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ObjectiveTo develop a deep learning–based artificial intelligence (AI) scheme for predicting the likelihood of the ground-glass nodule (GGN) detected on CT images being invasive adenocarcinoma (IA) and also compare the accuracy of this AI scheme with that of two radiologists.MethodsFirst, we retrospectively collected 828 histopathologically confirmed GGNs of 644 patients from two centers. Among them, 209 GGNs are confirmed IA and 619 are non-IA, including 409 adenocarcinomas in situ and 210 minimally invasive adenocarcinomas. Second, we applied a series of pre-preprocessing techniques, such as image resampling, rescaling and cropping, and data augmentation, to process original CT images and generate new training and testing images. Third, we built an AI scheme based on a deep convolutional neural network by using a residual learning architecture and batch normalization technique. Finally, we conducted an observer study and compared the prediction performance of the AI scheme with that of two radiologists using an independent dataset with 102 GGNs.ResultsThe new AI scheme yielded an area under the receiver operating characteristic curve (AUC) of 0.92 ± 0.03 in classifying between IA and non-IA GGNs, which is equivalent to the senior radiologist’s performance (AUC 0.92 ± 0.03) and higher than the score of the junior radiologist (AUC 0.90 ± 0.03). The Kappa value of two sets of subjective prediction scores generated by two radiologists is 0.6.ConclusionsThe study result demonstrates using an AI scheme to improve the performance in predicting IA, which can help improve the development of a more effective personalized cancer treatment paradigm.Key Points• The feasibility of using a deep learning method to predict the likelihood of the ground-glass nodule being invasive adenocarcinoma.• Residual learning–based CNN model improves the performance in classifying between IA and non-IA nodules.• Artificial intelligence (AI) scheme yields higher performance than radiologists in predicting invasive adenocarcinoma.

H5N6 highly pathogenic avian influenza virus (HPAIV) clade 2.3.4.4 not only exhibits unprecedented intercontinental spread in poultry, but can also cause serious infection in humans, posing a public health threat. Phylogenetic analyses show that 40% (8/20) of H5N6 viruses that infected humans carried H9N2 virus-derived internal genes. However, the precise contribution of H9N2 virus-derived internal genes to H5N6 virus infection in humans is unclear. Here, we report on the functional contribution of the H9N2 virus-derived matrix protein 1 (M1) to enhanced H5N6 virus replication capacity in mammalian cells. Unlike H5N1 virus-derived M1 protein, H9N2 virus-derived M1 protein showed high binding affinity for H5N6 hemagglutinin (HA) protein and increased viral progeny particle release in different mammalian cell lines. Human host factor, G protein subunit beta 1 (GNB1), exhibited strong binding to H9N2 virus-derived M1 protein to facilitate M1 transport to budding sites at the cell membrane. GNB1 knockdown inhibited the interaction between H9N2 virus-derived M1 and HA protein, and reduced influenza virus-like particles (VLPs) release. Our findings indicate that H9N2 virus-derived M1 protein promotes avian H5N6 influenza virus release from mammalian, in particular human cells, which could be a major viral factor for H5N6 virus cross-species infection.

Concrete is often used in building, bridges, dams, roads and other infrastructures. However, the porosities and natural hydrophilicity of concrete often induce the damage of the concrete architecture or other disasters. Endowing the concrete with superhydrophobicity can effectively improve the antifreeze–thaw, anti-corrosion and anti-icing properties and expand the application prospect of concrete in the modern construction industry. Despite all this, the compressive strength of superhydrophobic concrete is not high enough, limiting its application. Here, we maintained superhydrophobic concrete for 28 days and improved the compressive strength for 3.5 times from 10 MPa to 34.48 MPa. The main mechanism is that calcium silicate hydrate structures grow with the increase in maintenance time and make the inside microstructures connected more closely. In addition, XPS spectra were also collected to investigate the chemical compositions of the superhydrophobic concrete. A series of tests were carried out on superhydrophobic concrete and indicated that the superhydrophobic concrete after maintenance had high surface robustness, anti-corrosion property and high anti-icing and deicing capacity, showing the application value.

Micro-milling is a low-cost, efficient, and high-precision machining method for manufacturing tiny parts, and has significant application value in various fields. In order to meet the high-accuracy requirements, several composite micro-milling methods have been proposed. However, these methods cannot change surface characteristics of materials, and poor permeability of cooling medium on the tool-workpiece interface remains unsolved. Atmospheric pressure plasma jet can efficiently improve surface wettability without obviously changing surface microstructures and may have promising application potential in machining of difficult-to-cut materials. Here, we propose to induce atmospheric pressure plasma jet to the micro-milling area to improve machinability and surface quality of TC4 titanium alloy. The influences of plasma jet on material wettability and mechanical property are firstly investigated by conducting plasma modification and tensile experiments. Then, micro-milling experiments of TC4 titanium alloy are performed under different atmospheres (dry, nitrogen jet, plasma jet, minimum quantity lubrication, and plasma jet + minimum quantity lubrication). The experimental results indicate that plasma jet can promote material fracture of TC4 titanium alloy, as well as reduce cutting force and cutting temperature, thereby obtaining better surface quality.

