Search

Abstract Clade A type 2C protein phosphatases (PP2Cs) are crucial components of the abscisic acid (ABA) signaling pathway. Research on clade A PP2Cs has focused more on their roles related to ABA signaling and stress responses than on the molecular mechanisms mediating their effects on plant growth and grain yield. Rice (Oryza sativa L.) is an important food crop worldwide. We previously determined that OsPP2C49, which encodes a rice clade A PP2C family member, negatively controls rice responses to drought, salt, and high-temperature stresses. In this study, we investigated the regulatory effects of OsPP2C49 on ABA responses and rice grain yield. By analyzing potential interactions with core ABA components, including pyrabactin resistance 1 (PYR1)/PYR1-like (PYL)/regulatory component of the ABA receptor (RCAR) and stress-activated protein kinases (SAPKs), we confirmed that OsPP2C49 is involved in the ABA signaling pathway. OsPP2C49 overexpression led to decreased ABA sensitivity and increased rice grain yield; the opposite phenotypes were observed in the ospp2c49 knockout mutants. Therefore, OsPP2C49 negatively regulates ABA responses, but positively modulates rice grain yield. Furthermore, we found that OsPP2C49 can interact with and dephosphorylate five OsSAPKs in vitro. Unlike OsPP2C49, these OsSAPKs positively modulate ABA responsiveness, but negatively affect rice yield. These findings indicate that OsPP2C49 may partially regulate ABA responses and rice grain production by dephosphorylating OsSAPKs. This study preliminarily explored the molecular basis of the regulatory effects of OsPP2C49 on rice plant growth and grain yield.

In this work, we report a counter-intuitive activation of abnormal grain growth (AGG) in randomly-oriented fine grains (FGs) in an L-PBF Al–Mg–Sc–Zr alloy, which is unlikely from perspectives of curvature-driven grain growth, crystallographic texture or strain-induced boundary migration. The observed spontaneous AGG is understood in light of the growth instability of an arbitrary grain in an evolving particle-pinned polycrystalline aggregation. A generalized criterion for AGG is hence proposed, which efficaciously explains the observed susceptibility of FGs to AGG, the presence of multiple AGG activation sites, and the asynchrony of AGG activation.

This study systematically investigates the flow behavior of 7050 aluminum (Al) alloy produced via spray forming and subjected to a proposed pretreatment through thermal compression tests. The experimental findings reveal that the peak stress increased with decreasing deformation temperature or increasing strain rates. The parameters in the Arrhenius constitutive model were determined and verified by experimental results for spray formed (SFed) 7050 Al alloy. Hot deformation activation energy of the SFed 7050 Al alloy (147.38 kJ/mol) is notably lower than that of cast Al–Zn–Mg–Cu–Zr alloys, which is attributed to factors such as fine grains, low segregation, pores, and dispersed Al3Zr induced by pretreatment. Furthermore, processing maps have been constructed at various strains, revealing optimal stable deformation conditions at 300–450 °C/0.001–0.15s−1 and 425–450 °C/0.2–1s−1. Microstructural analysis of deformed samples highlights the critical role of dynamic recrystallization in influencing the stable and unstable areas of the alloy, which may be activated by high temperature and slow strain rate. The hot deformation mechanism of the SFed Al alloy is governed by interactions among η-Mg(Zn,Al,Cu)2 precipitates, dispersed Al3Zr particles, dislocation structures, and (sub-)grain boundaries.

This research aimed to enhance the strength and ductility of spray formed (SFed) 7050 aluminum (Al) alloy through hot extrusion and subsequent heat treatment. Microstructure and mechanical properties evolution during these processes were investigated. It was found that the low densification of the SFed 7050 Al alloy due to various defects such as pores, with an average size of 7.6 μm and an area fraction of 3.7 % could be notably enhanced by hot extrusion, even achieving a level close to theoretical density. This process led to a transformation of grains from equiaxed to elongated shapes along extrusion direction and significant grain refinement, exhibiting a strong fiber texture. While the employed extrusion ratio exceeds 16 with proper heat treatment, the SFed 7050 Al alloys achieves superior strength-ductility combination compared with reported Al alloys. The achieved high performance should be attributed to the grain refinement, strong texture and high densification that suppress defect-induced plastic instability. Furthermore, the combination of hot extrusion and heat treatment, provides an effective way to enhance strength and ductility for SFed 7050 Al alloy.

