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Abstract Objectives To investigate the potential of intratumoral and peritumoral radiomics derived from T2-weighted MRI to preoperatively predict extrapelvic peritoneal metastasis (EPM) in patients with epithelial ovarian cancer (EOC). Methods In this retrospective study, 488 patients from four centers were enrolled and divided into training (n = 245), internal test (n = 105), and external test (n = 138) sets. Intratumoral and peritumoral models were constructed based on radiomics features extracted from the corresponding regions. A combined intratumoral and peritumoral model was developed via a feature-level fusion. An ensemble model was created by integrating this combined model with specific independent clinical predictors. The robustness and generalizability of these models were assessed using tenfold cross-validation and both internal and external testing. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC). The Shapley Additive Explanation method was employed for model interpretation. Results The ensemble model showed superior performance across the tenfold cross-validation, with the highest mean AUC of 0.844 ± 0.063. On the internal test set, the peritumoral and ensemble models significantly outperformed the intratumoral model (AUC = 0.786 and 0.832 vs. 0.652, p = 0.007 and p

In this era of Transformers enjoying remarkable success, Convolutional Neural Networks (CNNs) remain highly relevant and useful. Indeed, hybrid Transformer-CNN network architectures, which combine the benefits of both approaches, have achieved impressive results. Vision Transformer (ViT) is a significant neural network architecture that features a convolutional layer as its first layer, primarily built on the transformer framework. However, owing to the distinct computation patterns inherent in attention and convolution, existing hardware accelerators for these two models are typically designed separately and lack a unified approach toward accelerating both models efficiently. In this paper, we present a dedicated accelerator on a field-programmable gate array (FPGA) platform. The accelerator, which integrates a configurable three-dimensional systolic array, is specifically designed to accelerate the inferential capabilities of hybrid Transformer-CNN networks. The Convolution and Transformer computations can be mapped to a systolic array by unifying these operations for matrix multiplication. Softmax and LayerNorm which are frequently used in hybrid Transformer-CNN networks were also implemented on FPGA boards. The accelerator achieved high performance with a peak throughput of 722 GOP/s at an average energy efficiency of 53 GOPS/W. Its respective computation latencies were 51.3 ms, 18.1 ms, and 6.8 ms for ViT-Base, ViT-Small, and ViT-Tiny. The accelerator provided a 12× improvement in energy efficiency compared to the CPU, a 2.3× improvement compared to the GPU, and a 1.5× to 2× improvement compared to existing accelerators regarding speed and energy efficiency.

5G base stations have experienced rapid growth, making their demand response capability non-negligible. However, the collaborative optimization of the distribution network and 5G base stations is challenging due to the complex coupling, competing interests, and information asymmetry among different stakeholders. In this paper, a distributed collaborative optimization approach is proposed for power distribution and communication networks with 5G base stations. Firstly, the model of 5G base stations considering communication load demand migration and energy storage dynamic backup is established. Afterward, a collaborative optimal operation model of power distribution and communication networks is designed to fully explore the operation flexibility of 5G base stations, and then an improved distributed algorithm based on the ADMM is developed to achieve the collaborative optimization equilibrium. Finally, the effectiveness of the proposed distributed collaborative optimization model is validated by a modified IEEE 33-bus power distribution and communication networks with 5G base stations.

Abstract Oncolytic viruses (OVs) offer a novel approach to treat solid tumors; however, their efficacy is frequently suboptimal due to various limiting factors. To address this challenge, we engineered an OV containing targets for neuron-specific microRNA-124 and Granulocyte-macrophage colony-stimulating factor (GM-CSF), significantly enhancing its neuronal safety while minimally compromising its replication capacity. Moreover, we identified PARP1 as an HSV-1 replication restriction factor using genome-wide CRISPR screening. In models of glioblastoma (GBM) and triple-negative breast cancer (TNBC), we showed that the combination of OV and a PARP inhibitor (PARPi) exhibited superior efficacy compared to either monotherapy. Additionally, single-cell RNA sequencing (scRNA-seq) revealed that this combination therapy sensitized TNBC to immune checkpoint blockade, and the incorporation of an immune checkpoint inhibitor (ICI) further increased the survival rate of tumor-bearing mice. The combination of PARPi and ICI synergistically enhanced the ability of OV to establish durable tumor-specific immune responses. Our study effectively overcomes the inherent limitations of OV therapy, providing valuable insights for the clinical treatment of TNBC, GBM, and other malignancies.

Family doctor teams, serving as health gatekeepers, are extensively advocated in China. Their composition, comprising a heterogeneous mix of professionals, contributes to a more comprehensive service, but also poses challenges. Consequently, scholarly interest has arisen in comprehending how these compositions, known as faultlines, influence team dynamics and outcomes. However, there is a lack of comprehensive exploration into how faultlines influence team members’ communication processes and knowledge sharing. This study aims to provide insights into the associations between faultlines in primary care teams and team performance, specifically exploring how knowledge sharing may mediate these effects, with the goal of revealing key insights to optimize contracted family doctor services. Survey data from 291 family doctor teams in China was utilized to test hypotheses, revealing a negative association between (social-category and information-based) faultlines and knowledge sharing. Team knowledge sharing acts as a mediator in the relationship between these faultlines and team performance. Our findings advance faultlines theory and emphasize the mediating role of knowledge sharing in elucidating the interplay between faultlines and team performance. These insights are crucial for fostering collaboration, managing faultlines, and enhancing healthcare team performance.

