. More importantly, we discovered that rFLU-HMPV/F-NS afforded significant protective efficacy against the wild-type HMPV and influenza virus challenge, with significantly attenuated pathological changes and reduced viral titers in the lung tissues of immunized mice. Collectively, these findings demonstrated that chimeric recombinant rFLU-HMPV/F-NS as a promising HMPV candidate vaccine has potentials for the development of HMPV vaccine.

Ferroelectric (FE) thin films have recently attracted renewed interest in research due to their great potential for designing novel tunable electromagnetic devices such as large intelligent surfaces (LISs). However, the mechanism of how a polar structure in the FE thin films contributes to desired tunable performance, especially within the microwave frequency range, which is the most widely used frequency range of electromagnetics, has not been illustrated clearly. In this paper, we described several straightforward and cost-effective methods to fabricate and characterize Ba0.6Sr0.4TiO3 (BST) thin films at microwave frequencies. The prepared BST thin films here exhibit homogenous structures and great tunability (η) in a wide frequency and temperature range when the applied field is in the out-of-plane direction. The high tunability can be attributed to high concentration of polar nanoclusters. Their response to the applied direct current (DC) field was directly visualized using a novel non-destructive near-field scanning microwave microscopy (NSMM) technique. Our results have provided some intriguing insights into the application of the FE thin films for future programmable high-frequency devices and systems.

Oil-impregnated paper is the most widely used insulating material for power transformers. Power transformers inevitably generate a lot of heat during operation. Among them, thermal aging is one of the main forms of aging for insulating paper. In this study, the ab initio molecular dynamics method based on the density functional theory is used to simulate the cracking mechanism of cellobiose under transient high temperature. The results show that the cellobiose is relatively stable at 343 K, the motility of the cellobiose is enhanced at 1,800 K, the cellobiose starts to decompose at 2,400 K, and new characteristic products are formed at 3,000 K. The characteristic products include CO, H2O, CH3OH, H2, and CH4. These characteristic products can represent the degree of cracking of insulating paper. Therefore, it is necessary to explore the mechanism of cracking of insulating paper caused by transient high temperature.

Abstract A CO2-based Enhanced Geothermal System (CO2-EGS) has dual benefits of heat extraction and CO2 storage. Mineralization storage of CO2 may reduce reservoir permeability, thereby affecting heat extraction. Solutions require further research to optimize and balance these two benefits. In this study, CO2 storage and heat extraction were simulated by alternating cyclic injection of water and supercritical CO2 into fractured granite. By analyzing the changes of ion composition in water samples and the minerals of fracture surface, the mechanisms controlling the fracture permeability with and without proppant were obtained. The results suggest that monticellite and vaterite were formed besides montmorillonite, calcite and illite after increasing the injection cycles. This promotes mineralization storage of CO2 but reduces reservoir permeability. Without proppant, the permeability decreased in three stages and the reduction rate exhibited a sharp-slow–fast–slow trend. While the use of proppant caused an increase of two orders of magnitude in permeability. Therefore, increasing the non-contact area of the main fracture and the CO2 flow velocity can avoid a large decrease in permeability, which will increase the heat extraction and mineralization storage of CO2. The findings provide solutions for the CO2 emission reduction and the efficient exploitation of hot dry rock.

Abstract Monocots are a major taxon within flowering plants, have unique morphological traits, and show an extraordinary diversity in lifestyle. To improve our understanding of monocot origin and evolution, we generate chromosome-level reference genomes of the diploid Acorus gramineus and the tetraploid Ac. calamus, the only two accepted species from the family Acoraceae, which form a sister lineage to all other monocots. Comparing the genomes of Ac. gramineus and Ac. calamus, we suggest that Ac. gramineus is not a potential diploid progenitor of Ac. calamus, and Ac. calamus is an allotetraploid with two subgenomes A, and B, presenting asymmetric evolution and B subgenome dominance. Both the diploid genome of Ac. gramineus and the subgenomes A and B of Ac. calamus show clear evidence of whole-genome duplication (WGD), but Acoraceae does not seem to share an older WGD that is shared by most other monocots. We reconstruct an ancestral monocot karyotype and gene toolkit, and discuss scenarios that explain the complex history of the Acorus genome. Our analyses show that the ancestors of monocots exhibit mosaic genomic features, likely important for that appeared in early monocot evolution, providing fundamental insights into the origin, evolution, and diversification of monocots.