Abstract Aqueous Zn/V2O5 batteries are featured for high safety, low cost, and environmental compatibility. However, complex electrode components in real batteries impede the fundamental understanding of phase transition processes and intercalation chemistry. Here, model batteries based on V2O5 film electrodes which show similar electrochemical behaviors as the real ones are built. Advanced surface science characterizations of the film electrodes allow to identify intercalation trajectories of Zn2+, H2O, and H+ during V2O5 phase transition processes. Protons serve as the vanguard of intercalated species, facilitating the subsequent intercalation of Zn2+ and H2O. The increase of capacity in the activation process is mainly due to the transition from V2O5 to more active V2O5·nH2O structure caused by the partial irreversible deintercalation of H2O rather than the increase of active sites induced by the grain refinement of electrode materials. Eventually, accumulation of Zn species within the oxide electrode results in the formation of inactive (Zn3(OH)2V2O7·2H2O) structure. The established intercalation chemistry helps to design high‐performance electrode materials.

ABSTRACT Background The association among coronary heart disease, ischemic stroke, and hydrocephalus remains ambiguous. Objectives There is a need for a Mendelian randomization study to evaluate the underlying causality between coronary heart disease, ischemic stroke, and hydrocephalus. Methods The data source utilized genome‐wide association studies, employing a threshold of p

Abstract Dysregulation of the transforming growth factor‐β (TGF‐β) signaling pathway regulates cancer stem cells (CSCs) and drug sensitivity, whereas it remains largely unknown how feedback regulatory mechanisms are hijacked to fuel drug‐resistant CSCs. Through a genome‐wide CRISPR activation screen utilizing stem‐like drug‐resistant properties as a readout, the TGF‐β receptor‐associated binding protein 1 (TGFBRAP1) is identified as a TGF‐β‐inducible positive feedback regulator that governs sensitivity to tyrosine kinase inhibitors (TKIs) and promotes liver cancer stemness. By interacting with and stabilizing the TGF‐β receptor type 1 (TGFBR1), TGFBRAP1 plays an important role in potentiating TGF‐β signaling. Mechanistically, TGFBRAP1 competes with E3 ubiquitin ligases Smurf1/2 for binding to TGFΒR1, leading to impaired receptor poly‐ubiquitination and proteasomal degradation. Moreover, hyperactive TGF‐β signaling in turn up‐regulates TGFBRAP1 expression in drug‐resistant CSC‐like cells, thereby constituting a previously uncharacterized feedback mechanism to amplify TGF‐β signaling. As such, TGFBRAP1 expression is correlated with TGFΒR1 levels and TGF‐β signaling activity in hepatocellular carcinoma (HCC) tissues, as well as overall survival and disease recurrence in multiple HCC cohorts. Therapeutically, blocking TGFBRAP1‐mediated stabilization of TGFBR1 by selective inhibitors alleviates Regorafenib resistance via reducing CSCs. Collectively, targeting feedback machinery of TGF‐β signaling pathway may be an actionable approach to mitigate drug resistance and liver cancer stemness.