Nonaqueous Li metal batteries (LMBs) and aqueous Zn metal batteries (ZMBs) are promising next-generation secondary batteries owing to their high energy density. Selecting an appropriate electrolyte is critical for addressing the safety issues nonaqueous and aqueous metal batteries can encounter. Ionic liquids (ILs) have been widely used in secondary metal batteries because they are non-flammable, present good thermal stability, and have wide electrochemical windows. This review highlights the research progress on IL-based electrolytes for stable Li/Zn metal anodes. We focus particularly on these electrolytes' electrochemistry and functionalities at the electrolyte/anode interface for inhibiting dendrite growth, preventing side reactions, and enhancing electrochemical performance. It is expected that this review will shed some light on the development of ILs for next-generation metal batteries.

To enhance the performance and reduce the amount of ester-based lubricants used in weak gel drilling fluids, a shear dynamics simulation under extreme pressure conditions was employed to refine the formulation of the base oil and pressure additives. The simulation results were validated using fatty acid methyl, ethyl, and butyl esters. Fatty acid methyl ester demonstrated the lowest temperature increase and the highest load-bearing capacity post-shear. The four-ball friction test revealed that methyl oleate had a coefficient of friction of 0.0018, approximately a third of that for butyl oleate, confirming the simulation’s accuracy. By using methyl oleate as the base oil and oleamide as the pressure-resistant component, the optimal shear stress was achieved with a 10% addition of oleamide. A lubricant composed of 90% methyl oleate and 10% oleamide was tested and showed a coefficient of friction of 0.03 when 0.5% was added to bentonite slurry, indicating a strong lubricating film. Adding 1% of this lubricant to a low gel drilling fluid system did not affect its rheological properties, and the gel structure remained stable after seven days of aging. Field tests at the Fu86-3 well in the Jiangsu Oilfield of Sinopec confirmed that adding 1% of the ester-based lubricant to the drilling fluid significantly improved drilling efficiency, reduced drag by an average of 33%, and increased the drilling rate to 22.12 m/h. This innovation effectively prevents drilling complications and successfully achieves the objectives of enhancing efficiency.

Climate-smart agriculture (CSA) is a global development strategy aimed to address the interlinked challenges of food security and climate change. Expanding the implementation of conservation agriculture (CA), a vital component of CSA, is essential for enhancing agricultural and food security resilience while sustainably managing arable land. However, the extensive heterogeneity of biophysical and socioeconomic conditions presents significant complexities in promoting CA adoption. Addressing these challenges, this study carried out a comprehensive theoretical investigation of biophysical and socioeconomic factors influencing CA adoption and performance, integrating stakeholder feedback to create a systematic and robust evaluation index system for assessing CA suitability. By integrating multi-influencing factor techniques and fuzzy logic methods, we spatially identified suitable areas for CA implementation in China, providing valuable insights for land use policy. The reliability of the models was verified through a sensitivity analysis using the map removal sensitivity analysis method and the extended Fourier amplitude sensitivity test. The results indicated that 29.78% of the cultivated land was unsuitable or marginally suitable for CA, while 29.30 and 40.92% were determined to be moderately suitable and suitable zones, respectively. Suitable cultivated land was primarily distributed in the northern arid and semi-arid regions, the Loess Plateau, the Huang-Huai-Hai Plain, and the Northeast China Plain. Conversely, unsuitable, and marginally suitable cultivated land was predominantly located in the Qinghai Tibet Plateau, Middle-lower Yangtze Plain, Sichuan Basin and surrounding areas, the Yunnan-Guizhou Plateau, and Southern China. The topographical index, annual mean precipitation, humidity index, and population density were identified as the most significant factors influencing CA suitability. The CA suitability maps generated in this study will guide the development and extension agents targeting CA to suitable locations with a high potential impact, thereby maximizing the likelihood of adoption and minimizing the risk of failure.

Abstract Background Preoperative differentiation between benign and borderline epithelial ovarian tumors (EOTs) is challenging and can significantly impact clinical decision making. The purpose was to investigate whether radiomics based on T2-weighted MRI can discriminate between benign and borderline EOTs preoperatively. Methods A total of 417 patients (309, 78, and 30 samples in the training and internal and external validation sets) with pathologically proven benign and borderline EOTs were included in this multicenter study. In total, 1130 radiomics features were extracted from manually delineated tumor volumes of interest on images. The following three different models were constructed and evaluated: radiomics features only (radiomics model); clinical and radiological characteristics only (clinic-radiological model); and a combination of them all (combined model). The diagnostic performances of models were assessed using receiver operating characteristic (ROC) analysis, and area under the ROC curves (AUCs) were compared using the DeLong test. Results The best machine learning algorithm to distinguish borderline from benign EOTs was the logistic regression. The combined model achieved the best performance in discriminating between benign and borderline EOTs, with an AUC of 0.86 ± 0.07. The radiomics model showed a moderate AUC of 0.82 ± 0.07, outperforming the clinic-radiological model (AUC of 0.79 ± 0.06). In the external validation set, the combined model performed significantly better than the clinic-radiological model (AUCs of 0.86 vs. 0.63, p = 0.021 [DeLong test]). Conclusions Radiomics, based on T2-weighted MRI, can provide critical diagnostic information for discriminating between benign and borderline EOTs, thus having the potential to aid personalized treatment options.