AIM: To investigate the effectiveness of a modified inferior oblique muscle belly transposition for treatment of V-pattern exotropia combined with mild to moderate inferior oblique muscle overaction. METHODS: Thirteen cases (23 affected eyes) of V-pattern exotropia with inferior oblique muscle overaction (+ or ++) who underwent the modified inferior oblique muscle belly transposition procedure were retrospectively reviewed. The amount of V-pattern, grade of inferior oblique overaction, degree of vertical strabismus, abnormal head posture, and the fovea-disc angle were evaluated before and after surgery. RESULTS: The V-pattern was corrected in all cases, and the amount of V-pattern reduced by 17.85±5.13 prism diopter (PD) on average (t=16.07, P

Objective To conduct a systematic review and meta-analysis evaluating the diagnostic value of folate receptor-positive (FR+) circulating tumour cells (CTCs) as a potential tumour marker for lung cancer diagnosis. Methods The PubMed, Embase, and Web of Science databases were searched for relevant articles published between database inception and November 2022. Eligible studies were selected based on inclusion and exclusion criteria. Sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and area under the curve (AUC) were pooled with 95% confidence intervals (CI), using RevMan 5.4 and STATA 17.0 software to assess the diagnostic value of FR+CTC for lung cancer. Results After screening, 11 studies involving 3469 subjects were eligible for inclusion. The pooled sensitivity and specificity were 0.79 (95% CI 0.76, 0.82) and 0.84 (95% CI 0.81, 0.96), respectively, and the pooled positive and negative likelihood ratios were 4.90 (95% CI 4.25, 5.65) and 0.25 (95% CI 0.22, 0.29), respectively. The pooled diagnostic odds ratio was 19.70 (95% CI 16.06, 24.16). The AUC of the pooled summary receiver operating characteristic curve was 0.89 (95% CI 0.85, 0.91). Sensitivity analysis showed that this result was stable after one-by-one study elimination. Conclusion Folate receptor-positive CTCs may have good diagnostic value in lung cancer.

Equivalence ratio (Φ) is one of the most important parameters in combustion diagnostics. In previous studies, flame color characteristics have been widely applied to model the Φ of premixed hydrocarbon flames. The flame spatial characteristics also change with the varying Φ. In this paper, a high-speed color camera was employed to capture the premixed propane flame images under different Φ conditions (Φ = 0.93 to 1.53). Then, the relationship between the spatial characteristics and the Φ variation was investigated. The area and height of propane premixed flames perform a strong sensitive response to the Φ variation. Based on the research above, the Φ measurement models were constructed using color and spatial characteristics. A comparison was made between the color characteristics (Color-Φ) model and the color-spatial characteristics (Multi-dimensional-Φ) model. Both models were applied to a set of color images of a premixed propane flame, and the result indicates that the Multi-dimensional-Φ model performs with higher accuracy.

The ubiquitin ligase Nrdp1/RNF41 promotes the ubiquitin-dependent degradation of multiple important substrates, including BRUCE/BIRC6, a giant ubiquitin-conjugating enzyme inhibiting both apoptosis and autophagy. miR-183-5p is associated with various malignancies potentially by targeting dozens of genes. Here, we show that the lncRNA LINC00960 binds to the Nrdp1-targeting miR-183-5p and promotes apoptosis. Compared to other known miR-183-5p targets, Nrdp1 mRNA is among the few with top scores to complement miR-183-5p. miR-183-5p binds to the 3′UTR of Nrdp1 mRNA and downregulates Nrdp1 at both the mRNA and protein levels. The miR-183-5p mimics inhibit DNA damage-induced apoptosis probably by upregulating BRUCE level, whereas the miR-183-5p inhibitor suppresses the effects of miR-183-5p. LINC00960 is the noncoding RNA with the highest score to complement miR-183-5p. LINC00960 overexpression reduces, but its knockdown increases, the level of miR-183-5p, whereas LINC00960 overexpression increases, but its knockdown decreases, the level of Nrdp1 and apoptosis. Importantly, the expression of LINC00960, which is associated with multiple types of tumors, positively correlates with that of Nrdp1 in several tumors but inversely correlates with that of miR-183-5p in multiple human tumor cell lines, as analysed by quantitative PCR. Thus, miR-183-5p downregulates Nrdp1 expression and inhibits apoptosis, whereas LINC00960 upregulates Nrdp1 and promotes apoptosis by inhibiting miR-183-5p. These results may provide new ideas for the prevention, diagnosis and treatment of apoptosis-related diseases, such as tumors and neurodegenerative diseases.

