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Abstract Background Neuroblastoma (NB) is the most common extracranial solid tumor in childhood and is closely related to the early development and differentiation of neuroendocrine (NE) cells. The disease is mainly represented by high-risk NB, which has the characteristics of high mortality and difficult treatment. The survival rate of high-risk NB patients is not ideal. In this article, we not only conducted a comprehensive study of NB through single-cell RNA sequencing (scRNA-seq) but also further analyzed cuproptosis, a new cell death pathway, in order to find clinical treatment targets from a new perspective. Materials and Methods The Seurat software was employed to process the scRNA-seq data. This was followed by the utilization of GO enrichment analysis and GSEA to unveil pertinent enriched pathways. The inferCNV software package was harnessed to investigate chromosomal copy number variations. pseudotime analyses involved the use of Monocle 2, CytoTRACE, and Slingshot software. CellChat was employed to analyze the intercellular communication network for NB. Furthermore, PySCENIC was deployed to review the profile of transcription factors. Result Using scRNA-seq, we studied cells from patients with NB. NE cells exhibited superior specificity in contrast to other cell types. Among NE cells, C1 PCLAF + NE cells showed a close correlation with the genesis and advancement of NB. The key marker genes, cognate receptor pairing, developmental trajectories, metabolic pathways, transcription factors, and enrichment pathways in C1 PCLAF + NE cells, as well as the expression of cuproptosis in C1 PCLAF + NE cells, provided new ideas for exploring new therapeutic targets for NB. Conclusion The results revealed the specificity of malignant NE cells in NB, especially the key subset of C1 PCLAF + NE cells, which enhanced our understanding of the key role of the tumor microenvironment in the complexity of cancer progression. Of course, cell death played an important role in the progression of NB, which also promoted our research on new targets. The scrutiny of these findings proved advantageous in uncovering innovative therapeutic targets, thereby bolstering clinical interventions.

Abstract Underwater friction stir welding (UFSW) achieves reliable joining between dissimilar materials and meets the welding demand for function and properties in lightweight structures of modern engineering. A defect monitoring method based on Variational Mode Decomposition optimized by Beluga Whale Optimization and Hilbert–Huang Transform (BWO–VMD–HHT) is proposed to solve the unclear feature of AE signal in UFSW due to the aqueous medium. UFSW experiments on Al alloy and carbon fiber reinforced thermoplastic (CFRTP) are carried out with AE signals measured. The time–frequency domain features of AE signals are extracted by BWO–VMD–HHT. The experimental results show that the main frequency of the AE signal is 22.5 kHz, and surface crack defects, shallow hole defects, and deep hole defects are accompanied by the transfer phenomena of different frequency components. Then, the feature vectors are built by frequency components in the BWO–VMD–HHT spectrum and reduced by principal component analysis, including 22.5 kHz, 24 kHz, 20.6 kHz, 18.4 kHz, 17.3 kHz, and 15.6 kHz. The feature vectors are divided into the train and test sets, and the welding defect prediction model (ResNet18-attention) is built by ResNet18 and trained by feature vectors. In the test set, the ResNet18-attention is compared with the BP, SVM, and RBF. Test results show that the precision of models has improved by at least 10%, which are trained by BWO–VMD–HHT features vector. Also, ResNet18-attention has achieved an average precision of 0.906 and recognizes the category of weld defect accurately, and this method can be applied to the defect monitoring of UFSW.

ObjectiveThe aim of this research was to gain a thorough understanding of the processes involved in cell communication and discover potential indicators for treating multiple myeloma (MM) through the use of single-cell RNA sequencing (scRNA-seq). And explored the expression of multiple myeloma-related subgroups on metal ion-related pathways to explore the relationship between MM and metal ions.MethodsWe performed a fair examination using single-cell RNA sequencing on 32 bone marrow specimens collected from 22 individuals at different points of MM advancement and 9 individuals without any health issues. To analyze the scRNA-seq data, we employed advanced computational algorithms, including Slingshot, Monocle2, and other methodologies. Specifically, Slingshot and Monocle2 enabled us to simulate the biological functionalities of different cell populations and map trajectories of cell developmental pathways. Additionally, we utilized the UMAP algorithm, a powerful dimension reduction technique, to cluster cells and identify genes that were differentially expressed across clusters.ResultsOur study revealed distinct gene expression patterns and molecular pathways within each patient, which exhibited associations with disease progression. The analysis provided insights into the tumor microenvironment (TME), intra- and inter-patient heterogeneity, and cell-cell interactions mediated by ligand-receptor signaling. And found that multiple myeloma-related subgroups were expressed higher levels in MMP and TIMP pathways, there were some associations.ConclusionOur study presents a fresh perspective for future research endeavors and clinical interventions in the field of MM. The identified gene expression patterns and molecular pathways hold immense potential as therapeutic targets for the treatment of multiple myeloma. The utilization of scRNA-seq technology has significantly contributed to a more precise understanding of the complex cellular processes and interactions within MM. Through these advancements, we are now better equipped to unravel the underlying mechanisms driving the development and progression of this complex disease.