Deep learning has been extensively employed for predicting the remaining useful life (RUL) of equipment owing to the powerful feature extraction ability of deep learning. However, the deep learning prediction results are often affected by random noise, modeling parameters, and other factors, considerably reducing the credibility of point predictions. This reduction may lead to inappropriate decisions and sometimes even cause equipment operation collapse. Therefore, the key to ensuring the smooth progress of the entire industrial production process is accurately quantifying the uncertainties transmitted in the output of the RUL prediction model and forming an effective and reasonable maintenance decision plan. The prediction interval is a statistical measure used to quantify uncertainty in predictions. The prediction interval comprises the upper and lower prediction bounds between which an unknown value is expected with a specific probability. The option of prediction intervals enables decision-makers and operational planners to effectively quantify the uncertainty level associated with point predictions and consider multiple solutions for optimal and worst-case conditions. A wide prediction interval indicates a high degree of uncertainty in the underlying system operation. This information signals decision-makers to avoid choosing risky actions under uncertain conditions. By contrast, a narrow prediction interval implies that decisions can be made with more confidence and unexpected situations will be less in the future. The aim of this paper is to analyze and elaborate the basic ideas and development trends of current deep learning-based RUL interval prediction models to provide a good reference for exploring implementable deep learning-based RUL interval prediction model that is highly reliable, cost-efficient, and easy. Thus, while facing the practical demand of uncertainty quantification in the modeling of equipment RUL based on deep learning, this paper first analyzes the sources of uncertainty in RUL prediction, such as data quality, model error, and changes in model parameters and the external environment. Subsequently, five popular deep learning-based RUL interval prediction models are presented: bootstrap deep learning, local uncertainty, stochastic process deep learning, Bayesian deep learning, and deep learning quantile regression. Through the model establishment process and current development status analysis, the advantages and disadvantages of the five RUL interval prediction models are summarized. Finally, the challenges encountered during the current research on the RUL interval prediction of equipment based on deep learning and potential future research directions are explored.

Hydrogen removal from particle-reinforced Al composite is critical for preventing porosities near particle clusters and improving comprehensive material properties. This study investigated the effects of different argon flow schemes and power ultrasound on bubble dispersion in water. Based on similarity theory, the optimal argon flow scheme for ultrasonic-assisted argon (UAA) treatment was identified and applied to TiB2/2024 Al composite to explore the degassing mechanism. Three argon flow schemes for UAA treatment: EV-EC (External ventilation, equal channel), IV-EC (Internal ventilation, equal channel), and IV-RC (Internal ventilation, reduced channel) were evaluated through numerical simulation and water simulation experiments. The results demonstrated that IV-RC scheme exhibits superior bubble dispersion characteristics and a broader bubbling range. Experimental results in Al composite confirmed that UAA treatment with IV-RC scheme achieved the highest degassing efficiency, with a relative density improvement of up to 98.01 % and the lowest hydrogen content (0.0235 ppm). Synchrotron radiation X-ray computed tomography results indicated that UAA treatment effectively reduces the pore size and volume, transforming interconnected, complex pores into dispersed, nearly spherical ones. Ultrasonic cavitation aids this process by breaking small argon bubbles into numerous tiny bubbles that penetrate deeply into the melt, reducing the wettability angle between particles and the matrix and thereby improving hydrogen removal efficiency.

Abstract Objective The aim of the study is to identify clinical and dosimetric factors that could predict the risk of radiation-induced hypothyroidism(RIHT) in head and neck cancer(HNC) patients following intensity-modulated radiotherapy(IMRT). Methods A total of 103 HNC patients were included in our study. General clinical characteristic and dosimetric data of all recruited patients were analyzed, respectively. The univariate and multivariate logistic regression anlalysis were successively conducted to identify optimal predictors, which aim to construct the nomogram. And the joint prediction was performed. Results The incidence of patients with HNC was 36.9% (38/103). Among the clinical factors, gender, N stage, chemotherapy, frequency of chemotherapy and surgery involving the thyroid were related to RIHT. Logistic regression analysis showed that thyroid volume, Dmean, VS45, VS50, VS60 and V30,60 were independent predictors of RIHT, which were also incorporated in the nomogram. An AUC of 0.937 (95%CI, 0.888–0.958) also was showed outstanding resolving ability of the nomogram. When the volume of the thyroid was greater than 10.6 cm3, the incidence of RIHT was 14.8%, and when the volume of the thyroid was equal to or smaller than 10.6 cm3, the incidence was 72.5%. The incidence rates of RIHT in the group with VS60≦8.4cm3 and VS60 > 8.4cm3 were 61.4% and 19.3%, respectively. Conclusions Thyroid volume and thyroid VS60 are independent predictors of RIHT in patients with HNC. Moreover, more attention should be paid to patients with thyroid volume ≤ 10.6cm3. Thyroid VS60 > 8.4cm3 may be a useful threshold for predicting the development of RIHT. The nomogram conducted by the research may become a potential and valuable tool that could individually predict the risk of RIHT for HNC patients.