Purpose To analyze the role of six human epididymis protein 4 (HE4)‐related mitochondrial ribosomal proteins (MRPs) in ovarian cancer and selected MRPL15, which is most closely related to the tumorigenesis and prognosis of ovarian cancer, for further analyses. Methods Using STRING database and MCODE plugin in Cytoscape, six MRPs were identified among genes that are upregulated in response to HE4 overexpression in epithelial ovarian cancer cells. The Cancer Genome Atlas (TCGA) ovarian cancer, GTEX, Oncomine, and TISIDB were used to analyze the expression of the six MRPs. The prognostic impact and genetic variation of these six MRPs in ovarian cancer were evaluated using Kaplan‐Meier Plotter and cBioPortal, respectively. MRPL15 was selected for immunohistochemistry and GEO verification. TCGA ovarian cancer data, gene set enrichment analysis, and Enrichr were used to explore the mechanism of MRPL15 in ovarian cancer. Finally, the relationship between MRPL15 expression and immune subtype, tumor‐infiltrating lymphocytes, and immune regulatory factors was analyzed using TCGA ovarian cancer data and TISIDB. Results Six MRPs (MRPL10, MRPL15, MRPL36, MRPL39, MRPS16, and MRPS31) related to HE4 in ovarian cancer were selected. MRPL15 was highly expressed and amplified in ovarian cancer and was related to the poor prognosis of patients. Mechanism analysis indicated that MRPL15 plays a role in ovarian cancer through pathways such as the cell cycle, DNA repair, and mTOR 1 signaling. High expression of MRPL15 in ovarian cancer may be associated with its amplification and hypomethylation. Additionally, MRPL15 showed the lowest expression in C3 ovarian cancer and was correlated with proliferation of CD8+ T cells and dendritic cells as well as TGFβR1 and IDO1 expression. Conclusion MRPL15 may be a prognostic indicator and therapeutic target for ovarian cancer. Because of its close correlation with HE4, this study provides insights into the mechanism of HE4 in ovarian cancer. MRPL15 is highly expressed in epithelial ovarian cancer and is associated with poor overall survival of patients.

Pure copper is an important metal material in the fields of integrated circuits, mold manufacturing, and aerospace. Its excellent ductility and plasticity lead to problems such as burrs and tool wear in cutting, which poses great challenges to the improvement of machining accuracy and surface quality. To achieve high-quality and efficient processing of pure copper, this paper proposes to use nanographene water-based lubricant (NGWL) to regulate its removal behavior. A single-grain diamond scribing test and a micro-milling test were carried out to systematically study the action mechanism of NGWL on removal behavior of pure copper. The results showed that, compared with dry scribing at normal forces of 100, 400, 700, and 1000 mN, the material removal efficiency induced by NGWL was increased by 54.1%, 80.7%, 44.8%, and 30.3%, respectively. Compared with dry micro-milling at feed speeds of 200, 600, 1000, and 1400 μm/s, for the 75°XT4E tool, the surface roughness Sa with NGWL-assisted micro-milling was reduced by 75.5%, 73.1%, 61.4%, and 44.2%, respectively. Similarly, for the 65°UDT4E tool, compared to dry micro-milling, the Sa with NGWL lubrication was also reduced by 28.9%, 52.2%, 54.4%, and 36.9%, respectively. The Sa of pure copper induced by NGWL could be as low as about 20 nm without scales. Overall, NGWL can regulate removal behavior of pure copper by alleviating plastic deformation and promoting ductile fracture, thereby providing a new approach to achieving high-quality and efficient processing of pure copper.

In Australia, fire has become part of the natural ecosystem. Severe fires have devastated Australia's unique forest ecosystems due to the global climate change. In this study, we integrated a multi-resolution segmentation method and a hierarchical classification framework based on expert-based knowledge to classify the burned areas and land-uses in Kangaroo Island, South Australia. Using an object-based image classification framework that combines colour and shape features from input layers, we demonstrated that the objects segmented from the multi-source data lead to a higher accuracy in classification with an overall accuracy of 90.2% and a kappa coefficient of 85.2%. On the other hand, the single source data from post-fire Landsat-8 imagery showed an overall accuracy of 87.4% which is also statistically acceptable. According to our experiment results, more than 30.44% of the study area was burned during the 2019-2020 'Black-Summer' fire season in Australia. Among the burned areas, high severity accounted for 12.14%, moderate severity for 11.48%, while low severity was 6.82%. For unburned areas, farmland accounted for 45.52% of the study area, of which about one-third was affected by the disturbances other than fire. The remaining area consists of 19.42% unaffected forest, 3.48% building and bare land, and 1.14% water. The comparison analysis shows that our object-based image classification framework takes full advantage of the multi-source data and generates the edges of burned areas more clearly, which contributes to the improved fire management and control.