BackgroundCervical cancer (CC) is the fourth most common malignancy among women globally and serves as the main cause of cancer-related deaths among women in developing countries. The early symptoms of CC are often not apparent, with diagnoses typically made at advanced stages, which lead to poor clinical prognoses. In recent years, numerous studies have shown that there is a close relationship between mast cells (MCs) and tumor development. However, research on the role MCs played in CC is still very limited at that time. Thus, the study conducted a single-cell multi-omics analysis on human CC cells, aiming to explore the mechanisms by which MCs interact with the tumor microenvironment in CC. The goal was to provide a scientific basis for the prevention, diagnosis, and treatment of CC, with the hope of improving patients’ prognoses and quality of life.MethodThe present study acquired single-cell RNA sequencing data from ten CC tumor samples in the ArrayExpress database. Slingshot and AUCcell were utilized to infer and assess the differentiation trajectory and cell plasticity of MCs subpopulations. Differential expression analysis of MCs subpopulations in CC was performed, employing Gene Ontology, gene set enrichment analysis, and gene set variation analysis. CellChat software package was applied to predict cell communication between MCs subpopulations and CC cells. Cellular functional experiments validated the functionality of TNFRSF12A in HeLa and Caski cell lines. Additionally, a risk scoring model was constructed to evaluate the differences in clinical features, prognosis, immune infiltration, immune checkpoint, and functional enrichment across various risk scores. Copy number variation levels were computed using inference of copy number variations.ResultThe obtained 93,524 high-quality cells were classified into ten cell types, including T_NK cells, endothelial cells, fibroblasts, smooth muscle cells, epithelial cells, B cells, plasma cells, MCs, neutrophils, and myeloid cells. Furthermore, a total of 1,392 MCs were subdivided into seven subpopulations: C0 CTSG+ MCs, C1 CALR+ MCs, C2 ALOX5+ MCs, C3 ANXA2+ MCs, C4 MGP+ MCs, C5 IL32+ MCs, and C6 ADGRL4+ MCs. Notably, the C2 subpopulation showed close associations with tumor-related MCs, with Slingshot results indicating that C2 subpopulation resided at the intermediate-to-late stage of differentiation, potentially representing a crucial transition point in the benign-to-malignant transformation of CC. CNVscore and bulk analysis results further confirmed the transforming state of the C2 subpopulation. CellChat analysis revealed TNFRSF12A as a key receptor involved in the actions of C2 ALOX5+ MCs. Moreover, in vitro experiments indicated that downregulating the TNFRSF12A gene may partially inhibit the development of CC. Additionally, a prognosis model and immune infiltration analysis based on the marker genes of the C2 subpopulation provided valuable guidance for patient prognosis and clinical intervention strategies.ConclusionsWe first identified the transformative tumor-associated MCs subpopulation C2 ALOX5+ MCs within CC, which was at a critical stage of tumor differentiation and impacted the progression of CC. In vitro experiments confirmed the inhibitory effect of knocking down the TNFRSF12A gene on the development of CC. The prognostic model constructed based on the C2 ALOX5+MCs subset demonstrated excellent predictive value. These findings offer a fresh perspective for clinical decision-making in CC.

BackgroundOvarian carcinoma (OC) is a prevalent gynecological malignancy associated with high recurrence rates and mortality, often diagnosed at advanced stages. Despite advances in immunotherapy, immune exhaustion remains a significant challenge in achieving optimal tumor control. However, the exploration of intratumoral heterogeneity of malignant epithelial cells and the ovarian cancer tumor microenvironment is still limited, hindering our comprehensive understanding of the disease.Materials and methodsUtilizing single-cell RNA sequencing (scRNA-seq), we comprehensively investigated the cellular composition across six ovarian cancer patients with omental metastasis. Our focus centered on analysis of the malignant epithelial cells. Employing CytoTRACE and slingshot pseudotime analyses, we identified critical subpopulations and explored associated transcription factors (TFs) influencing ovarian cancer progression. Furthermore, by integrating clinical factors from a large cohort of bulk RNA sequencing data, we have established a novel prognostic model to investigate the impact of the tumor immune microenvironment on ovarian cancer patients. Furthermore, we have investigated the condition of immunological exhaustion.ResultsOur study identified a distinct and highly proliferative subgroup of malignant epithelial cells, known as C2 TOP2A+ TCs. This subgroup primarily consisted of patients who hadn’t received neoadjuvant chemotherapy. Ovarian cancer patients with elevated TOP2A expression exhibited heightened sensitivity to neoadjuvant chemotherapy (NACT). Moreover, the transcription factor MYBL2 in this subgroup played a critical role in ovarian cancer development. Additionally, we developed an independent prognostic indicator, the TOP2A TCs Risk Score (TTRS), which revealed a correlation between the High TTRS Group and unfavorable outcomes. Furthermore, immune infiltration and drug sensitivity analyses demonstrated increased responsiveness to Paclitaxel, Cisplatin, and Gemcitabine in the Low TTRS Group.ConclusionThis research deepens our understanding of malignant epithelial cells in ovarian cancer and enhances our knowledge of the ovarian cancer immune microenvironment and immune exhaustion. We have revealed the heightened susceptibility of the C2 TOP2A+ TCs subgroup to neoadjuvant chemotherapy and emphasized the role of MYBL2 within the C2 subgroup in promoting the occurrence and progression of ovarian cancer. These insights provide valuable guidance for the management of ovarian cancer treatment.

