Predictive model of the efficiency of hematopoietic stem cell collection in patients with multiple myeloma and lymphoma based on multiple peripheral blood markers.

INTRODUCTION: Autologous hematopoietic stem cell transplantation (ASCT) has gained extensive application in the treatment of lymphoma and multiple myeloma (MM). Plenty of studies demonstrate that peripheral blood indicators could be considered potential predictive biomarkers for hematopoietic stem cells (HSCs) collection efficiency, including white blood cell count (WBC), monocyte count (Mono), platelet count (PLT), hematocrit, and hemoglobin levels. Currently, clinically practical predictive models based on these peripheral detection indicators to quickly, conveniently, and accurately predict collection efficiency are lacking. METHODS: In total, 139 patients with MM and lymphoma undergoing mobilization and collection of ASCT were retrospectively studied. The study endpoint was successful collection of autologous HSCs. We analyzed the effects of clinical characteristics and peripheral blood markers on collection success, and screened variables to establish a prediction model. We determined the optimal cutoff value of peripheral blood markers for predicting successful stem cell collection and the clinical value of a multi-marker prediction approach. We also established a prediction model for collection efficacy. RESULTS: Univariate and multivariate logistic regression analyses showed that the mobilization regimen, Mono, PLT, mononuclear cell count (MNC), and peripheral blood CD34+ cell count (PB CD34+ counts) were significant predictors of successful collection of peripheral blood stem cells (PBSC). Two predictive models were constructed based on the results of multivariate logistic analyses. Model 1 included the mobilization regimen, Mono, PLT, and MNC, whereas Model 2 included the mobilization regimen, Mono, PLT, MNC, and PB CD34+ counts. Receiver operating characteristic (ROC) curve analysis showed that the PB CD34+ counts, Model 1, and Model 2 could predict successful HSCs collection, with cutoff values of 26.92 × 106/L, 0.548, and 0.355, respectively. Model 1 could predict successful HSCs collection with a sensitivity of 84.62%, specificity of 75.73%, and area under the curve (AUC) of 0.863. Model 2 could predict successful HSCs collection with a sensitivity of 83.52%, specificity of 94.17%, and AUC of 0.946; thus, it was superior to the PB CD34+ counts alone. CONCLUSION: Our findings suggest that the combination of the mobilization regimen, Mono, PLT, MNC, and PB CD34+ counts before collection has predictive value for the efficacy of autologous HSCs collection in patients with MM and lymphoma. Using models based on these predictive markers may help to avoid over-collection and improve patient outcomes.

Chemical fuel-driven transient 2D supramolecular organic frameworks (SOFs): catalysis for green synthesis.

Mimicking the dissipative assemblies found in living systems fueled by bioenergy, we present a novel chemical fuel-driven transient 2D SOF, formed via the redox reaction-driven transient self-assembly of tetraphenylene-based structural units and cucurbit[8]uril (CB[8]). The system was initiated by adding sodium dithionite (SDT) as the fuel, leading to the formation of 2D SOFs through 2 : 1 host-guest complexation between the viologen cation radical and CB[8]. These 2D SOFs then spontaneously disassemble over time as the radicals are oxidized by air. The temporal assembly and lifetimes of these transient SOFs can be controlled by adjusting the concentrations of the fuel. Moreover, the resulting transient 2D SOFs exhibited remarkable potential as catalysts for the green synthesis of benzyl sulfones in water.

Identification of key genes and immune infiltration in peripheral blood biomarker analysis of delayed cerebral ischemia: Valproic acid as a potential therapeutic drug.