It is well known that a sufficient and necessary condition for a continuous function gg to be almost periodic on time scale T{\mathbb{T}} is the existence of an almost periodic function ff on R{\mathbb{R}} such that ff is an extension of gg. The purpose of this article is to extend these results to Sp{S}^{p}-almost periodic functions. We prove that the necessity is true, that is, an Sp{S}^{p}-almost periodic function on T{\mathbb{T}} can be extended to an Sp{S}^{p}-almost periodic function on R{\mathbb{R}}. However, a counterexample is given to show that the sufficiency is not true in general. By introducing a concept of minor translation set and characterizing the almost periodicity on T{\mathbb{T}} in terms of this new concept, we obtain a condition to ensure the sufficiency. Moreover, we show the necessity of this condition by a counterexample.

By precisely controlling the distance between two train sets, virtual coupling (VC) enables flexible coupling and decoupling in urban rail transit. However, relying on train-to-train communication for obtaining the train distance can pose a safety risk in case of communication malfunctions. In this paper, a distance-estimation framework based on monocular vision is proposed. First, key structure features of the target train are extracted by an object-detection neural network, whose strategies include an additional detection head in the feature pyramid, labeling of object neighbor areas, and semantic filtering, which are utilized to improve the detection performance for small objects. Then, an optimization process based on multiple key structure features is implemented to estimate the distance between the two train sets in VC. For the validation and evaluation of the proposed framework, experiments were implemented on Beijing Subway Line 11. The results show that for train sets with distances between 20 m and 100 m, the proposed framework can achieve a distance estimation with an absolute error that is lower than 1 m and a relative error that is lower than 1.5%, which can be a reliable backup for communication-based VC operations.

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Designing wideband thermal cloaks remains a challenge, especially at high frequencies. We propose an optimization approach for the design of a thermal cloak for an arbitrary object with large thermal conductivity (copper), in a given frequency band and for a specific diffusion direction. Cloaking performance is assessed as a function of frequency (in the optimal direction) and as a function of angle (at the optimal frequency). Near-perfect cloaking is achieved over a finite frequency band, and, moreover, the thermal cloak performs well in the time domain, including in the transient regime, irrespective of the initial temperature distribution. Interestingly, this specially optimized cloak also works fairly well for other objects with large thermal conductivity but breaks down for those of low thermal conductivity.

Abstract Immune checkpoint inhibitors (ICIs) have shown remarkable success in cancer treatment. However, in cancer patients without sufficient antitumor immunity, numerous data indicate that blocking the negative signals elicited by immune checkpoints is ineffective. Drugs that stimulate immune activation‐related pathways are emerging as another route for improving immunotherapy. In addition, the development of nanotechnology presents a promising platform for tissue and cell type‐specific delivery and improved uptake of immunomodulatory agents, ultimately leading to enhanced cancer immunotherapy and reduced side effects. In this review, we summarize and discuss the latest developments in nanoparticles (NPs) for cancer immuno‐oncology therapy with a focus on lipid‐based NPs (lipid‐NPs), including the characteristics and advantages of various types. Using the agonists targeting stimulation of the interferon genes (STING) transmembrane protein as an exemplar, we review the potential of various lipid‐NPs to augment STING agonist therapy. Furthermore, we present recent findings and underlying mechanisms on how STING pathway activation fosters antitumor immunity and regulates the tumor microenvironment and provide a summary of the distinct STING agonists in preclinical studies and clinical trials. Ultimately, we conduct a critical assessment of the obstacles and future directions in the utilization of lipid‐NPs to enhance cancer immunotherapy.

The clinical manifestations of bone metastases are diversified while many sites remain asymptomatic at early stage. As the early diagnosis method is not perfect and the early symptoms of tumor bone metastasis are not typical, bone metastasis is not easy to be detected. Therefore, the search for bone metastasis-related markers is effective for timely detection of tumor bone metastases and the development of drugs to inhibit bone metastases. As a result, bone metastases can only be diagnosed when symptoms are found, increasing the risk of developing skeletal-related event (SREs), which significantly impairs the patient’s quality of life. Therefore, the early diagnosis of bone metastases is of great importance for the treatment and prognosis of cancer patients. Changes of bone metabolism indexes appear earlier in bone metastases, but the traditional biochemical indexes of bone metabolism lack of specificity and could be interfered by many factors, which limits their application in the study of bone metastases. Some new biomarkers of bone metastases have good diagnostic value, such as proteins, ncRNAs, circulating tumor cells (CTCs). Therefore, this study mainly reviewed the initial diagnostic biomarkers of bone metastases which were expected to provide references for the early detection of bone metastases.