The colors of walnut fruits and leaves are similar in the oil transformation period, and the fruits are easily blocked by the branches and leaves. On the basis of the improved YOLOv7-tiny, a detection model is proposed and integrated into an Android application to solve the problem of walnut identification. Ablation experiments conducted with three improved strategies show that the strategies can effectively enhance the performance of the model. In terms of combinatorial optimization, the YOLOv7-tiny detection model that combines FasterNet and LightMLP modules works excellently. Its AP50 and AP50–95 are 3.1 and 4 percentage points (97.4% and 77.3%, respectively) higher than those of the original model. YOLOv7-tiny’s model size and number of parameters are reduced by 14.6% and 14.4%, respectively, relative to those of the original model, and its detection time decreases to 15.4 ms. The model has good robustness and generalization ability and can provide a technical reference for intelligent real-time detection of walnuts during the oil conversion period.

Minimizing informal recycling activities is critical for the sustainable end-of-life treatment of electronics. Recent studies have started to revisit the concept of informality in recycling and reported empirical examples where informal sectors coordinate with formal sectors, jointly contributing to a greener recycling solution. This case study examines the systematic effort to transform and integrate the informal sector into the formal recycling industry for managing e-waste in Guiyu, China. This paper analyzes the policy design, implementation, technology development and market establishment of Guiyu's formal sector that enabled the evolution of the local informal recycling industry. The results show that the salient success factor is to offer advanced and centralized e-waste treatment by constructing a formal recycling sector while maintaining the competitive characteristics of the old informal businesses, including manual dismantling and private e-waste collection networks. Those characteristics ensured increased reuse value and sufficient e-waste sources. Meanwhile, the study found that many challenges and conflicts during this transition are rooted in the often-overlooked societal and historical contexts that profoundly shaped the local recycling industry. Authorities of regions facing challenges regulating informal recycling of e-waste, especially developing countries, could initiate similar systems based on local realities and the collaboration between formal and informal sectors to minimize the environmental and societal consequences of unregulated informal e-waste recycling.

Mesh quality is critical to the accuracy and efficiency of finite element calculations, and mesh smoothing is an essential means of reducing the number of poor elements and improving mesh quality. The deep Q-network-based optimization algorithm for planar Delaunay mesh (unconstrained DQN) has attracted increasing attention due to its advantages in autonomous optimization. However, the unconstrained DQN model does not constrain the movement area of the central node during the training process, and element quality easily falls into a local optimum, resulting in a low generalization of the DQN model. In this paper, an updateable iterative inner polygon is proposed as a constraint to limit the central node’s movement and control the element’s angle. Next, the performance of different neural networks when training the same dataset is analyzed, and the appropriate neural network is selected. After that, the effectiveness and generalization of the method were analyzed. Finally, the results were compared with those obtained by existing methods. The results show that the proposed algorithm can improve the minimum angle of global elements and the shape of poor elements, and the trained DQN model has a high generalization.

Lithium-ion battery (LIB)-based electric vehicles (EVs) are regarded as a critical technology for the decarbonization of transportation. The rising demand for EVs has triggered concerns on the supply risks of lithium and some transition metals such as cobalt and nickel needed for cathode manufacturing. There are also concerns about environmental damage from current recycling and disposal practices, as several spent LIBs are reaching the end of their life in the next few decades. Proper LIB end-of-life management can alleviate supply risks of critical materials while minimizing environmental pollution. Direct recycling, which aims at recovering active materials in the cathode and chemically upgrading said materials for new cathode manufacturing, is promising. Compared with pyrometallurgical and hydrometallurgical recycling, direct recycling has closed the material loop in cathode manufacturing via a shorter pathway and attracted attention over the past few years due to its economic and environmental competitiveness. This paper reviews current direct recycling technologies for the cathode, which is considered as the material with the highest economic value in LIBs. We structure this review in line with the direct recycling process sequence: cathode material collection, separation of cathode active materials from other components, and regeneration of degraded cathode active materials. Methods to harvest cathode active materials are well studied. Efforts are required to minimize fluoride emissions during complete separation of cathode active materials from binders and carbon. Regeneration for homogeneous cathode is achieved via solid-state or hydrothermal re-lithiation. However, the challenge of how to process different cathode chemistries together in direct recycling needs to be solved. Overall, the development of direct recycling provides the possibility to accelerate the sustainable recycling of spent LIBs from electric vehicles.