In this paper, based on the conventional nonoverlapping stator wound field synchronous (N-SWFS) machine, a novel multi-excitation-tooth N-SWFS (MN-SWFS) machine is firstly proposed by changing winding configurations and the excitation-teeth shape. The electromagnetic performance of four optimized MN-SWFS machines sharing the same 12-stator-teeth but different rotor-teeth numbers, namely 12/10, 12/11, 12/13, and 12/14, is compared by finite element analysis (FEA). The corresponding simulation results show that 12/10 and 12/14 are the optimal stator-teeth/rotor-teeth combinations due to much smaller back electromotive force (back-EMF) THD and torque ripple ( $T_{rip}$ ). Finally, a series of comparative studies are carried out on the proposed MN-SWFS machines and the conventional N-SWFS machines. The comparative results validate that the proposed 12/10 and 12/14 MN-SWFS machines exhibit better electromagnetic performance than the conventional 12/11 and 12/13 N-SWFS machines, such as higher fundamental back-EMF amplitude and greater torque output capability, though their cogging torque ( $T_{cog}$ ) and torque ripple are slightly higher, and the torque anti-saturation ability is slightly weaker.

Carbon trading policy and consumer environmental awareness are increasingly important to manufacturers’ carbon emission reduction and pricing. To analyze their strategy selection of carbon emission reduction and pricing, this paper develops three game models, where two manufacturers could choose no cooperation (NC), only cooperation in carbon emission reduction (SC), or simultaneous cooperation in carbon emission reduction and pricing (CC). By solving these models and comparing their environmental R&D levels, net carbon emissions, and profits, the paper finds strategy selection for manufacturers and its conditions. Results show that from the view of the environmental R&D level and supply chain’s profit, NC and SC may be the optimal strategy and the second-best strategy, respectively. From the net carbon emission point of view, CC and SC should be the optimal strategy and the second-best strategy, respectively. As to manufacturers’ profits, CC should be the optimal strategy, and NC or SC should be the second-best strategy. From comprehensive views, none of these strategies could be the optimal strategy, but SC may be the second-best strategy. This paper contributes in three aspects. First, this paper designs three strategies of carbon emission reduction and pricing for two manufacturers. Second, this paper takes the initial carbon emission allowances of the government as one of decision variables. Finally, this paper investigates the effects of different strategies and finds strategy selections for manufacturers from a single view and comprehensive views.

The high pH and salinity of saline alkali soil not only seriously restrict the growth of crops, but also aggravate the pollution of heavy metals. The fixation of heavy metals and the regulation of pH by phosphorus solubilizing microorganisms may become a new way to repair heavy mental and improve saline alkali soil. In this study, a saline-alkali resistant bacteria (CZ-B1, CGMCC No: 1.19458) was screened from saline-alkali soil, and its tolerance to salt/alkali/lead stress was investigated by shaking flask experiment. The strain was identified as Bacillus amyloliquefaciens by morphology and 16S rRNA gene sequence analysis. The optimum growth temperature of CZ-B1 is about 35°C–40℃. The maximum salt stress and pH that it can tolerance are 100 g/L and 9 respectively, and its tolerance to Pb2+ can reach 2000 mg/L. The phosphorus release amount of CZ-B1 to Ca3(PO4)2 within 72 h is 91.00–102.73 mg/L. The phosphate solubilizing index in PVK agar medium and NBRIP agar medium are more than 2, which can be defined as phosphate solubilizing bacteria. Moreover, the dissolution of CZ-B1 to phosphorus is mainly attributed to tartaric acid, citric acid and succinic acid in inorganic medium. In addition, the removal rate of Pb2+ by CZ-B1 can reach 90.38% for 500 mg/L. This study found that CZ-B1 can immobilize Pb through three biological mechanisms (organic acid, extracellular polymers and mineralization reaction). The release of succinic acid (10.97 g/L) and citric acid (5.26 g/L) may be the main mechanism to promote the mineralization reaction of CZ-B1 (phosphate and oxalate) and resistance to Pb stress. In addition, the high enrichment of Pb2+ by EPS can increase the rate of extracellular electron transfer and accelerate the mineralization of CZ-B1. The screening and domestication of saline-tolerant phosphorus-solubilizing bacteria not only help to remediate Pb contamination in saline soils, but also can provide P element for plant growth in saline soil.

IntroductionThe objective of this study is to construct a multi-epitope vaccine GILE containing B-cell and T-cell epitopes against Echinococcus Multilocularis (E. multilocularis) infection based on the dominant epitopes of E. multilocularis EMY162, LAP, and GLUT1.MethodsThe structure and hydrophobicity of GILE were predicted by SWISSMODEL, pyMOL, SOPMA and VMD, and its sequence was optimized by Optimum™ Codon. The GILE gene was inserted into pCzn1 and transformed into Escherichia coli Arctic express competent cells. IPTG was added to induce the expression of recombinant proteins. High-purity GILE recombinant protein was obtained by Ni-NTA Resin. BALB/c mice were immunized with GILE mixed with Freund’s adjuvant, and the antibody levels and dynamic changes in the serum were detected by ELISA. Lymphocyte proliferation was detected by MTS. The levels of IFN-g and IL-4 were detected by ELISpot and flow cytometry (FCM). T cells were detected by FCM. The growth of hepatic cysts was evaluated by Ultrasound and their weights were measured to evaluate the immune protective effect of GILE.ResultsThe SWISS-MODEL analysis showed that the optimal model was EMY162 95-104―LAP464-479―LAP495-510―LAP396-410―LAP504-518―EMY162112-126. The SOPMA results showed that there were Alpha helix (14.88%), Extended strand (26.25%), Beta turn (3.73%) and Random coil (45.82%) in the secondary structure of GILE. The restriction enzyme digestion and sequencing results suggested that the plasmid pCzn1-GILE was successfully constructed. The SDSPAGE results indicated that the recombinant protein was 44.68 KD. The ELISA results indicated that mice immunized with GILE showed higher levels of serum antibodies compared to the PBS group. The FCM and ELISpot results indicated that mice immunized with GILE secreted more IFN-g and IL-4. Immunization with GILE also led to a significant decrease in the maximum diameter and weight of cysts and stimulated the production of CD4+ and CD8+ T Cell.DiscussionA multi-epitope vaccine GILE with good immunogenicity and antigenicity has been successfully constructed in this study, which may provide important theoretical and experimental bases for the prevention and treatment of E. multilocularis infection.