Serpin family A member 1 (SERPINA1) is expressed abundantly in gliomas and can predict unfavorable prognosis of patients with glioma. Studies have shown that nicotinamide adenine dinucleotide phosphate quinone dehydrogenase 1 (NQO1) can promote the proliferation of glioblastoma multiforme cells and enhance the expression of SERPINA1, but its effects on glioma cells remain unknown. In this study, we explored the functions of SERPINA1 in glioma tumorigenesis in vitro and then investigated whether NQO1 affects the protein expression of SERPINA1 and its mRNA level. The results showed that the translation of SERPINA1 was suppressed while its mRNA level had no significant changes under the condition of NQO1 silencing. Luciferase reporter assay and biotin pull-down assay further indicated that NQO1 bond with SERPINA1 3′ untranslated region. miR-1321 was also identified to target SERPINA1, repressing its mRNA and protein levels. SERPINA1 and NQO1 promoted glioma cell proliferation and suppressed cell apoptosis. Moreover, SERPINA1 rescued the effects of sh-NQO1 in glioma cell malignant phenotypes. In conclusion, our findings showed that oncogene NQO1 and antioncogene miR-1321 bind to oncogene SERPINA1 to affect proliferation and apoptosis of glioma cells, which can bring new solution of antitumor treatments for glioma in the future.

ERK1/2 are essential proteins mediating mitogen-activated protein kinase signaling downstream of RAS in pancreatic adenocarcinoma (PDAC). Our previous study reveals that ARF6 plays a positive regulatory role in ERK1/2 pathway in a feedback loop manner. A significant part of the literature on ARF6 has emphasized its oncogenic effect as an essential downstream molecule of ERK1/2, and no research has been done on the regulation mechanisms of the feedback loop between ARF6 and the ERK1/2 signaling pathway. In the present study, we explore the gene network downstream of ARF6 and find that DUSP6 may be the critical signal molecule in the positive feedback loop between ARF6 and ERK1/2. Specifically, to elucidate the negative correlations between ARF6 and DUSP6 in pancreatic cancer, we examine their expressions in pancreatic cancer tissues by immunohistochemical staining. Then the impact of DUSP6 on the proliferation and apoptosis of PDAC cells are investigated by gain-of-function and loss-of-function approaches. Mechanism explorations uncover that ARF6 suppresses the expression of DUSP6, which is responsible for the dephosphorylation of ERK1/2. Altogether, these results indicate that DUSP6 plays a tumor-suppressive role and acts as an intermediate molecule between ARF6 and ERK1/2 in PDAC cells, thereby forming a positive feedback loop.

Abstract Photodynamic therapy (PDT) has shown impressive therapeutic effects on various types of cancers by reactive oxygen species (ROS) generation and induction of immune responses. However, under certain conditions, the immune responses induced by PDT are not always sufficient to eradicate the remaining tumor cells. On the other hand, the photosensitizer indocyanine green (ICG) can mediate PDT under near-infrared (NIR) illumination, thereby enhancing the penetration depth of the excitation light into the tumor. We found that ICG is rapidly taken up in vitro by colorectal MC38 and CT26 tumor cells and it promotes PDT-mediated cell-killing effects. Our results furthermore revealed that ICG induces immunogenic cell death (ICD), as dendritic cells (DCs) were found to engulf ICG-PDT-treated tumor cells and undergo phenotypic maturation. ICG accumulated in tumors 2 h after administration, as measured by fluorescence and photoacoustic imaging. Considering the advantages of ICG as a photosensitizer, we sought to design a therapy that combines PDT and immune checkpoint blockade to maximize tumor control. To this end, a 25% thermosensitive polymer 407 hydrogel was included as a co-delivery platform for this treatment scheme. NIR-PDT under 808 nm irradiation in combination with cytotoxic T-lymphocyte-associated protein 4 (CTLA4)/programmed death-ligand 1 (PD-L1) checkpoint blockade prolonged survival rate of colorectal tumor-bearing mice by inducing a series of immune responses, like the phagocytosis of tumor debris by macrophages and DCs, and induction of acute inflammation, leukocyte infiltration, maturation and activation of DCs. Altogether, our work presents a NIR-triggered PDT strategy in combination with immune checkpoint blockade. Compared to a single treatment, the combination treatment increased efficiency to inhibit solid tumor growth and improved the survival rate of tumor-bearing mice.