Background: Neurofibromatosis type 2 (NF2) is a rare genetic syndrome that predisposes individuals to develop bilateral vestibular schwannomas (VSs) causing a high risk of life-threatening neurological complications. Traditional treatment options for NF2-associated VS usually cause neurological damage, and to date, there are no FDA-approved pharmacotherapies for NF2. The aim of this study was to evaluate the antitumor efficacy of Qu-Du-San-Jie (QDSJ) decoction, a traditional Chinese medicine formula, on NF2-associated VS and to investigate the potential underlying mechanisms.Methods: Ultra high-performance liquid chromatography-mass spectroscopy (UHPLC-MS) analysis was performed to identify the components of QDSJ and their targets. To determine the relationships between the putative targets of QDSJ and the differential genes of NF2-associated VS, the drug-disease crossover genes were screened using the UHPLC-MS data combined with our previous gene expression profiling data. The differentially expressed genes were imported into the STRING database to generate a PPI network. Differentially expressed gene targets and pathways were identified using GO and KEGG pathway enrichment analyses. The in vitro and in vivo drug efficacy of QDSJ decoction was tested using a patient-derived schwannoma cell line and a patient-derived xenograft mouse model, respectively. H&E staining, immunochemistry, and immunofluorescence staining were used to evaluate the cell proliferation and tumor vessels.Results: A total of 133 compounds were identified in QDSJ decoction using UHPLC-MS analysis. Network pharmacology showed that the regulation of necroptosis, apoptosis, cell cycle, angiogenesis, adherens junction, and neuroactive ligand-receptor interaction could be associated with the efficacy of QDSJ in treating NF2-associated VS. Treatment with QDSJ induced necrotic cell death and apoptosis of schwannoma cells in vitro and suppressed the tumor growth in vivo. Histopathological analysis revealed areas of cell necrosis and enlarged tumor blood vessels in the QDSJ-treated tumors. The numbers of cells positive for Cyclin D1 and Ki-67 were significantly reduced in QDSJ-treated tumors compared to control tumors. Immunofluorescence staining of CD31 and αSMA showed a decreased number and density of tumor vessels and normalized vessel structure in QDSJ-treated tumors.Conclusion: Our study demonstrates that QDSJ decoction shows significant antitumor activity against NF2-associated schwannoma and is a possible candidate for future clinical trials.

Obtaining field sea ice data is crucial for the validation and improvement of satellite data and numerical models. During the 36th Chinese National Antarctic Research Expedition, seven field observations covering the whole area were conducted in Nella Fjord, and large amounts of in situ sea ice and snow thickness data were acquired. Then, the influences of snow cover, topography, and air temperature on the sea ice growth rate were examined. Based on the relationship between the sea ice growth rate and air temperature, an empirical model of sea ice thickness was developed. The results show that sea ice started to freeze in early March, and the peak growth rate was reached in mid-June, with a mean growth rate of 0.62 cm/d. Between mid-June and mid-October, the mean growth rate was 0.36–0.4 cm/d; between mid-October and mid-November, the mean growth rate decreased to 0.15 cm/d. After mid-November, ice growth stopped, and the ice thickness decreased. The growth rate and thickness of sea ice near the shore were generally greater than those closer to the center of the fjord, with differences of 0.25 cm/d in mean growth rate and 7.16 cm in mean thickness. Because of the large exchanges of heat between the atmosphere and the ocean, the sea ice thickness increased rapidly during the early stage of freeze-up. When the air temperature was between -12 and −15°C, the ice growth rate was between 0.36 and 0.4 cm/d. However, when the ice thickness reached 0.5 m, the sea ice growth rate became less sensitive to air temperature. In addition, we found that the proposed model has high simulation accuracy for the growth rate of sea ice. Based on the model, we estimated that the growth rates become zero at an air temperature of approximately −4°C. Our study highlights the inverse relationship between the sea ice growth rate and the snow thickness and the fact that the sea ice thickness is mainly affected by air temperature.

The contributions and interaction of biotic and abiotic processes in community assembly are crucial for understanding the elevational patterns of biodiversity. The combined analyses of taxonomic, phylogenetic, and functional diversity are necessary to resolve this issue. By investigating vegetation in 24 transects sampled on Hongla Snow Mountain, in the central Hengduan Mountain Ranges in Southwest China, we delineated the elevational vegetation spectrum on the eastern and western slopes, analyzed the elevational variation in taxonomic, phylogenetic, and functional diversity of woody plant species, and compared the community structure of phylogeny and function in the low-elevational shrublands, mid-elevational forests, and alpine shrubs and meadows. The species richness, phylogenetic diversity, and functional diversity of woody plants showed nonstandard hump-shaped patterns with two peaks along the elevational gradient. The community structure of phylogeny and function (including tree height, leaf area, specific leaf area, leaf thickness, bark thickness, and wood density) clustered in the low-elevation shrub communities, being random and over-dispersed in mid-elevational forests. The phylogenic structure was over-dispersed in alpine communities, whereas the functional structure was clustered. Elevational patterns in taxonomic, phylogenetic, and functional diversity, together with the mean and variation in woody plant functional traits, suggested drought stress and freeze stress as environmental filters dominating the assembly of low and high elevation non-forest communities, and a conspicuous effect of biotic facilitation was also suggested for alpine habitats. By contrast, interspecific competition dominated the community assembly of forests at mid-elevations. The difference in biodiversity indices between the west and east slopes reflected the effects of the Indian Monsoon on the geomorphic patterns of ecosystem structure. These results increased our understanding of biodiversity patterns and underlying mechanisms in the Hengduan Mountains of Southwest China and highlighted the priorities for biodiversity conservation in this region.