The cast Al–3Li–2Cu-0.15Zr alloy is a promising material due to its high strength-to-weight ratio and stiffness. In this work, the Sn addition and heat treatment were employed to regulate its microstructure and mechanical properties. The results indicate that Sn exists in the matrix as Sn solute atoms and Sn-rich particles including Li5Sn2, Li13Sn5, Li7Sn2, and Li22Sn5. The number of these particles increases as the Sn content rises. The addition of Sn significantly enhances the grain refinement, reducing the average grain size to 50.2 μm when 0.3 wt% Sn is incorporated. During the aging process, the δ′ and δ'/β′ precipitates gradually grow and coarsen, while the T1 and θ′ precipitates nucleate and grow. Some δ′ precipitates attach to the board of θ′ to form sandwich-like phases, such as δ'/θ'/δ'. The addition of Sn promotes the nucleation of θ′ and T1 precipitates. This is achieved by leveraging the Sn-rich particles as nucleation sites and utilizing Sn solute atoms to decrease the interface energy between these precipitates and α-Al. Moreover, the addition of Sn with a high vacancy binding energy and the reduction of aging temperature can effectively decrease the diffusion rate of Li atoms and vacancies, thereby inhibiting the broadening of the δ′-PFZ. After a suitable heat treatment, the Sn-modified Al–Li alloy exhibits a microstructure characterized by fine and equiaxed grain, fine and uniform δ′ precipitates, and a narrow δ′-PFZ, contributing to excellent mechanical properties of the alloy. Significantly, the underlying mechanisms behind the aforementioned observations were discussed analytically.

Abstract Reprogrammed cellular metabolism is essential for maintaining cancer stem cells (CSCs) state. Here, we report that mitochondrial D-lactate catabolism is a necessary initiating oncogenic event during tumorigenesis of esophageal squamous cell carcinoma (ESCC). We discover that cyclin-dependent kinase 7 (CDK7) phosphorylates nuclear Yes-associated protein 1 (YAP) at S127 and S397 sites and enhances its transcription function, which promotes D-lactate dehydrogenase (LDHD) protein expression. Moreover, LDHD is enriched significantly in ESCC-CSCs rather than differentiated tumor cells and high LDHD status is connected with poor prognosis in ESCC patients. Mechanistically, the CDK7-YAP-LDHD axis helps ESCC-CSCs escape from ferroptosis induced by D-lactate and generates pyruvate to satisfy energetic demands for their elevated self-renewal potential. Hence, we conclude that esophageal CSCs adopt a D-lactate elimination and pyruvate accumulation mode dependent on CDK7-YAP-LDHD axis, which drives stemness-associated hallmarks of ESCC-CSCs. Reasonably, targeting metabolic checkpoints may serve as an effective strategy for ESCC therapy.