Flame combustion diagnostics is a technique that uses different methods to diagnose the flame combustion process and study its physical and chemical basis. As one of the most important parameters of the combustion process, the flame equivalence ratio has a significant influence on the entire flame combustion, especially on the combustion efficiency and the emission of pollutants. Therefore, the measurement of the flame equivalence ratio has a huge impact on efficient combustion and environment protection. In view of this, several effective measuring methods were proposed, which were based on the different characteristics of flames radicals such as spectral properties. With the rapid growth of machine learning, more and more scholars applied it in the combustion diagnostics due to the excellent ability to fit parameters. This paper presents a review of various measuring techniques of hydrocarbon flame equivalent ratio and the applications of machine learning in combustion diagnostics, finally making a brief comparison between different measuring methods.

Surface symmetry breaking and disorder have been recently explored to overcome operation bandwidth, unwanted diffraction, and polarization dependence issues in the conventional metasurface designs thanks to their increasing degrees of design freedom. However, efficient full‐wave simulation and optimization of electrically large electromagnetic structures have been a longstanding problem. Herein, an interactive learning approach is developed to build new meta‐atom datasets which include the effect of mutual coupling. A deep learning‐based model is developed to extract features of incident/reflection waves and their neighboring interaction responses from a limited number of known meta‐atoms. Finally, the deep neural network is incorporated with optimization algorithms to design, as an example, large‐scale metasurfaces for beam manipulation and wideband scattering reduction. The results demonstrate that the proposed architecture can be successfully applied to rapidly design aperture‐efficient metasurfaces or metalenses at large scales of over tens of thousands of meta‐atoms.

Train distance estimation in a turnout area is an important task for the autonomous driving of urban railway transit, since this function can assist trains in sensing the positions of other trains within the turnout area and prevent potential collision accidents. However, because of large incident angles on object surfaces and far distances, Lidar or stereo vision cannot provide satisfactory precision for such scenarios. In this paper, we propose a method for train distance estimation in a turnout area based on monocular vision: firstly, the side windows of trains in turnout areas are detected by instance segmentation based on YOLOv8; secondly, the vertical directions, the upper edges and lower edges of side windows of the train are extracted by feature extraction; finally, the distance to the target train is calculated with an appropriated pinhole camera model. The proposed method is validated by practical data captured from Hong Kong Metro Tsuen Wan Line. A dataset of 2477 images is built to train the instance segmentation neural network, and the network is able to attain an MIoU of 92.43% and a MPA of 97.47% for segmentation. The accuracy of train distance estimation is then evaluated in four typical turnout area scenarios with ground truth data from on-board Lidar. The experiment results indicate that the proposed method achieves a mean RMSE of 0.9523 m for train distance estimation in four typical turnout area scenarios, which is sufficient for determining the occupancy of crossover in turnout areas.

In order to study the evolution characteristics of the fracture plane of the anti-dip rock slope with the steep and gently dipping structural plane under the condition of its own weight. Taking the toppling deformation form of right abutment of Miaowei Hydropower Station as the geological prototype, the centrifugal model test was carried out by presetting non-penetrating cracks of the rock strata in different parts of the slope body to simulate the evolution characteristics of the fracture surface of the anti-dip rock slope under the condition of its own weight. The researches have demonstrated that: (1) The failure of anti-dip rock slopes with steep and gently dipping structural planes are marked by the formation of fracture surfaces, which are divided into three stages: in the initial period (0–40g, g is the acceleration of gravity), it refers to the stage of partial fracturation which takes partial fracturation and stratum forwarding on the trailing edge as the major failure characteristics with less position changes in slope plane. In the middle period (40g–80g), it refers to the formation stage of major fracture plane which can be formed in the deep structural plane of slope through expansion and connection in a top-down approach. Position changes in slope nearly account for 3/4 of total position changes. In the later period (80g–120g), it refers to the formation stage of multi-stage fracture plane whose main formation feature is the stress redistribution of fracture strata within the slope. Position changes in slope basically remain unchanged. (2) The fracture of rock bridge between structural planes is transient, but the formation of fracture plane is a gradual development process which is mainly controlled by steep-inclined structural planes. The strain at the crevice of the main fracture plane is the greatest and the stress mode is the most complex. And the fracture strain at the secondary fracture plane takes the second place. Based on fracture mechanics, the fracture criteria of the rock compression-shear and unbalanced force formula for rock stratum have been simplified. It is revealed that the unbalanced force of the rock stratum at the main fracture surface decreases from 1/3 of the slope height to the bottom and top of the slope. The formation of fracture surface is mainly affected by the ratio of the intensity factor of shear stress to normal stress, the length of rock structure plane and the crack rate.