Aiming at the acoustic attenuation in the salt-cavern environment, this paper established a theoretical relationship of the ultrasonic attenuation in the salt-cavern gas storage, based on the wave equation of the acoustic wave propagating in a non-ideal medium, and considering the specific environment of gas storage, and analyzes how the wall roughness of the gas storage affects the acoustic attenuation. The results show that the inner wall roughness of the salt-cavern gas storage has an effect on the acoustic attenuation. The inner wall surface is at the solid-liquid interface, where the change of the medium will affect the attenuation of the acoustic wave, and the effective reflection coefficient of the inner wall will cause the acoustic wave to attenuate at a lower frequency. On this basis, the characteristics of insoluble particles in the salt-cavern gas storage were also studied, and the main components of different media in salt-cavern cavities and the diameter distribution of different particles were obtained, and an experimental platform was established. According to the experimental results, the roughness of a reflective surface significantly affects the attenuation coefficient of the acoustic wave, and the acoustic wave will suffer two energy losses on a rough wall surface. In addition, the insoluble particles also affect the acoustic attenuation significantly, and scattering attenuation increases with the particle size. The research conclusions provide theoretical basis for the variation characteristics of ultrasonic attenuation with the environmental medium and ultrasonic excitation frequency of the salt-cavern gas storage.

Improving energy efficiency and optimizing energy structure is the key to achieving the “dual carbon” goal and high-quality development. This paper calculates the energy efficiency of 30 provinces in China between 2000 and 2017 using the DEA method. The study found that in China, the energy efficiency is higher in East China than in West China, in South China than in North China, and in the coastal areas than in the interior. Moreover, the efficiency gap between clean fuel and fossil fuel is widening. Taking total power consumption as energy input and measuring carbon emissions using regional grid base line emission factor can accurately measure China’s clean energy efficiency. The conclusions of the study provide important references for promoting China’s energy transformation and the development of the green economy.

Abstract It suggests that the poly (3-hydroxybutyric acid-co-3-hydroxyvaleric acid) (PHBV) scaffold can be used for cartilage tissue engineering, but PHBV is short of bioactivity that is required for cartilage regeneration. To fabricate a bioactive cartilage tissue engineering scaffold that promotes cartilage regeneration, quercetin (QUE) modified PHBV (PHBV-g-QUE) fibrous scaffolds were prepared by a two-step surface modification method. The PHBV-g-QUE fibrous scaffold facilitates the growth of chondrocytes and maintains chondrocytic phenotype resulting from the upregulation of SOX9, COL II, and ACAN. The PHBV-g-QUE fibrous scaffold inhibited apoptosis of chondrocyte and reduced oxidative stress of chondrocytes by regulating the transcription of related genes. Following PHBV-g-QUE fibrous scaffolds and PHBV fibrous scaffolds with adhered chondrocytes were implanted into nude mice for 4 weeks, it demonstrated that PHBV-g-QUE fibrous scaffolds significantly promoted cartilage regeneration compared with the PHBV fibrous scaffolds. Hence, it suggests that the PHBV-g-QUE fibrous scaffold can be potentially applied in the clinical treatment of cartilage defects in the future.

The problem of electrochemical corrosion of buried pipelines in near-neutral electrolytes leads to defects in or even fracture of oil and gas pipelines and the leakage of natural gas. Based on the principle of material diffusion and migration, the research object established an electrochemical corrosion model under the metallographic structure of pipes with ferritic–pearlitic pipeline steel. The results show that the most severe corrosion occurs at the center of the corrosion on the surface of the pipeline steel in a near-neutral corrosive environment. In addition, due to corrosion product accumulation, the material corrosion rate increased by about 38%. The electrolyte potential near the corrosion electrode is smaller, the ion concentration near the electrode is the highest, and the mass transfer phenomenon around the corrosion electrode is obvious. When the material undergoes metallographic corrosion, the corrosion is more severe. This research method can be used to predict the electrochemical corrosion occurring in the metal structure of buried pipelines and has some guidance for the assessment of the integrity of the external surface of buried pipes.