BACKGROUND: Delayed cerebral ischemia (DCI) is a common and serious complication of subarachnoid hemorrhage (SAH). Its pathogenesis is not fully understood. Here, we developed a predictive model based on peripheral blood biomarkers and validated the model using several bioinformatic multi-analysis methods. METHODS: Six datasets were obtained from the GEO database. Characteristic genes were screened using weighted correlation network analysis (WGCNA) and differentially expressed genes. Three machine learning algorithms, elastic networks-LASSO, support vector machines (SVM-RFE) and random forests (RF), were also used to construct diagnostic prediction models for key genes. To further evaluate the performance and predictive value of the diagnostic models, nomogram model were constructed, and the clinical value of the models was assessed using Decision Curve Analysis (DCA), Area Under the Check Curve (AUC), Clinical Impact Curve (CIC), and validated in the mouse single-cell RNA-seq dataset. Mendelian randomization(MR) analysis explored the causal relationship between SAH and stroke, and the intermediate influencing factors. We validated this by retrospectively analyzing the qPCR levels of the most relevant genes in SAH and SAH-DCI patients. This experiment demonstrated a statistically significant difference between SAH and SAH-DCI and normal group controls. Finally, potential small molecule compounds interacting with the selected features were screened from the Comparative Toxicogenomics Database (CTD). RESULTS: The fGSEA results showed that activation of Toll-like receptor signaling and leukocyte transendothelial cell migration pathways were positively correlated with the DCI phenotype, whereas cytokine signaling pathways and natural killer cell-mediated cytotoxicity were negatively correlated. Consensus feature selection of DEG genes using WGCNA and three machine learning algorithms resulted in the identification of six genes (SPOCK2, TRRAP, CIB1, BCL11B, PDZD8 and LAT), which were used to predict DCI diagnosis with high accuracy. Three external datasets and the mouse single-cell dataset showed high accuracy of the diagnostic model, in addition to high performance and predictive value of the diagnostic model in DCA and CIC. MR analysis looked at stroke after SAH independent of SAH, but associated with multiple intermediate factors including Hypertensive diseases, Total triglycerides levels in medium HDL and Platelet count. qPCR confirmed that significant differences in DCI signature genes were observed between the SAH and SAH-DCI groups. Finally, valproic acid became a potential therapeutic agent for DCI based on the results of target prediction and molecular docking of the characterized genes. CONCLUSION: This diagnostic model can identify SAH patients at high risk for DCI and may provide potential mechanisms and therapeutic targets for DCI. Valproic acid may be an important future drug for the treatment of DCI.

Effects of neonicotinoid residues on non-target soil animals: A case study of meta-analysis.

Neonicotinoids (NEOs) are currently the fastest-growing and most widely used insecticide class worldwide. Increasing evidence suggests that long-term NEO residues in the environment have toxic effects on non-target soil animals. However, few studies have conducted surveys on the effects of NEOs on soil animals, and only few have focused on global systematic reviews or meta-analysis to quantify the effects of NEOs on soil animals. Here, we present a meta-analysis of 2940 observations from 113 field and laboratory studies that investigated the effects of NEOs (at concentrations of 0.001-78,600.000 mg/kg) on different soil animals across five indicators (i.e., survival, growth, behavior, reproduction, and biochemical biomarkers). Furthermore, we quantify the effects of NEOs on different species of soil animals. Results show that NEOs inhibit the survival, growth rate, behavior, and reproduction of soil animals, and alter biochemical biomarkers. Both the survival rate and longevity of individuals decreased by 100 % with NEO residues. The mean values of juvenile survival, cocoon number, and egg hatchability were reduced by 97 %, 100 %, and 84 %, respectively. Both individual and cocoon weights were reduced by 82 %, while the growth rate decreased by 88 % with NEO residues. Our meta-analysis confirms that NEOs pose significant negative impacts on soil animals.

Corrigendum: Novel FOXL2 variants in two Chinese families with blepharophimosis, ptosis, and epicanthus inversus syndrome.

[This corrects the article DOI: 10.3389/fgene.2024.1343411.].

Upgrading CO2 to sustainable aromatics via perovskite-mediated tandem catalysis.

The directional transformation of carbon dioxide (CO2) with renewable hydrogen into specific carbon-heavy products (C6+) of high value presents a sustainable route for net-zero chemical manufacture. However, it is still challenging to simultaneously achieve high activity and selectivity due to the unbalanced CO2 hydrogenation and C-C coupling rates on complementary active sites in a bifunctional catalyst, thus causing unexpected secondary reaction. Here we report LaFeO3 perovskite-mediated directional tandem conversion of CO2 towards heavy aromatics with high CO2 conversion (> 60%), exceptional aromatics selectivity among hydrocarbons (> 85%), and no obvious deactivation for 1000 hours. This is enabled by disentangling the CO2 hydrogenation domain from the C-C coupling domain in the tandem system for Iron-based catalyst. Unlike other active Fe oxides showing wide hydrocarbon product distribution due to carbide formation, LaFeO3 by design is endowed with superior resistance to carburization, therefore inhibiting uncontrolled C-C coupling on oxide and isolating aromatics formation in the zeolite. In-situ spectroscopic evidence and theoretical calculations reveal an oxygenate-rich surface chemistry of LaFeO3, that easily escape from the oxide surface for further precise C-C coupling inside zeolites, thus steering CO2-HCOOH/H2CO-Aromatics reaction pathway to enable a high yield of aromatics.