As an important part of the additive manufacturing technology, wire arc additive manufacture (WAAM) is outstanding with high deposition efficiency, large size of deposited parts, short periodic time, and low costs. WAAM also shows potential in in-situ composite manufacturing and gradient material preparation. Given the potential in wire arc manufacturing of double-alloy gradient structured materials, the walls were deposited using alternating feeds (depositing a layer of A wire and then depositing a layer of B wire) of high-strength-low-plasticity ZL205 and low-strength-high-plasticity 4043 welding wire. In this process, the liquid phases of the two types of wire were efficiently mixed, which showed a regular distribution of molten pool track and avoided evident defects. Generally, through such gradient structure design, high-strength low-toughness materials and high-toughness low-strength materials can be effectively combined, which achieves the regulation of mechanical properties. Specifically, the overall structural and mechanical properties can be improved by adjusting the proportion of a certain component. As an extension from the wire arc printing technology, WAAM shows extremely high application potential and industrial values. Moreover, the addition of a dissimilar alloy can decrease the formation of columnar grains during additive manufacturing. Such compositional gradient can destroy the columnar extensive growth during the deposition in WAAM.

Normal pressure hydrocephalus (NPH) is a prevalent type of hydrocephalus, including secondary normal pressure hydrocephalus (SNPH) and idiopathic normal pressure hydrocephalus (INPH). However, its clinical diagnosis and pathological mechanism are still unclear. Leucine-rich α-2 glycoprotein (LRG) is involved in various human diseases, including cancer, diabetes, cardiovascular disease, and nervous system diseases. Now the physiological mechanism of LRG is still being explored. According to the current research results on LRG, we found that the agency of LRG has much to do with the known pathological process of NPH. This review focuses on analyzing the LRG signaling pathways and the pathological mechanism of NPH. According to the collected literature evidence, we speculated that LRG probably be involved in the pathological process of NPH. Finally, based on the mechanism of LRG and NPH, we also summarized the evidence of molecular targeted therapies for future research and clinical application.

With the development of new urban power systems, the centralized-distributed hierarchical partition management architecture has gradually become a consensus. Existing hierarchical partition methods are mostly static. And if the partition results are determined, it will remain unchanged for a relatively long time. However, the new type power system experiences more frequent and larger fluctuations in power generation and load, requiring dynamic responses to the system’s real-time operation. In this case, traditional partition methods are no longer applicable, and new hierarchical partition methods for system operation need to be adopted. Therefore, this paper proposes a power balance mechanism of urban power system based on dynamic hierarchical partition method, including dynamic hierarchical partition method and corresponding decoupling power balance models. The former can continuously change the results of hierarchical partition according to the real-time state of the power system, so as to reduce the inter-regional liaison cost and improve the economy. The latter improves the independence of the region and the security of the power system through decoupling power balance. Eventually, the proposed method is validated with an modified Hawaii 37-node system.

Abstract Effective treatment for metastasis, a leading cause of cancer‐associated death, is still lacking. To seed on a distal organ, disseminated cancer cells (DCCs) must adapt to the local tissue microenvironment. However, it remains elusive how DCCs respond the pro‐metastatic niche signals. Here, systemic motif‐enrichment identified myocyte enhancer factor 2D (MEF2D) as a critical sensor of niche signals to regulate DCCs adhesion and colonization, leading to intrahepatic metastasis and recurrence of liver cancer. In this context, MEF2D transactivates Itgb1 (coding β1‐integrin) and Itgb4 (coding β4‐integrin) to execute temporally unique functions, where ITGB1 recognizes extracellular matrix for early seeding, and ITGB4 acts as a novel sensor of neutrophil extracellular traps‐DNA (NETs‐DNA) for subsequent chemotaxis and colonization. In turn, an integrin‐FAK circuit promotes a phosphorylation‐dependent USP14‐orchastrated deubiquitination switch to stabilize MEF2D via circumventing degradation by the E3‐ubiquitin‐ligase MDM2. Clinically, the USP14(pS432)‐MEF2D‐ITGB1/4 feedback loop is often hyper‐active and indicative of inferior outcomes in human malignancies, while its blockade abrogated intrahepatic metastasis of DCCs. Together, DCCs exploit a deubiquitination‐dependent switch on MEF2D to integrate niche signals in the liver mesenchyme, thereby amplifying the pro‐metastatic integrin‐FAK signaling. Disruption of this feedback loop is clinically applicable with fast‐track potential to block microenvironmental cues driving metastasis.