The actual earthquake resistance performance and the seismic damage state of bridges during future earthquakes are important issues that need to be resolved. Using an expressway reinforced concrete (RC) girder bridge in a high seismic intensity area of China as the research object, the damage correlation between different structural components of the bridge is analyzed, and the key components that determine the structural safety state of the bridge are determined. Then, the safety evaluation indexes of the bridge pier and bearing are researched, and a two-stage seismic safety evaluation methodology for RC girder bridges is proposed. The first stage is a rapid and general evaluation using empirical statistical methods, and the second stage is a precise evaluation obtained by calculating the damage index of the components. Subsequently, the seismic damage prediction matrix is presented. Considering the modification of the bridge span number, service life, and skew angle, a seismic safety evaluation from a typical single bridge to a group of bridges of the same type is implemented. Finally, an actual expressway bridge in China is presented as a numerical example to illustrate the application of the method. The research results show that damage to the key components, including bearings, piers, and abutments, is the deciding factor of the bridge damage state. The seismic damage states of piers and bearings can be conveniently assessed according to the pier top displacement angle and bearing shear deformation during earthquakes. According to the suggested standard of RC girder bridge seismic damage, the seismic safety evaluation of the whole bridge structure can be obtained using the seismic safety evaluation of individual key components of the bridge structure. According to the evaluation results of individual bridges and considering the modification of influencing factors, an earthquake performance evaluation of a group of bridges of the same type can be obtained. The two-stage seismic safety evaluation methodology proposed in this study is effective and efficient.

Objective(s): To observe and determine the effect and mechanism of psoralen on tumor necrosis factor-α (TNF-α)-induced muscle atrophy.Materials and Methods: Three sets of C2C12 cells, including blank control, TNF-α (10 or 20 ng/ml) treatment and a TNF-α (10 or 20 ng/ml) plus psoralen (80 μM) administration were investigated. Cell viability was assessed using Cell Counting Kit-8 (CCK-8) assay. Western blot analysis was used to detect protein expression of atrophic markers. Flowcytometry was used to observe the effect of psoralen on apoptosis. A quantitative real-time PCR (qRT-PCR) assay was performed to detect the mRNA level of miR-675-5P.Results: TNF-α (1, 10, 20 and 100 ng/ml) treatment inhibited C2C12 myoblast viability (PConclusion: Psoralen could reduce TNF-α-induced cytotoxicity, atrophy and apoptosis in C2C12 myoblasts. The therapeutic effect of psoralen may be achieved by down-regulating miR-675-5P.

Bacterial canker of kiwifruit is a devastating disease caused by Pseudomonas syringae pv. actinidiae (Psa). The type III secretion system (T3SS), which translocates effectors into plant cells to subvert plant immunity and promote extracellular bacterial growth, is required for Psa virulence. Despite that the “HrpR/S-HrpL” cascade that sophisticatedly regulates the expression of T3SS and effectors has been well documented, the transcriptional regulators of hrpR/S remain to be determined. In this study, the OmpR-like transcription factor, previously identified by DNA pull-down assay, was found to be involved in the regulation of hrpR/S genes, and its regulatory mechanisms and other functions in Psa were explored through techniques including gene knockout and overexpression, ChIP-seq, and RNA-seq. The OmpR-like transcription factor had binding sites in the promoter region of the hrpR/S, and the transcriptional level of the hrpR/S increased after the deletion of OmpR-like and decreased upon its overexpression in an OmpR-like deletion background. Additionally, OmpR-like overexpression reduced the strain’s capacity to form biofilms and lipopolysaccharides, led to its slow growth in King’s B medium, and reduced its swimming ability, although there was no significant effect on its pathogenicity against kiwifruit hosts. Our results indicated that OmpR-like directly and negatively regulates the transcription of hrpR/S and may be involved in the regulation of multiple biological processes in Psa. Our results provide a basis for further understanding the transcriptional regulation mechanism of hrpR/S in Psa.

In addition to the common stable and metastable phases in titanium alloys, the face-centered cubic phase was recently observed under various conditions; however, its formation remains largely unclarified. In this work, the effect of nonmetallic interstitial atoms O, N, C and B on the formation of the face-centered cubic phase of titanium was investigated with the density functional theory. The results indicate that the occupancy of O, N, C and B on the octahedral interstitial sites reduces the energy gap between the hexagonal-close-packed (HCP) and face-centered cubic (FCC) phases, thus assisting the formation of FCC-Ti under elevated temperature or plastic deformation. Such a gap further decreases with the increase in the interstitial content, which is consistent with the experimental observation of FCC-Ti under high interstitial content. The relative stability of the interstitial-containing HCP-Ti and FCC-Ti was studied against the physical and chemical origins, e.g., the lattice distortion and the electronic bonding. Interstitial O, N, C and B also reduce the stacking fault energy, thus further benefiting the formation of FCC-Ti.