Dynamic alterations in M2 macrophage subtypes enhance flap expansion efficiency and tissue regeneration.

Dilatation of soft skin tissue is a common surgical procedure in plastic surgery. M2 macrophages play a critical role in reducing inflammation, promoting epithelial and vascular endothelial cell proliferation, enhancing collagen synthesis in fibroblasts, and orchestrating extracellular matrix remodelling by promoting angiogenesis, epithelialisation, and fibrosis. Macrophages improve flap survival by promoting microangiogenesis and collagen remodelling. However, the role of macrophages in flap expansion has not yet been investigated. Improving the expansion efficiency of dilatation flaps and promoting flap vascularisation are the pressing problems in the fields of plastic and reconstruction surgery. In the present study, we used a mouse model to assess the effects of macrophage activation on skin expansion, thickness, ultrastructure, intradermal angiogenesis, and collagen and cytokine levels. Our findings revealed dynamic changes in the macrophage content and subtypes within the expansion flaps. The enrichment of M2 macrophages significantly enhanced the efficiency of flap expansion, vascularisation, and collagen synthesis. Our findings underline the pivotal role of M2 macrophages in tissue regeneration at the molecular and biochemical levels. These findings provide a basis for improving flap expansion efficiency using M2 macrophages.

A novel HDAC6 inhibitor attenuate APAP-induced liver injury by regulating MDH1-mediated oxidative stress.

Glutathione (GSH) depletion, mitochondrial damage, and oxidative stress have been implicated in the pathogenesis of acetaminophen (APAP) hepatotoxicity. Here, we demonstrated that the expression of histone deacetylase 6 (HDAC6) is highly elevated, whereas malate dehydrogenase 1 (MDH1) is downregulated in liver tissues and AML-12 cells induced by APAP. The therapeutic benefits of LT-630, a novel HDAC6 inhibitor on APAP-induced liver injury, were also substantiated. On this basis, we demonstrated that LT-630 improved the protein expression and acetylation level of MDH1. Furthermore, after overexpression of MDH1, an upregulated NADPH/NADP+ ratio and GSH level and decreased cell apoptosis were observed in APAP-stimulated AML-12 cells. Importantly, MDH1 siRNA clearly reversed the protection of LT-630 on APAP-stimulated AML-12 cells. In conclusion, LT-630 could ameliorate liver injury by modulating MDH1-mediated oxidative stress induced by APAP.

Response of the cultivation suitability of Pu'er tea (Camellia sinensis var. assamica) to climate conditions and change in China.

Crop cultivation suitability plays a vital role in determining the distribution, quality, and production of crop and can be greatly affected by climate change. Therefore, evaluating crop cultivation suitability under climate change and identifying the factors influencing it can optimize crop cultivation layout and improve production and quality. Based on comprehensive datasets including geographical distribution points, climate data, soil characteristics, and topography, our study employed the MaxEnt model to simulate the potential distribution of Pu'er tea (Camellia sinensis var. assamica) cultivation suitability in Yunnan Province from 1961 to 2020. Furthermore, we assessed the consistency between the simulated suitable areas and the actual production of Pu'er tea. The results showed that precipitation of the warmest quarter, precipitation of the driest month, and average temperature in January were the three dominant environmental variables affecting the cultivation distribution of Pu'er tea. The high suitable areas for Pu'er tea cultivation in Yunnan Province were mainly distributed in the western and southern regions, accounting for 13.89% of the total area of Yunnan Province. The medium suitable areas are mainly distributed in the central and western regions of Yunnan Province, accounting for 20.07% of the total area of Yunnan Province. Over the past 60 years, the unsuitable area for Pu'er tea has increased, while the suitable area has shown a trend of migration to the southwest. Changes in precipitation and temperature were found to be the main drivers of the changes in the distribution of suitable areas for Pu'er tea. We also found a mismatch between the cultivation suitability and the actual production of Pu'er tea. Our study provides an accurate assessment and zoning analysis of the suitability of Pu'er tea cultivation in Yunnan Province, which can help optimize the layout of Pu'er tea cultivation and reduce potential climate risks.