Membranes with fast and selective ion transport are essential for electrochemical processes. Here the authors provide mechanistic insights into the structures of metal-ion coordinated polybenzimidazole membranes and the preferential K+ transport, and their application in an alkaline zinc-iron flow battery.

Flow batteries (FBs) have emerged as a promising technology for practical energy storage, mainly due to their outstanding characteristics of ultralong lifespan, safety, and scalability. Despite these attractive features, current FB technologies remain relatively expensive and have low energy density, limiting their widespread implementation. The multi-electron transfer FB systems are one of the most promising strategies to reduce the cost and enhance energy density. In this review, we give a comprehensive overview of the progress on multi-electron reaction materials, including the inorganic halogen-based, transition metal-based, and heteropoly acid-based materials and organic molecules (viologen derivatives, quinone derivatives, and heterocyclic aromatic compound derivatives). Finally, the challenge and perspective on the exploration of multi-electron materials for high-performance FBs are also provided.

Pituitary adenoma (PA) is the third most common central nervous system tumor originating from the anterior pituitary, but its pathogenesis remains unclear. The Wnt signaling pathway is a conserved pathway involved in cell proliferation, Self-renewal of stem cells, and cell differentiation. It is related to the occurrence of various tumors, including PA. This article reviews the latest developments in Wnt pathway inhibitors and pathway-targeted drugs. It discusses the possibility of combining Wnt pathway inhibitors with immunotherapy to provide a theoretical basis for the combined treatment of PA.

Background: Esophageal cancers are primarily categorized as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). While various (epi) genomic alterations associated with tumor development in ESCC and EAC have been documented, a comprehensive comparison of the transcriptomes in these two cancer subtypes remains lacking. Methods: We collected 551 gene expression profiles from publicly available sources, including normal, ESCC, and EAC tissues or cell lines. Subsequently, we conducted a systematic analysis to compare the transcriptomes of these samples at various levels, including gene expression, promoter activity, alternative splicing (AS), alternative polyadenylation (APA), and gene fusion. Results: Seven distinct cluster gene expression patterns were identified among the differentially expressed genes in normal, ESCC, and EAC tissues. These patterns were enriched in the PI3K-Akt signaling pathway and the activation of extracellular matrix organization and exhibited repression of epidermal development. Notably, we observed additional genes or unique expression levels enriched in these shared pathways and biological processes related to tumor development and immune activation. In addition to the differentially expressed genes, there was an enrichment of lncRNA co-expression networks and downregulation of promoter activity associated with the repression of epidermal development in both ESCC and EAC. This indicates a common feature between these two cancer subtypes. Furthermore, differential AS and APA patterns in ESCC and EAC appear to partially affect the expression of host genes associated with bacterial or viral infections in these subtypes. No gene fusions were observed between ESCC and EAC, thus highlighting the distinct molecular mechanisms underlying these two cancer subtypes. Conclusions: We conducted a comprehensive comparison of ESCC and EAC transcriptomes and uncovered shared and distinct transcriptomic signatures at multiple levels. These findings suggest that ESCC and EAC may exhibit common and unique mechanisms involved in tumorigenesis.

The effects of combined Ti and Zr addition on microstructures and mechanical properties are systematically investigated in Al–Zn–Mg–Cu alloy by microstructure characterizations and a physical-based model. The results show that combined addition of Ti and Zr can promote the precipitation of nano L12 Al3(Ti,Zr) dispersoids, while primary D022 Al3Ti and Al3(Ti,Zr) phases are formed during solidification when Ti addition is over 0.2 wt%. As compared to the 0Ti alloy, the ductility and toughness is enhanced markedly by 0.1–0.2 wt%Ti addition since the volume fraction of nano L12 Al3(Ti,Zr) dispersoids is increased. Both the strength and ductility are significantly decreased when Ti addition is more than 0.35 wt%. The strain hardening behavior and fractured morphology analyses suggest that the deterioration of mechanical properties is mainly due to the localized recrystallization and cracks caused by coarse primary phases, which cause the higher dislocation dynamic recovery rate. Combined addition of minor Ti and Zr elements may provide a simple approach to improve toughness and simultaneously reduce cost in developing high-strength Al alloys.