The integration of electronics and biology has spawned bioelectronics and opened exciting opportunities to fulfill the unmet needs of therapeutic treatments. Recent developments in nanoelectronics and soft and biocompatible materials have shown potential applicability to clinical practices, including physiological sensing, drug delivery, cardiovascular monitoring, and brain stimulation. To date, most bioelectronic devices require wired connections for electrical control, making their implantation complicated and inconvenient for patients. As an alternative, wireless technology is proliferating to create bioelectronics that offer noninvasive control, biotelemetry, and wireless power transfer (WPT). This review paper provides a comprehensive overview of wireless bioelectronics and ongoing developments in their applications for organ-specific treatments, including disorders and dysfunctions. The main emphasis is on delineating the key features of antennas, namely their radiation characteristics, materials, integration with rest of the electronics, and experimental setup. Although the recent progress in wireless mediated bioelectronics is expected to enhance the control of its functionalities, there are still numerous challenges that need to be addressed for commercialization, as well as to address ever-expanding and evolving future therapeutic targets.

The inhibitory effects of ClO2, clove essential oil and cinnamon essential oil on Fusarium graminearum were studied by observing the colony diameter, mycelial growth and spore germination. The results showed that ClO2, clove essential oil and cinnamon essential oil had significant inhibitory effect on Fusarium graminearum, among which, clove essential oil had lower inhibitory effect than cinnamon essential at low density (20~40 µL/L air), and its inhibitory effect was improved dramatically and better than cinnamon essential with the increase of density. Through the regression equation of inhibition rate, the IC50 of ClO2, clove essential oil and cinnamon essential oil were 27 mg/L, 58 µL/L air and 66 µL/L air respectively. By means of ergosterol content determination, scanning electron microscope observation and Fourier transform infrared analysis, we found that ClO2 and essential oil destroyed cell structure in different degrees, ClO2 destroyed cell membrane, leading to the exudation of contents. High density of clove essential oil destroyed cell structure, while cinnamon essential oil resulted in maldevelopment of mycelium.

The application of energy storage technology can solve the problems of randomness and volatility in the development and use of renewable energy, such as wind and solar energy, and effectively improve energy utilization. Rock heat storage is one of the primary forms of sensible heat storage. The heat storage efficiency and heat storage capacity of rock packed bed are important indicators to measure the energy storage effect of a rock energy storage system. This paper takes CO2 as the heat-carrying medium and broken granite grains as the packed bed matrix of the energy storage system. It establishes a porous medium thermal-hydraulic-mechanical coupling model of the broken rock bed. The heat injection and production process of the large-sized rock bed heat storage system is simulated using the COMSOL finite element software, and the heat storage efficiency and heat storage capacity of the broken rock bed is analyzed under different fluid injection pressures and injection temperatures. The results show that: 1) With the increase of CO2 injection pressure, the heat storage and heat production speed of the heat storage system will increase, and the heat storage rate changes from two stages of “low rise - slow decline” to four stages of “rapid increase—stability—rapid decrease—stability”; 2) With the increase of CO2 injection temperature, the maximum heat storage capacity of the rock bed heat storage system will increase. Due to the increase in the temperature gradient between CO2 and the rock bed, the heat storage and the heat production time of the heat storage system will increase, and its speed will decrease.

Abstract Introduction Diosgenin is a natural steroidal compound with reported antidiabetic and many other protective properties. This study aimed to explore the protective effect of diosgenin on high‐glucose (HG)‐induced retinal pigment epithelial cells. Methods HG‐induced ARPE‐19 cells were considered as a cell model of diabetic retinopathy (DR). The viability and apoptosis of ARPE‐19 cells induced by HG treated with either diosgenin or Compound C (CC; dorsomorphin) were detected by Cell Counting Kit‐8 assay and flow cytometric analysis. The expression of apoptosis‐related proteins, inflammation‐related proteins, and AMPK/Nrf2/HO‐1 pathway‐related proteins was detected by western blotting. The levels of inflammatory cytokines and detection of oxidative stress indexes were performed using the appropriate assay kits. The messenger RNA expression of inflammatory cytokines was detected by real‐time quantitative polymerase chain reaction. Results There was no obvious effect of diosgenin on the viability of ARPE‐19 cells and the viability of ARPE‐19 cells was significantly reduced after HG induction. However, diosgenin increased the viability, inhibited the apoptosis, and reduced the inflammatory response and oxidative stress of ARPE‐19 cells induced by HG. In addition, diosgenin could activate the AMPK/Nrf2/HO‐1 pathway. CC, an AMPK inhibitor, could reverse the above changes caused by diosgenin treatment in ARPE‐19 cells induced by HG. Conclusions Diosgenin could protect ARPE‐19 cells from inflammatory damage and oxidative stress induced by HG, by activating the AMPK/Nrf2/HO‐1 pathway.