Abstract Background Exosomes are extracellular vesicles (EVs) derived from endocytic compartments of eukaryotic cells which contain various biomolecules like mRNAs or miRNAs. Exosomes influence the biologic behaviour and progression of malignancies and are promising candidates as non-invasive diagnostic biomarkers or as targets for therapeutic interventions. Usually, quantitative real-time polymerase chain reaction (qRT-PCR) is used to assess gene expression in cancer exosomes, however, the ideal reference genes for normalization yet remain to be identified. Results In this study, we performed an unbiased analysis of high-throughput mRNA and miRNA-sequencing data from exosomes of patients with various cancer types and identify candidate reference genes and miRNAs in cancer exosomes. The expression stability of these candidate reference genes was evaluated by the coefficient of variation “CV” and the average expression stability value “M”. We subsequently validated these candidate reference genes in exosomes from an independent cohort of ovarian cancer patients and healthy control individuals by qRT-PCR. Conclusions Our study identifies OAZ1 and hsa-miR-6835-3p as the most reliable individual reference genes for mRNA and miRNA quantification, respectively. For superior accuracy, we recommend the use of a combination of reference genes - OAZ1/SERF2/MPP1 for mRNA and hsa-miR-6835-3p/hsa-miR-4468-3p for miRNA analyses.

Atherosclerosis (AS) is a pathological process involving lipid oxidation, immune system activation, and endothelial dysfunction. The activated immune system could lead to inflammation and oxidative stress. Risk factors like aging and hyperhomocysteinemia also promote the progression of AS. Epigenetic modifications, including DNA methylation, histone modification, and non-coding RNA, are involved in the modulation of genes between the environment and AS formation. DNA methylation is one of the most important epigenetic mechanisms in the pathogenesis of AS. However, the relationship between the progression of AS and DNA methylation is not completely understood. This review will discuss the abnormal changes of DNA methylation in AS, including genome-wide hypermethylation dominating in AS with an increase of age, hypermethylation links with methyl supply and generating hyperhomocysteinemia, and the influence of oxidative stress with the demethylation process by interfering with the hydroxyl-methylation of TET proteins. The review will also summarize the current status of epigenetic treatment, which may provide new direction and potential therapeutic targets for AS.

The transcription factors, B-box (BBX), belong to a subfamily of the zinc finger family of proteins and exhibit multiple biological functions in plant growth, development, and abiotic stress response pathways. In this study, a total of 23 CaBBX members were identified using the pepper reference genome database. According to the gene structure, conserved domains, and the phylogenetic tree, 23 CaBBX genes were divided into four groups, wherein the analysis of the promoter region indicated the presence of cis-acting elements related to plant development, hormones, and stress response. Interspecies collinearity analysis showed that the CaBBXs had three duplicated gene pairs, and the highest gene density was found on chromosomes 2 and 7. Transcriptome RNA-seq data and quantitative polymerase chain reaction (qRT-PCR) analysis of pepper plants spanning the entire period showed that more than half of the CaBBX genes were widely expressed in diversity tissues of pepper. Co-expression network analysis indicated that the CaBBXs and the anthocyanin structural genes had a close co-expression relationship. Thus, it was reasonably speculated that the CaBBX genes may be involved in the regulation of anthocyanin biosynthesis. Overall, this study involved the genome-wide characterization of the CaBBX family and may serve as a solid foundation for further investigations on CaBBX genes involved in the anthocyanin synthesis mechanisms and development in pepper.

By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H -band-selected massive galaxies in the COSMOS-DASH field, which includes 17,292 galaxies with stellar mass M _⋆ > 10 ^10 M _⊙ at 0.5 < z < 2.5. The classification scheme is designed to provide a complete morphology classification for galaxies via a combination of two machine-learning steps. We first use an unsupervised machine-learning method (i.e., bagging-based multiclustering) to cluster galaxies into five categories: spherical (SPH), early-type disk, late-type disk, irregular (IRR), and unclassified. About 48% of the galaxies (8258/17,292) are successfully clustered during this step. For the remaining sample, we adopt a supervised machine-learning method (i.e., GoogLeNet) to classify them, during which galaxies that are well classified in the previous step are taken as our training set. Consequently, we obtain a morphology classification result for the full sample. The t-SNE test shows that galaxies in our sample can be well aggregated. We also measure the parametric and nonparametric morphologies of these galaxies. We find that the Sérsic index increases from IRR to SPH and the effective radius decreases from IRR to SPH, consistent with the corresponding definitions. Galaxies from different categories are separately distributed in the G – M _20 space. Such consistencies with other characteristic descriptions of galaxy morphology demonstrate the reliability of our classification result, ensuring that it can be used as a basic catalog for further galaxy studies.

Classification of galaxy morphology is a challenging but meaningful task for the enormous amount of data produced by the next-generation telescope. By introducing the adaptive polar-coordinate transformation, we develop a rotationally-invariant supervised machine-learning (SML) method that ensures consistent classifications when rotating galaxy images, which is always required to be satisfied physically, but difficult to achieve algorithmically. The adaptive polar-coordinate transformation, compared with the conventional method of data augmentation by including additional rotated images in the training set, is proved to be an effective and efficient method in improving the robustness of the SML methods. In the previous work, we generated a catalog of galaxies with well-classified morphologies via our developed unsupervised machine-learning (UML) method. By using this UML data set as the training set, we apply the new method to classify galaxies into five categories (unclassifiable, irregulars, late-type disks, early-type disks, and spheroids). In general, the result of our morphological classifications following the sequence from irregulars to spheroids agrees well with the expected trends of other galaxy properties, including Sérsic indices, effective radii, nonparametric statistics, and colors. Thus, we demonstrate that the rotationally-invariant SML method, together with the previously developed UML method, completes the entire task of automatic classification of galaxy morphology.