This study focuses on the inversion of sub-bottom profile (SBP) data in the northern South China Sea using an empirical relationship derived from sediment acoustic data. The sub-bottom profile is primarily utilized for various marine applications, such as geological mapping and resource exploration. In this research, we present a study conducted in the northern slope canyon of the South China Sea. Firstly, we obtained the seabed reflection coefficient from sub-bottom profiles obtained by the autonomous underwater vehicle (AUV) detection system. Secondly, we utilized the acoustic empirical relationship in the northern South China Sea to establish relationship equations between the seabed reflection coefficient and the porosity, density, and average particle size of the sediment at a main frequency of 4 kHz (the AUV shallow profile main frequency). Then, using these equations, we were able to invert the physical parameters such as porosity, density, and average particle size of the seabed surface sediments. Finally, the inverted results are compared and analyzed by using the sediment samples test data. The overall deviation rate of the inverted physical parameters is within the range of ±10% when compared. The inverted results closely match the measured values, accurately reflecting the dynamic changes in the physical properties of seabed surface sediments. Notably, the average grain size is a direct indicator of the sediment particles size with smaller particles found in deeper water. The variation characteristics of sediment physical parameters align well with the variation of sediment types in the canyon, which is consistent with changes in the water depth, topography, and hydrodynamic conditions of the area. This further demonstrates the reliability of the inversion results.

Abstract Background Cell division cycle 6 (CDC6) has been proven to be associated with the initiation and progression of human multiple tumors. However, it’s role in glioma, which is ranked as one of the common primary malignant tumor in the central nervous system and is associated with high morbidity and mortality, is unclear. Methods In this study, we explored CDC6 gene expression level in pan-cancer. Furthermore, we focused on the relationships between CDC6 expression, its prognostic value, potential biological functions, and immune infiltrates in glioma patients. We also performed vitro experiments to assess the effect of CDC6 expression on proliferative, apoptotic, migrant and invasive abilities of glioma cells. Results As a result, CDC6 expression was upregulated in multiple types of cancer, including glioma. Moreover, high expression of CDC6 was significantly associated with age, IDH status, 1p/19q codeletion status, WHO grade and histological type in glioma (all p

Interpretability of DNN-based object detection has been a rising concern for the research community. The first step towards this goal is a saliency map that visualizes the importance (saliency) of pixels in an image for the object detected by a specific model. Black-box based methods generate a saliency map without the need to look into the internals of a model, thus applicable to all models without the need of adaptation. In addition, they provide more reliable evaluation on the saliency of pixels than white-box methods by means of the absence of these pixels from the image. However, with current black-box methods, the absence of pixels is produced by random image masks. Despite the need of a great number of random masks for sufficient coverage, the quality of the pixel saliency is not assured to be satisfactory. In this work, we propose a more effective black-box framework with hierarchical masking. In this framework, called GSM-HM, pixel saliency is evaluated at multiple levels, with each lower level performing a refinement on the saliency information of the upper level. This hierarchical framework significantly reduces the masking efforts on less valuable pixels, thus it can produce saliency maps with higher qualities. In our experiments, the quality of a generated saliency map is evaluated with four different metrics: deletion, insertion, convergence and RAM (the ratio of average to maximum). Compared with D-RISE, a recent black-block method, GSM-HM generates more accurate saliency maps evaluated by these metrics.