Lithium isotopic constraints on the evolution of continental clay mineral factory and marine oxygenation in the earliest Paleozoic Era.

The evolution of oxygen cycles on Earth's surface has been regulated by the balance between molecular oxygen production and consumption. The Neoproterozoic-Paleozoic transition likely marks the second rise in atmospheric and oceanic oxygen levels, widely attributed to enhanced burial of organic carbon. However, it remains disputed how marine organic carbon production and burial respond to global environmental changes and whether these feedbacks trigger global oxygenation during this interval. Here, we report a large lithium isotopic and elemental dataset from marine mudstones spanning the upper Neoproterozoic to middle Cambrian [~660 million years ago (Ma) to 500 Ma]. These data indicate a dramatic increase in continental clay formation after ~525 Ma, likely linked to secular changes in global climate and compositions of the continental crust. Using a global biogeochemical model, we suggest that intensified continental weathering and clay delivery to the oceans could have notably increased the burial efficiency of organic carbon and facilitated greater oxygen accumulation in the earliest Paleozoic oceans.

PlexinA1 promotes gastric cancer migration through preventing MICAL1 protein ubiquitin/proteasome-mediated degradation in a Rac1-dependent manner.

Metastasis promotes the development of tumors and is a significant cause of gastric cancer death. For metastasis to proceed, tumor cells must become mobile by modulating their cytoskeleton. MICAL1 (Molecule Interacting with CasL1) is known as an actin cytoskeleton regulator, but the mechanisms by which it drives gastric cancer cell migration are still unclear. Analysis of gastric cancer tissues revealed that MICAL1 expression is dramatically upregulated in stomach adenocarcinoma (STAD) samples as compared to noncancerous stomach tissues. Patients with high MICAL1 expression had shorter overall survival (OS), post-progression survival (PPS) and first-progression survival (FPS) compared with patients with low MICAL1 expression. RNAi-mediated silencing of MICAL1 inhibited the expression of Vimentin, a protein involved in epithelial-mesenchymal transition. This effect correlates with a significant reduction in gastric cancer cell migration. MICAL1 overexpression reversed these preventive effects. Immunoprecipitation experiments and immunofluorescence assays revealed that PlexinA1 forms a complex with MICAL1. Importantly, specific inhibition of PlexinA1 blocked the Rac1 activation and ROS production, which, in turn, impaired MICAL1 protein stability by accelerating MICAL1 ubiquitin/proteasome-dependent degradation. Overexpression of PlexinA1 enhanced Rac1 activation, ROS production, MICAL1 and Vimentin expressions, and favored cell migration. In conclusion, this study identified MICAL1 as an important facilitator of gastric cancer cell migration, at least in part, by affecting Vimentin expression and PlexinA1 promotes gastric cancer cell migration by binding to and suppressing MICAL1 degradation in a Rac1/ROS-dependent manner.

NOTCH1 as a Negative Regulator of Avian Adipocyte Differentiation: Implications for Fat Deposition.

The NOTCH signaling pathway plays a pivotal role in diverse developmental processes, including cell proliferation and differentiation. In this study, we investigated whether this signaling molecules also contribute to avian adipogenesis. Using previous mRNA-seq datasets, we examined the expression of 11 signaling members during avian adipocyte differentiation. We found most members are down-regulated throughout differentiation (p < 0.05). As a representative, NOTCH1 was decreased in cultured chicken abdominal adipocytes during adipogenesis at mRNA and protein levels (p < 0.05). Moreover, using an overexpression plasmid for NOTCH1's intracellular domain (NICD1), as well as siRNA and DAPT to activate or deplete NOTCH1 in cells, we investigated the role of NOTCH1 in avian adipogenesis. Our findings illuminate that NOTCH1 activates the expression of HES1 and SOCS3 while it decreases NR2F2 and NUMB (p < 0.05), as well as inhibits oleic acid-induced adipocyte differentiation (p < 0.01). We further demonstrate that HES1, a downstream transcription factor activated by NOTCH1, also significantly inhibits adipogenesis by suppressing PPARγ and C/EBPα (p < 0.01). Collectively, these findings establish NOTCH1 as a negative regulator of avian adipocyte differentiation, unveiling NOTCH signaling as a potential target for regulating avian fat deposition.