Local ecosystem services have been significantly affected by land cover changes associated with rapid urbanization in China. Based on the 2000 and 2010 land cover data products with 30-m resolution, we examined the similarities and differences in the impacts of land cover change on ecosystem service values (ESV) at three coastal urban agglomerations in China between 2000 and 2010 (Liaodong Peninsula (LP), Jing-Jin-Ji (JJJ) and Shandong Peninsula (SP)). A rapid evaluation method developed by Xie et al. (2008) was used to derive an ecosystem service value coefficient. The most significant change was an increase in artificial surfaces, due to urban expansion, which mainly occurred on cultivated land. The greatest loss in total ESV (2273 million Chinese Yuan) occurred in SP, due to the large decrease in wetland areas, because this service has the highest estimated coefficient. The second greatest loss in ESV (893 million Yuan) occurred in JJJ, due to the urban expansion of major cities. In contrast, ESV increased (72 million Yuan) in LP. This study demonstrates that urban expansion does not necessarily lead to a net decline in ESV. In conclusion, land use and land cover policymaking should consider the sustainability of ecosystem services in relation to economic growth.

Background Pyruvate dehydrogenase (PDH) deficiency is an uncommon condition responsible for primary refractory lactic acidosis, and PDH E1β ( PDHB ) subunit gene mutation rarely causes of PDH deficiency. We described a missense mutation of PDHB gene in a neonate with PDH deficiency, and verified the mutation damages PDH activity in vitro. Methods Whole exome sequencing (WES) was used to discover the missense mutation. We constructed the recombinant eukaryotic recombinant expression vector, the phage-PDHB-wt/mut, containing human full-length wild-type (NM_000925.4) or mutant (c.575G > T) PDHB gene, and transfected vector into 293T cells. Western blot was performed to assess PDH protein stability, PDH activity was measured. Results A 37-week-gestation male infant was noted to have refractory lactic acidosis, growth retardation, and neurodevelopmental anomalies with abnormal brain magnetic resonance (MR) findings, starting with convulsive seizures at 3 months of age. WES analysis revealed the homozygous missense mutations in the PDHB gene, which was c.575G > T (p.Arg192Leu) in exon 6. This missense mutation of PDHB was predicted to be harmful by bioinformatics software including Sorting Intolerant From Tolerant (SIFT), Polyphen2, LRT, and Mutation Taster. Western blot showed that normal PDH protein expression was significantly decreased in the phage -PDHB-mut transfected cells than that in the phage -PDHB-wt transfected cells ( P  < 0.001). PDH activities analysis revealed that PDH activity was significantly decreased in the phage -PDHB-mut transfected cells than that in the phage -PDHB-wt transfected cells ( P  < 0.001). Conclusions c.575G > T (p.Arg192Leu) in PDHB gene is a pathogenic missense mutation, which causes PDH deficiency in autosomal recessive inheritance mode.

In order to solve the problem of low efficiency and high cost in designing inserts with groove, finite element simulation (FEM) method has been employed to directly simulate the chip breaking condition. However, the current methods tend to involve a large number of cutting experiments and a user subroutine program used for secondary development, causing inconveniency in engineering application. Here, we propose a high-efficient three-dimensional (3D) FEM method to analyze the chip breakage properties of complicate-grooved insert. For the simulation, a three-dimensional cutting simulation model is established by Deform 3D FE package, and the Johnson-Cook (J-C) material constitutive model and Cockcroft-Latham (C-L) ductile fracture criterion are adopted. To verify the validity of the model, the simulations and corresponding turning experiments of AISI 1045 steel are performed with complicate-grooved insert at several combination groups of cutting depth and feed rate. The estimated chip morphology, chip breaking process, and cutting force from the simulation are in good consistency with those from the experiments. Additionally, the comparisons between the simulations and corresponding turning experiments with complicate-grooved insert and flat rake insert are conducted. The results show that the chip breaking groove can significantly change the chip flow angle and the chip geometry and that the complicate-grooved insert can more efficiently promote chip breakage than the flat rake insert. Therefore, the 3D FEM method proposed can be used to effectively investigate the chip formation mechanism and chip breakage properties and has promising application prospects in complicate-grooved insert design and cutting parameter optimization.