Summary: Long bones are generated by mesoderm-derived skeletal progenitor/stem cells (SSCs) through endochondral ossification, a process of sequential chondrogenic and osteogenic differentiation tightly controlled by the synergy between intrinsic and microenvironment cues. Here, we report that loss of TRIM28, a transcriptional corepressor, in mesoderm-derived cells expands the SSC pool, weakens SSC osteochondrogenic potential, and endows SSCs with properties of ectoderm-derived neural crest cells (NCCs), leading to severe defects of skeletogenesis. TRIM28 preferentially enhances H3K9 trimethylation and DNA methylation on chromatin regions more accessible in NCCs; loss of this silencing upregulates neural gene expression and enhances neurogenic potential. Moreover, TRIM28 loss causes hyperexpression of GREM1, which is an extracellular signaling factor promoting SSC self-renewal and SSC neurogenic potential by activating AKT/mTORC1 signaling. Our results suggest that TRIM28-mediated chromatin silencing establishes a barrier for maintaining the SSC lineage trajectory and preventing a transition to ectodermal fate by regulating both intrinsic and microenvironment cues.

A coaxial infrared-blue hybrid laser system was adopted in the cladding of high reflectivity pure copper on an AlSi7Mg alloy substrate, and the cladding stability, molten pool size and microstructure of the cladded samples by three types of laser sources (infrared, blue and their hybrid sources) were compared. The infrared-blue hybrid laser was validated to compensate for the forming instability of a high-power infrared laser and a low-power density blue laser. In addition, the heat accumulation in the cladding process with the hybrid laser was more obvious and the cooling rate was slower (1.36 × 104 K/s), which led to a coarser microstructure (1.56∼2.42 μm). Therefore, the hybrid laser can bring about stability and a larger molten pool size in cladding pure copper on the aluminum substrate, which is closely related to the great increase in the total laser absorption rate of the high reflectivity alloy and the reduction in the fluctuation of the absorption rate.

With the rising demand for nuclear energy, the storage/transportation of radioactive nuclear by-products are critical safety issues for humans and the environment. These by-products are closely related to various nuclear radiations. In particular, neutron radiation requires specific protection by neutron shielding materials due to its high penetrating ability to cause irradiation damage. Herein, a basic overview of neutron shielding is presented. Since gadolinium (Gd) has the largest thermal neutron capture cross-section among various neutron absorbing elements, it is an ideal neutron absorber for shielding applications. In the last two decades, there have been many newly developed Gd-containing (i.e., inorganic nonmetallic-based, polymer-based, and metallic-based) shielding materials developed to attenuate and absorb the incident neutrons. On this basis, we present a comprehensive review of the design, processing methods, microstructure characteristics, mechanical properties, and neutron shielding performance of these materials in each category. Furthermore, current challenges for the development and application of shielding materials are discussed. Finally, the potential research directions are highlighted in this rapidly developing field.

Perspective: Rechargeable aqueous zinc-ion batteries (AZIBs) have gained increasing attention owing to their low cost and high safety. Although hydrated vanadium oxides exhibit rich redox chemistry and open layer architecture, the insertion of multivalent Zn2+ during cycling inevitably leads to host collapse and severe vanadium dissolution. Accordingly, various ions and conducting polymers have been introduced into the interlayer to produce vanadium bronzes with a robust crystal structure. However, these pre-intercalated vanadium bronzes demonstrate limited improvement and still face the challenge of metal ion displacement and confusing reaction mechanisms. Herein, we report a novel molecular bronze with intercalated 3-phenylpropylamine for use as an AZIB cathode, which produces an ultrahigh interlayer of 18.0 Å. The cathode delivered an improved capacity of 420 mAh g−1 at 0.1 A g−1, an impressive rate capability of 158 mAh g−1 at 35 A g−1, and an outstanding lifespan with a capacity retention of 94% over 1200 cycles at 2A g−1. Furthermore, the reaction mechanism of H+/Zn2+ co-insertion was investigated in detail. This work proves that this strategy is universal for vanadium oxide bronzes and opens a new avenue for the fabrication of novel molecular bronzes as advanced AZIB cathodes.