3D printing (or more formally called additive manufacturing) has the potential to revolutionize the way objects are manufactured, ranging from critical applications such as aerospace components to medical devices, making the materials stronger, lighter and more durable than those manufactured via conventional methods. While the mechanical properties of Ti-6Al-4V parts manufactured with two major 3D printing techniques: selective laser melting (SLM) and electron beam melting (EBM), have been reported, it is unknown if the corrosion resistance of the 3D-printed parts is comparable to that of the alloy made with isothermal forging (ISF). The aim of this study was to identify the corrosion resistance and mechanisms of Ti-6Al-4V alloy manufactured by SLM, EBM and ISF via electrochemical corrosion tests in 3.5% NaCl solution, focusing on the effect of microstructures. It was observed that the equiaxed α + β microstructure in the ISF-manufactured Ti-6Al-4V alloy had a superior corrosion resistance to the acicular martensitic α′ + β and lamellar α + β microstructures of the 3D-printed samples via SLM and EBM, respectively. This was mainly due to the fact that (1) a higher amount of β phase was present in the ISF-manufactured sample, and (2) the fraction of phase interfaces was lower in the equiaxed α + β microstructure than in the acicular α′ + β and lamellar α + β microstructures, leading to fewer microgalvanic cells. The lower corrosion resistance of SLM-manufactured sample was also related to the higher strain energy and lower electrochemical potential induced by the presence of martensitic twins, resulting in faster anodic dissolution and higher corrosion rate.

The distribution of high-quality reservoirs in Shahejie Formation of the Shijiutuo Uplift, Central Bohai Sea, is the key factor to determine the oil and gas accumulation. Likewise, diagenesis is the key factor to control the development of lacustrine carbonate reservoirs in Shahejie Formation. So, accurately analyzing the diagenesis is very important for improving reservoir prediction. By means of polarizing microscopy, fluorescence microscopy, scanning electron microscopy, cathodoluminescence and electron probe analysis techniques, reservoir characteristics and diagenetic evolution sequence are determined. The diagenetic stage was determined by X-ray diffraction of clay minerals. Gas-liquid inclusion homogenization temperature and oxygen isotope geothermometer are used to analyze the formation period of authigenic carbonate minerals. Bioclastic dolostone is the main type of carbonate rocks, followed by dolarenite. The visceral cavity pores and residual primary intergranular pores are the main reservoir space. The diagenetic evolution sequence is established based on the different occurrences of multistage dolomites and their relationship with other diagenesis phenomena, and the final diagenetic stage is the phase B of mesodiagenesis. The favorable diagenesis for reservoir physical properties is the early formation of the pore-lining dolomite deposited in the eodiagenesis and the grain-coating dolomite deposited in the syndiagenesis, both of which weaken the subsequent mechanical compaction to the reservoir porosity. Keywords: Paleogene, Shahejie Formation, Carbonate rock, Diagenesis, Diagenetic sequence

Medulloblastoma, as the most common malignant brain tumor in children, exhibits highly dysregulated DNA methylation. The novel epigenetic marker—5-hydroxymethylcytosine (5hmC) plays essential role in gene regulation during brain development and in brain tumors. However, the biological and clinical implications of 5hmC in medulloblastoma are still unclear. Here, we detected global 5hmC levels in two independent medulloblastoma patient cohorts (discovery cohort: n = 81; validation cohort: n = 171) using ultra-high performance liquid chromatography-tandem mass spectrometry analysis. Immunohistochemistry was used to identify the cell proliferation and expression of Ten-eleven translocation 1 and 2 (TET1/2). The prognostic impacts of covariates on progression-free survival (PFS) and overall survival (OS) were evaluated using multivariate Cox hazards regression models. We observed that global 5hmC levels were decreased in medulloblastomas compared to normal cerebellums (P < 0.001). Multivariate analysis showed that low global 5hmC levels correlated with poor PFS and OS rates (discovery cohort: PFS: P = 0.003, OS: P = 0.002; validation cohort: PFS: P = 0.0002, OS: P = 0.001). Immunohistochemistry showed an inverse correlation between 5hmC score and Ki-67 index (r = -0.747, P < 0.0001). Moreover, 5hmC score in MB samples was associated with nuclear expression of TET1 (r = -0.419, P = 0.003) and TET2 (r = -0.399, P = 0.005) proteins. Our study demonstrates that loss of 5hmC is an epigenetic biomarker in medulloblastomas. Our results indicate that 5hmC could be a candidate prognostic indicator for improving survival prediction of risk stratification in patients with medulloblastoma.