Cancers that are histologically defined as the same type of cancer often need a distinct therapy based on underlying heterogeneity; likewise, histologically disparate cancers can require similar treatment approaches due to intrinsic similarities. A comprehensive analysis integrated with drug response data and molecular alterations, particularly to reveal therapeutic concordance mechanisms across histologically disparate tumor subtypes, has not yet been fully exploited. In this study, we integrated pharmacological, genomic, and transcriptomic profiling data provided from the Cancer Genome Project (CGP) in a systematic in silico investigation of the pharmacological subtypes of cancers and the intrinsic concordance of molecular mechanisms leading to similar therapeutic responses across histologically disparate tumor subtypes. We further developed a novel approach to redefine cell-to-cell similarity and drug-to-drug similarity from the therapeutic concordance, providing a new point of view to study cancer heterogeneity. This study demonstrates how pharmacological and omics data can be used to systematically classify cancers in terms of response to various compounds and provides us with a purely therapy-oriented perspective to view tumor classifications independent of histology subtypes. The knowledge of pharmacological subtypes of 367 drugs are available via our website (http://www.hywanglab.cn/dtdb/), providing the resources for precision medicine in the perspective of therapeutic response-based re-classification of tumor.

Here we report a critically ill patient who was cured of SARS-CoV-2 infection in Changsha, China. A 66-year-old Chinese woman, with no significant past medical history, developed severe pneumonia-like symptoms and later diagnosed as severe COVID-19 pneumonia. Within 2 months of hospitalization, the patient deteriorated to ARDS including pulmonary edema and SIRS with septic shock. When treatment schemes such as antibiotics plus corticosteroids showed diminished therapeutic value, hUCMSC therapy was compassionately prescribed under the patient's consent of participation. After treatment, there was significant improvement in disease inflammation-related indicators such as IL-4, IL-6, and IL-10. Eventually, it confirmed the therapeutic value that hUCMSCs could dampen the cytokine storm in the critically ill COVID-19 patient and modulated the NK cells. In the continued hUCMSC treatment, gratifying results were achieved in the follow-up of the patient. The data we acquired anticipate a significant therapeutic value of MSC treatment in severe and critically ill patients with COVID-19, while further studies are needed.

Background: KRAS mutations are the most frequent oncogenic aberration in lung adenocarcinoma. KRAS mutant isoforms differentially shape tumour biology and influence drug responses. This heterogeneity challenges the development of effective therapies for patients with KRAS-driven non-small cell lung cancer (NSCLC). Methods: We developed an integrative pharmacogenomics analysis to identify potential drug targets to overcome MEK/ERK inhibitor resistance in lung cancer cell lines with KRAS(G12C) mutation (n = 12). We validated our predictive in silico results with in vitro models using gene knockdown, pharmacological target inhibition and reporter assays. Findings: Our computational analysis identifies casein kinase 2A1 (CSNK2A1) as a mediator of MEK/ERK inhibitor resistance in KRAS(G12C) mutant lung cancer cells. CSNK2A1 knockdown reduces cell proliferation, inhibits Wnt/β-catenin signalling and increases the anti-proliferative effect of MEK inhibition selectively in KRAS(G12C) mutant lung cancer cells. The specific CK2-inhibitor silmitasertib phenocopies the CSNK2A1 knockdown effect and sensitizes KRAS(G12C) mutant cells to MEK inhibition. Interpretation: Our study supports the importance of accurate patient stratification and rational drug combinations to gain benefit from MEK inhibition in patients with KRAS mutant NSCLC. We develop a genotype-based strategy that identifies CK2 as a promising co-target in KRAS(G12C) mutant NSCLC by using available pharmacogenomics gene expression datasets. This approach is applicable to other oncogene driven cancers. Fund: This work was supported by grants from the National Natural Science Foundation of China, the National Key Research and Development Program of China, the Lung Cancer Research Foundation and a Mildred-Scheel postdoctoral fellowship from the German Cancer Aid Foundation. Keywords: Pharmacogenomic profiles, KRAS mutations, Lung adenocarcinoma, CSNK2A1, CK2, MEK inhibitor, Silmitasertib, Wnt/β-catenin, EMT

ObjectiveTo determine whether machine learning based on conventional magnetic resonance imaging (MRI) sequences have the potential for the differential diagnosis of multiple myeloma (MM), and different tumor metastasis lesions of the lumbar vertebra.MethodsWe retrospectively enrolled 107 patients newly diagnosed with MM and different metastasis of the lumbar vertebra. In total 60 MM lesions and 118 metastasis lesions were selected for training classifiers (70%) and subsequent validation (30%). Following segmentation, 282 texture features were extracted from both T1WI and T2WI images. Following regression analysis using the least absolute shrinkage and selection operator (LASSO) algorithm, the following machine learning models were selected: Support‐Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), Artificial Neural Networks (ANN), and Naïve Bayes (NB) using 10-fold cross validation, and the performances were evaluated using a confusion matrix. Matthews correlation coefficient (MCC), sensitivity, specificity, and accuracy of the models were also calculated.ResultsTo differentiate MM and metastasis, 13 features in the T1WI images and 9 features in the T2WI images were obtained. Among the 10 classifiers, the ANN classifier from the T2WI images achieved the best performance (MCC = 0.605) with accuracy, sensitivity, and specificity of 0.815, 0.879, and 0.790, respectively, in the validation cohort. To differentiate MM and metastasis subtypes, eight features in the T1WI images and seven features in the T2WI images were obtained. Among the 10 classifiers, the ANN classifier from the T2WI images achieved the best performance (MCC = 0.560, 0.412, 0.449), respectively, with accuracy = 0.648; sensitivity 0.714, 0.821, 0.897 and specificity 0.775, 0.600, 0.640 for the MM, lung, and other metastases, respectively, in the validation cohort.ConclusionsMachine learning–based classifiers showed a satisfactory performance in differentiating MM lesions from those of tumor metastasis. While their value for distinguishing myeloma from different metastasis subtypes was moderate.