Because the failure potential of a landslide is difficult to assess, a motorway landslide that has obviously deformed was used as a case study in this research. Several multi-integrated geotechniques, including field investigation, drilling, electrical resistivity tomography (ERT), stability analysis, and numerical simulations, were used to achieve this goal. Field investigation with drilling was used to roughly determine the failure potential mass boundary and the material composition ERT technique was further used to distinguish the structure and composition of underground materials; the results agreed well with the field investigation, as well as the drilling data in the lithology judgement. The above investigations also showed the failure potential mass is in a slow sliding state and the slip surface roughly follows the contact zone between the upper soil and bedrock. Next, stability analysis based on the limit equilibrium method (LEM) was used to judge the current stability status of the slope, and its factor of safety (FOS) was 1.2 under the natural condition, 1.05 under the earthquake condition, and 1.15 under the rainfall condition. Based on the assessed potential slip surface and digital elevation data, a three-dimensional smoothed particle hydrodynamics (SPH) model was used to simulate the failure potential process. The dynamic information of the run-out behavior, including velocity, movement distance, and frictional energy, can be obtained, which is useful for hazard prediction.

The design of a metasurface array consisting of different unit cells with the objective of minimizing its radar cross-section is a popular research topic. Currently, this is achieved by conventional optimisation algorithms such as genetic algorithm (GA) and particle swarm optimisation (PSO). One major concern of such algorithms is the extreme time complexity, which makes them computationally forbidden, particularly at large metasurface array size. Here, we apply a machine learning optimisation technique called active learning to significantly speed up the optimisation process while producing very similar results compared to GA. For a metasurface array of size 10 × 10 at a population size of 106, active learning took 65 min to find the optimal design compared to genetic algorithm, which took 13,260 min to return an almost similar optimal result. The active learning optimisation strategy produced an optimal design for a 60 × 60 metasurface array 24× faster than the approximately similar result generated by GA technique. Thus, this study concludes that active learning drastically reduces computational time for optimisation compared to genetic algorithm, particularly for a larger metasurface array. Active learning using an accurately trained surrogate model also contributes to further lowering of the computational time of the optimisation procedure.

Flowering is the most studied ornamental trait in orchids where long vegetative phase may span up to three years. Cymbidium orchids produce beautiful flowers with astonishing shapes and pleasant scent. However, an unusually long vegetative phase is a major drawback to their ornamental value. We observed that under certain culture conditions, three cymbidium species (Cymbidium ensifolium, C. goeringii and C. sinense) skipped vegetative growth phase and directly flowered within six months, that could be a breakthrough for future orchids with limited vegetative growth. Hormonal and floral regulators could be the key factors arresting vegetative phase. Therefore, transcriptomic analyses were performed for leafless flowers and normal vegetative leaves to ascertain differentially expressed genes (DEGs) related to hormones (auxin, cytokinin, gibberellin, abscisic acid and ethylene), floral integrators and MADS-box genes. A significant difference of cytokinin and floral regulators was observed among three species as compared to other hormones. The MADS-box genes were significantly expressed in the leafless flowers of C. sinense as compared to other species. Among the key floral regulators, CONSTANS and AGAMOUS-like genes showed the most differential expression in the leafless flowers as compared to leaves where the expression was negligible. However, CONSTANS also showed downregulation. Auxin efflux carriers were mainly downregulated in the leafless flowers of C. ensifolium and C. sinense, while they were upregulated in C. goeringii. Moreover, gibberellin and cytokinin genes were also downregulated in C. ensifolium and C. sinense flowers, while they were upregulated in C. goeringii, suggesting that species may vary in their responses. The data mining thus, outsources the valuable information to direct future research on orchids at industrial levels.