Selective laser-melted (SLM) Ti-6Al-4V alloy was quasi-statically compressed in the transverse and longitudinal directions at a strain rate of 1 × 10−3 s−1 at room temperature. The twinning, in-grain misorientation axis (IGMA) distribution and active slip modes of individual grains in the deformed SLM Ti-6Al-4V alloy were studied in detail via transmission Kikuchi diffraction (TKD) and transmission electron microscopy (TEM). The α’/α phase was textured with the c-axis oriented either at ~45° or perpendicular to the building direction (BD). A combined analysis of the IGMA distribution and Schmid factor revealed that the prismatic slip or pyramidal slip was easily activated in the soft grains with their c-axes perpendicular to the BD (or the loading direction) in the longitudinal compressed sample, while slip was hardly activated in the transverse compressed sample due to the lack of soft grains. Prismatic slip with IGMA around Taylor axis also occurred in {10–11} twins. The observations revealed that the prismatic slip played a key role in accommodating the external strain and, thus, well explained the anisotropy of mechanical properties in the SLM Ti-6Al-4V alloy.

China is the largest producer of synthetic ammonia, accounting for one-third of the world’s total production. Ammonia is mainly used to produce fertilizer and is also considered as a potential fuel and new energy carrier for the future. Concomitantly, the ammonia industry is the largest energy consumer and CO _2 emitter in China’s chemical industry. In this study, we developed the MESSAGEix-ammonia model with detailed process descriptions to evaluate the energy-saving and emission reduction potential that can be generated by energy efficiency (EE) improvement, as well as the transition path and emission characteristics in the context of deep emission reduction. Results show that the cost-effective EE measures implemented under the EE scenario could reduce fresh water, fuel coal, and electricity consumptions by 7%, 25%, and 16%, as well as reduce CO _2 , PM _2.5 , SO _2 , and NOx emissions by 33%, 24%, 24%, and 24%, respectively, by 2060. Regarding the exploration of the deep de-carbonization path, carbon capture and storage technology (CCS) increases the CO _2 reduction potential to 62%, but it requires additional electricity. Meanwhile, electrolysis technology not only saves additional fresh water and fuel coal, but also reduces CO _2 , PM _2.5 , SO _2 , and NOx by 80%, 84%, 86%, and 84%, respectively. Furthermore, the integration of electrolysis technology and CCS can bring 98% carbon emission reduction, which is close to net-zero emission status. With the development of renewable electricity, sufficient, clean, and affordable electricity can be provided for electrolysis devices. Our recommendation to policy makers is that electrolysis of water to produce ammonia using renewable electricity is a feasible deep de-carbonization pathway.

Lightweighting is a design strategy to reduce energy consumption through the reduction of mass of a product. Lightweighting can be applied to machine tools to reduce the amount of energy consumed during the use phase. Thus, the energy cost of machine operation will be reduced. One might also hypothesize that since a lighter-weight machine tool requires less material to build, the cost to produce such a machine will be less. However, it may also be the case that lightweighting a machine tool increases its complexity, which will likely drive up the cost to manufacture the machine. To explore the cost drivers associated with building a machine tool, data on the features associated with a wide variety of vertical milling machine tools are collected. Then, empirical cost models are fit to this data. The results from the cost models show that the machine tool mass is a significant cost driver; other key drivers are the number of axes and spindle power. The models are used to predict the cost benefits of lightweighting in terms of mass, which are compared to potential increased manufacturing costs associated with complexities introduced due to lightweighting.

This study aimed to explore mechanisms of the effects of hydroxysafflor yellow A (HSYA) on neural stem cells (NSCs) after heat stress (HS). Rat NSCs cells were cultured at 42 °C to impose heat stress. Cell counting kit-8 and Edu assay were used to analyze NSC proliferation. Annexin V/PI apoptosis kit was used to detect NSC apoptosis. Expression and phosphorylation of autophagy and apoptosis-associated proteins were determined by western blotting. We showed that HSYA significantly promoted proliferation and attenuated apoptosis of NSCs after heat stress. HSYA also increased Bcl-2 expression but decreased the expression of Bax and cleaved caspase-3 in NSCs induced by heat stress. In addition, HSYA decreased p38 and Hsp27-78 phosphorylation and MK-2 expression after heat stress, which was consistent with NSCs treated with SB203850 treatment or p38 knockdown. Furthermore, we demonstrated that heat stress increased LC3-II expression and mTOR phosphorylation, and decreased the expression of p62 in NSCs, while HSYA, SB203850 treatment or p38 knockdown reversed these alterations. In conclusion, HSYA significantly reversed the apoptosis and autophagy of NSCs induced by heat stress (P

Background: The auditory brainstem implants (ABIs) have been used to treat deafness for patients with neurofibromatosis Type 2 and nontumor patients. The lack of an appropriate animal model has limited the study of improving hearing rehabilitation by the device. This study aimed to establish an animal model of ABI in adult rhesus macaque monkey (Macaca mulatta). Methods: Six adult rhesus macaque monkeys (M. mulatta) were included. Under general anesthesia, a multichannel ABI was implanted into the lateral recess of the fourth ventricle through the modified suboccipital-retrosigmoid (RS) approach. The electrical auditory brainstem response (EABR) waves were tested to ensure the optimal implant site. After the operation, the EABR and computed tomography (CT) were used to test and verify the effectiveness via electrophysiology and anatomy, respectively. The subjects underwent behavioral observation for 6 months, and the postoperative EABR was tested every two weeks from the 1 st month after implant surgery. Result: The implant surgery lasted an average of 5.2 h, and no monkey died or sacrificed. The averaged latencies of peaks I, II and IV were 1.27, 2.34 and 3.98 ms, respectively in the ABR. One-peak EABR wave was elicited in the operation, and one- or two-peak waves were elicited during the postoperative period. The EABR wave latencies appeared to be constant under different stimulus intensities; however, the amplitudes increased as the stimulus increased within a certain scope. Conclusions: It is feasible and safe to implant ABIs in rhesus macaque monkeys (M. mulatta) through a modified suboccipital RS approach, and EABR and CT are valid tools for animal model establishment. In addition, this model should be an appropriate animal model for the electrophysiological and behavioral study of rhesus macaque monkey with ABI.