Tumor-specific genomic alterations allow systematic identification of genetic interactions that promote tumorigenesis and tumor vulnerabilities, offering novel strategies for development of targeted therapies for individual patients. We develop an Individualized Network-based Co-Mutation (INCM) methodology by inspecting over 2.5 million nonsynonymous somatic mutations derived from 6,789 tumor exomes across 14 cancer types from The Cancer Genome Atlas. Our INCM analysis reveals a higher genetic interaction burden on the significantly mutated genes, experimentally validated cancer genes, chromosome regulatory factors, and DNA damage repair genes, as compared to human pan-cancer essential genes identified by CRISPR-Cas9 screenings on 324 cancer cell lines. We find that genes involved in the cancer type-specific genetic subnetworks identified by INCM are significantly enriched in established cancer pathways, and the INCM-inferred putative genetic interactions are correlated with patient survival. By analyzing drug pharmacogenomics profiles from the Genomics of Drug Sensitivity in Cancer database, we show that the network-predicted putative genetic interactions (e.g., BRCA2-TP53) are significantly correlated with sensitivity/resistance of multiple therapeutic agents. We experimentally validated that afatinib has the strongest cytotoxic activity on BT474 (IC50 = 55.5 nM, BRCA2 and TP53 co-mutant) compared to MCF7 (IC50 = 7.7 μM, both BRCA2 and TP53 wild type) and MDA-MB-231 (IC50 = 7.9 μM, BRCA2 wild type but TP53 mutant). Finally, drug-target network analysis reveals several potential druggable genetic interactions by targeting tumor vulnerabilities. This study offers a powerful network-based methodology for identification of candidate therapeutic pathways that target tumor vulnerabilities and prioritization of potential pharmacogenomics biomarkers for development of personalized cancer medicine.

Objective: Several miR/s that regulate gene/s relevant in atherogenesis are being described. We identified a miR (miR-98) that targets LOX-1, a receptor for ox-LDL, and speculated that it might be relevant in atherogenesis. Approach and results: MicroRNA-98 was predicted by bioinformatics tools. The effects of miR-98 (by use of mimics and inhibitors) on LOX-1 expression and foam cell formation in mouse peritoneal macrophages were assessed. ApoE-/- mice fed by high fat diet were administered with mmu-agomiR-98 and mmu-antagomiR-98, and expression of LOX-1 and foam cell formation in aorta were quantified. LOX-1 was established to be a direct target of miR-98 by luciferase reporter assay. Enhancement of miR-98 decreased the expression of LOX-1 and inhibited foam cell formation and lipid accumulation. Inhibition of miR-98 had the opposite effects on all parameters. Conclusions: Reduced expression of miR-98 may relate to LOX-1 expression and foam cell formation and lipid accumulation in aortas of ApoE-/- mice. Plasma level of miR-98 may be a biomarker of atherosclerotic disease process and its modulation may offer a therapeutic strategy for atherosclerosis. Keywords: MiR-98, LOX-1, Ox-LDL, Foam cells

The long-term stability analysis of cutoff wall affected by construction effect is crucial. The longterm stability of the cutoff wall of Daning Reservoir is mainly affected by the combined action of highway vehicle load, extreme highway load and water load under different water storage loads. In this paper, the prediction model and method of grey theory are used to predict the horizontal displacement at the top of the cutoff wall, the settlement at the top, the maximum principal stress of the reinforced concrete wall, and the maximum principal stress of the plastic concrete wall based on grey analysis with each storage and drainage cycle as the time series point combined with the actual situation of the project. The long-term stability of the cutoff wall under load is predicted and evaluated. The results show that the maximum stress of the monitoring 2 – 2 section cutoff wall gradually tend to be stable during the whole storage and drainage cycle. The limit maximum compressive stress of reinforced concrete wall is 4.320 MPa, and the limit maximum compressive stress of plastic concrete wall is 1.758 MPa. Judging from the material strength, the maximum principal stress is within the design strength of the material, and the plastic failure of the wall does not occur, indicating that the combined anti-seepage system of rigid cutoff wall and plastic cutoff wall adopted by the Daning Reservoir is stable and safe in the later normal operation period.

Inflammation plays an important role in atherosclerosis. Inflammasomes play a crucial role in innate immunity, which mediates the body’s response to various pathogens. Of the different types of inflammasomes, NLRP3 has been implicated in atherosclerosis through the production of proinflammatory cytokines, IL-1β and IL-18. This review describes the role of the NLRP3 inflammasome in atherosclerosis and discusses potential therapeutic targets in the inflammasome pathway.