Biological control is a safe way of combating plant diseases using the living organisms. For the precise use of microbial biological control agents, the genetic information on the hypersensitive response (HR), and defense-related gene induction pathways of plants are necessary. Orchids are the most prominent stakeholders of floriculture industry, and owing to their long-awaited flowering pattern, disease control is imperative to allow healthy vegetative growth that spans more than 2 years in most of the orchids. We observed leaf-less flowering in three orchid species (Cymbidium ensifolium, C. goeringii and C. sinense). Using these materials as reference, we performed transcriptome profiling for healthy leaves from non-infected plants to identify genes specifically involved in plant-pathogen interaction pathway. For this pathway, a total of 253 differentially expressed genes (DEGs) were identified in C. ensifolium, 189 DEGs were identified in C. goeringii and 119 DEGs were found in C. sinense. These DEGs were mainly related to bacterial secretion systems, FLS2, CNGCs and EFR, regulating HR, stomatal closure and defense-related gene induction. FLS2 (LRR receptor-like serine/threonine kinase) contained the highest number of DEGs among three orchid species, followed by calmodulin. Highly upregulated gene sets were found in C. sinense as compared to other species. The great deal of DEGs, mainly the FLS2 and EFR families, related to defense and immunity responses can effectively direct the future of biological control of diseases for orchids.

Though existing metamaterial antireflection coatings have been optimized in terms of thickness and functionality, these coatings do not provide phase control in the deep subwavelength scale. Here, the authors report multi-layered metasurfaces that provide both antireflection and phase control.

Cao, Li, et al. sequence 13 perennial woody plant species of Lycium, and specifically provide a draft assembly of L. ruthenicum and a chromosome-level assembly of L. barbarum, the wolfberry or Goji berry. From a phylogenetic tree the authors identify an ancient hexaploidization event, and report the evolution of gene families including fruit ripening, fruit coloration, polysaccharide synthesis and self-incompatibility within Solanaceae and the general biogeography of L. barbarum.

Abstract The success of machine learning (ML) in materials property prediction depends heavily on how the materials are represented for learning. Two dominant families of material descriptors exist, one that encodes crystal structure in the representation and the other that only uses stoichiometric information with the hope of discovering new materials. Graph neural networks (GNNs) in particular have excelled in predicting material properties within chemical accuracy. However, current GNNs are limited to only one of the above two avenues owing to the little overlap between respective material representations. Here, a new concept of formula graph which unifies stoichiometry‐only and structure‐based material descriptors is introduced. A self‐attention integrated GNN that assimilates a formula graph is further developed and it is found that the proposed architecture produces material embeddings transferable between the two domains. The proposed model can outperform some previously reported structure‐agnostic models and their structure‐based counterparts while exhibiting better sample efficiency and faster convergence. Finally, the model is applied in a challenging exemplar to predict the complex dielectric function of materials and nominate new substances that potentially exhibit epsilon‐near‐zero phenomena.

In recent years, much attention has been paid to the application of high-speed centrifugal pumps; still, the development of this pump faces several challenges. In order to obtain a more comprehensive understanding of the high-speed centrifugal pump, this paper reviewed the engineering application, technical challenges, and feasible solutions of this pump from the aspects of hydraulic design, including cavitation, hydraulic excitation, efficiency issue at an ultra-low specific speed, and the solution to these problems. The current state of the structural design of the high-speed centrifugal pump was briefly described in addition. For the faults in the existing high-speed centrifugal pump, some research studies on pump monitoring were presented. Finally, the status and shortcomings of the design of the pump were simply analyzed and summarized. It is hoped that this study can provide some references for the design and practical usage of high-speed centrifugal pumps.

During orchid seed culture, seeds germinate as protocorms, and protocorms normally develop into plant with leaves and roots. Orchids require many years of vegetative development for flowering. However, under a certain combination of growth cultures, we observed that protocorms can directly flower without leaves and roots. Therefore, we performed comparative transcriptome analysis to identify the different transcriptional regulators of two types of protocorms of Cymbidium ensifolium, Cymbidium sinense, and Cymbidium goeringii. Zinc finger, MYB, AP2, and bHLH were the most abundant transcription factor (TF) families in the transcriptome. Weighted gene coexpression network analysis (WGCNA) was performed to identify hub genes related to leaf and flower development. The key hubs included SPL6, SVP, SEP2, KNOX1, AP2, OFP1, COL12, MYB13, MYB36, MYB59, bHLH086, and ARF7. The hub genes were further validated through statistical tools to propose the roles of key TFs. Therefore, this study initiates to answer that why there is no leaf initiation and root development and how can protocorm bypass the vegetative phase to flower? The outcomes can direct future research on short-span flowering in orchids through protocorms.