Particle-fluid based surface generation process has already become one of the most important materials processing technology for many advanced materials such as optical crystal, ceramics and so on. Most of the particle-fluid based surface generation technology involves two key process: chemical reaction which is responsible for surface softening; physical behavior which is responsible for materials removal/deformation. Presently, researchers cannot give a reasonable explanation about the complex process in the particle-fluid based surface generation technology because of the small temporal-spatial scale and the concurrent influence of physical-chemical process. Molecular dynamics (MD) method has already been proved to be a promising approach for constructing effective model of atomic scale phenomenon and can serve as a predicting simulation tool in analyzing the complex surface generation mechanism and is employed in this research to study the essence of surface generation. The deformation and piles of water molecule is induced with the feeding of abrasive particle which justifies the property mutation of water at nanometer scale. There are little silica molecule aggregation or materials removal because the water-layer greatly reduce the strength of mechanical interaction between particle and materials surface and minimize the stress concentration. Furthermore, chemical effect is also observed at the interface: stable chemical bond is generated between water and silica which lead to the formation of silconl and the reaction rate changes with the amount of water molecules in the local environment. Novel ring structure is observed in the silica surface and it is justified to be favored of chemical reaction with water molecule. The siloxane bond formation process quickly strengthened across the interface with the feeding of abrasive particle because of the compressive stress resulted by the impacting behavior.

Piles are extensively used as a means of slope stabilization. A novel engineering technique of truncated piles that are unlike traditional piles is introduced in this paper. A simplified numerical method is proposed to analyze the stability of slopes stabilized with truncated piles based on the shear strength reduction method. The influential factors, which include pile diameter, pile spacing, depth of truncation, and existence of a weak layer, are systematically investigated from a practical point of view. The results show that an optimum ratio exists between the depth of truncation and the pile length above a slip surface, below which truncating behavior has no influence on the piled slope stability. This optimum ratio is bigger for slopes stabilized with more flexible piles and piles with larger spacing. Besides, truncated piles are more suitable for slopes with a thin weak layer than homogenous slopes. In practical engineering, the piles could be truncated reasonably while ensuring the reinforcement effect. The truncated part of piles can be filled with the surrounding soil and compacted to reduce costs by using fewer materials.

Various factors and constraints should be considered when developing a manufacturing production schedule, and such a schedule is often based on rules. This paper develops a composite dispatching rule based on heuristic rules that comprehensively consider various factors in a semiconductor production line. The composite rule is obtained by exploring various states of a semiconductor production line (machine status, queue size, etc.), where such indicators as makespan and equipment efficiency are used to judge performance. A model of the response surface, as a function of key variables, is then developed to find the optimized parameters of a composite rule for various production states. Furthermore, dynamic scheduling of semiconductor manufacturing is studied based on support vector regression (SVR). This approach dynamically obtains a composite dispatching rule (i.e., parameters of the composite dispatching rule) that can be used to optimize production performance according to real-time production line state. Following optimization, the proposed dynamic scheduling approach is tested in a real semiconductor production line to validate the effectiveness of the proposed composite rule set.

The deprivation of sensory input after hearing damage results in functional reorganization of the brain including cross-modal plasticity in the sensory cortex and changes in cognitive processing. However, it remains unclear whether partial deprivation from unilateral auditory loss (UHL) would similarly affect the neural circuitry of cognitive processes in addition to the functional organization of sensory cortex. Here, we used resting-state functional magnetic resonance imaging to investigate intrinsic activity in 34 participants with UHL from acoustic neuroma in comparison with 22 matched normal controls. In sensory regions, we found decreased regional homogeneity (ReHo) in the bilateral calcarine cortices in UHL. However, there was an increase of ReHo in the right anterior insular cortex (rAI), the key node of cognitive control network (CCN) and multimodal sensory integration, as well as in the left parahippocampal cortex (lPHC), a key node in the default mode network (DMN). Moreover, seed-based resting-state functional connectivity analysis showed an enhanced relationship between rAI and several key regions of the DMN. Meanwhile, lPHC showed more negative relationship with components in the CCN and greater positive relationship in the DMN. Such reorganizations of functional connectivity within the DMN and between the DMN and CCN were confirmed by a graph theory analysis. These results suggest that unilateral sensory input damage not only alters the activity of the sensory areas but also reshapes the regional and circuit functional organization of the cognitive control network.