During rapid urbanization, it is necessary to increase soil permeability and soil porosity for reducing urban runoff and waterlogging risk. Woody plants are known to increase soil porosity and preferential flow in soil via living roots growth and dead roots decay. However, the primary results of dead woody plant roots on soil porosity and permeability have been discussed based only on the hypotheses or assumptions of different researchers. In this study, living and dead roots (decayed under natural conditions for more than 5 years) of Gansu poplar trees (Populus gansuensis) were selected. They were selected to compare the influence between living and dead roots on water infiltration rate and soil porosity in a cylindrical container (diameter = 20 cm, height = 66 cm) under laboratory conditions. Results indicated that the steady-state water fluxes at the bottom of the containers without roots (control), with living roots, and with dead roots were 54.75 ± 0.80, 61.31 ± 0.61, and 55.97 ± 0.59 cm d−1, respectively. Both living roots and dead roots increased the water infiltration rates in soil and also increased the water storage capacity of soil. The water storage capacities of soil without roots, with living roots, and with dead roots were 0.279, 0.317, and 0.322 cm3 cm−3, respectively. The results from SEM indicated that smaller pores (30–50 μm) were in living roots and larger pores (100–1000 μm) were in dead roots. The soil permeability was increased by living roots possibly due to the larger channels generated on the surface of the roots; however, water absorbed into the dead roots resulted in greater water storage capacity.

Celastrol is a natural proteasome inhibitor that exhibits promising anti-tumor effects in human malignancies, especially the androgen-independent prostate cancer (AIPC) with constitutive NF-κB activation. Celastrol induces apoptosis by means of proteasome inhibition and suppresses prostate tumor growth. However, the detailed mechanism of action remains elusive. In the current study, we aim to test the hypothesis that celastrol suppresses AIPC progression via inhibiting the constitutive NF-κB activity as well as modulating the Bcl-2 family proteins.We examined the efficacy of celastrol both in vitro and in vivo, and evaluated the role of NF-κB in celastrol-mediated AIPC regression. We found that celastrol inhibited cell proliferation in all three AIPC cell lines (PC-3, DU145 and CL1), with IC₅₀ in the range of 1-2 µM. Celastrol also suppressed cell migration and invasion. Celastrol significantly induced apoptosis as evidenced by increased sub-G1 population, caspase activation and PARP cleavage. Moreover, celastrol promoted cleavage of the anti-apoptotic protein Mcl-1 and activated the pro-apoptotic protein Noxa. In addition, celastrol rapidly blocked cytosolic IκBα degradation and nuclear translocation of RelA. Likewise, celastrol inhibited the expression of multiple NF-κB target genes that are involved in proliferation, invasion and anti-apoptosis. Celastrol suppressed AIPC tumor progression by inhibiting proliferation, increasing apoptosis and decreasing angiogenesis, in PC-3 xenograft model in nude mouse. Furthermore, increased cellular IκBα and inhibited expression of various NF-κB target genes were observed in tumor tissues.Our data suggest that, via targeting the proteasome, celastrol suppresses proliferation, invasion and angiogenesis by inducing the apoptotic machinery and attenuating constitutive NF-κB activity in AIPC both in vitro and in vivo. Celastrol as an active ingredient of traditional herbal medicine could thus be developed as a new therapeutic agent for hormone-refractory prostate cancer.

To enhance the compatibility, dispersibility, and flame retardant effect of antimony trioxide (Sb2O3) in polypropylene (PP), Sb2O3 is often modified by surface modifiers in industry. This study employed the aluminate coupling agent DL-411 for the wet surface modification of Sb2O3. The experiments investigated the effects of slurry pH, DL-411 dosage, modification time, and modification temperature on the water contact angle of modified Sb2O3 (Al-Sb2O3) and the viscosity of Al-Sb2O3/liquid paraffin suspension. Fourier transform infrared spectrometer (FTIR) characterization was conducted on Sb2O3 before and after modification with aluminate coupling agent DL-411. The optimized conditions for the modification were determined as follows: pH value9, DL-411 mass fraction of 1.5%, modification time of 5 min, and modification temperature of 30 °C. The obtained Al-Sb2O3, compounded with decabromodiphenyl ethane (DBDPE) as a flame retardant, was melt-blended with PP at a 25% mass fraction. The composite flame retardant material was tested for flame retardancy, mechanical properties, and melt flow rate. A thermogravimetric analyzer (TGA) and a scanning electron microscope (SEM) were used to characterize its thermal stability and microstructure. The flame retardancy and mechanical properties of PP/Al-SbBr composite flame retardant material were significantly improved compared to the same loading of PP/SbBr composite flame retardant material. The findings indicate that adjusting the pH value to an appropriate level allows the aluminate coupling agent DL-411 to effectively enhance the flame retardancy of Sb2O3-modified composites with reduced degradation of mechanical properties, even in an environment close to room temperature and with a relatively short modification time. [ABSTRACT FROM AUTHOR]

In user-generated content (UGC) platforms, content generators (i.e., posters) account for only a minority of users. The majority of users lurk, participating in information diffusion only and making no direct contributions to the platforms (i.e., diffusers). In this paper, we study diffusers' reposting behavior in a UGC platform and compare it with that of posters. We find that diffusers generally behave similarly to posters in reposting. Both groups repost more when seeing more posts and encountering popular posts. Interestingly, their reposting behavior diverges under information redundancy, i.e., when more popular posts are seen in a dense network. Under this condition, diffusers show a much higher propensity to repost, which is (partially) driven by their lesser need for uniqueness (NFU). Overall, this study suggests an exquisite way for platforms to activate their lurking users and it sheds light on their value in generating word-of-mouth and in facilitating information diffusion. It also provides useful guidelines for firms to approach the right type of lurking users (i.e., diffusers in a dense network) by using the right method of stimulation (i.e., offering popular albeit redundant information) during product diffusion online., Author(s): Xingyu Chen [sup.1] , Xing Li [sup.2] , Dai Yao [sup.3] , Zhimin Zhou [sup.1] Author Affiliations: (1) grid.263488.3, 0000 0001 0472 9649, College of Management, Shenzhen University, , [...]