A New Method Used to Enhance the SPAIR Image of the Spine MRI.

BACKGROUND: Magnetic resonance imaging (MRI) is a handy diagnostic tool for orthopedic disorders, particularly spinal and joint diseases. METHODS: The lumbar intervertebral disc is visible in the T1 and T2 weight sequences of the spine MRI, which aids in diagnosing lumbar disc herniation, lumbar spine tuberculosis, lumbar spine tumors, and other conditions. The lumbar intervertebral disc cannot be seen accurately in the Spectral Attenuated Inversion Recovery (SPAIR) due to weaknesses in the fat and frequency offset parameters, which is not conducive to developing the intelligence diagnosis model of medical image. RESULTS: In order to solve this problem, we propose a composite framework, which is first to use the contrast limited adaptive histogram equalization (CLAHE) method to enhance the SPAIR image contrast of the spine MRI and then use the non-local means method to remove the noise of the image to ensure that the image contrast is uniform without losing details. We employ the Information Entropy (IE), Peak signal-to-noise ratio (PSNR), and feature similarity index measure (FSIM) to quantify image quality after enhancement by the composite framework. CONCLUSION: The outcomes of the experiments' output images and quantitative data indicate that our composite framework is better than others.

Novel FOXL2 variants in two Chinese families with blepharophimosis, ptosis, and epicanthus inversus syndrome.

Introduction: Blepharophimosis, ptosis, and epicanthus inversus syndrome (BPES) is a rare inherited disorder. This study was aimed to identify and functionally validate FOXL2 variants in two Chinese families with BPES. Methods: The proband and his family members were subjected to whole-exome sequencing to identify disease-associated variants. Several bioinformatic tools were used to computationally predict altered proteins. In vitro functional assays were conducted by transfecting wild-type and mutant FOXL2 cDNAs into HEK-293 cells, followed by subcellular localization assays, luciferase reporter gene assays, and quantitative real-time polymerase chain reaction. Results: The clinical features of BPES, including small palpebral fissures, ptosis, telecanthus, and epicanthus inversus, were present in all affected patients. Two novel mutations were detected, c.292T>A and c.383G>T. Whole-exome sequencing analysis and prediction software suggested that these mutations were pathogenic. Functional studies showed that these two point mutations decreased FOXL2 protein expression, resulting in subcellular mislocalization and aberrant transcriptional activity of the steroidogenic acute regulatory protein gene promoter. Conclusion: Our results add to the current understanding of known FOXL2 variants in, and our in vitro experiments provide reference data and insights into the etiology of BPES. Further studies are needed to identify the possible mechanisms underlying the action of this mutation on the development of BPES.

An intrusion and environmental effects of man-made silver nanoparticles in cold seeps.

Silver nanoparticles (AgNPs) are among the most widely used metal-based engineered nanomaterials in biomedicine and nanotechnology, and account for >50 % of global nanomaterial consumer products. The increasing use of AgNPs potentially causes marine ecosystem changes; however, the environmental impacts of man-made AgNPs are still poorly studied. This study reports for the first time that man-made AgNPs intruded into cold seeps, which are important marine ecosystems where hydrogen sulfide, methane, and other hydrocarbon-rich fluid seepage occur. Using a combination of electron microscopy, geochemical and metagenomic analyses, we found that in the cold seeps with high AgNPs concentrations, the relative abundance of genes associated with anaerobic oxidation of methane (AOM) was lower, while those related to the sulfide oxidizing and sulfate reducing were higher. This suggests that AgNPs can stimulate the proliferation of sulfate-reducing and sulfide-oxidizing bacteria, likely due to the effects of activating repair mechanisms of the cells against the toxicant. A reaction of AgNPs with hydrogen sulfide to form silver sulfide could also effectively reduce the amount of available sulfate in local ecosystems, which is generally used as the AOM oxidant. These novel findings indicate that man-made AgNPs may be involved in the biogeochemical cycles of sulfur and carbon in nature, and their potential effects on the releasing of methane from the marine methane seeps should not be ignored in both scientific and environmental aspects.

Network evolution of diffusion in enterprise digitalization and intellectualization transformation: A technology-organization-environment framework perspective.

Enterprise digitalization and intellectualization (EDI) is a crucial aspect of China's modernization process. However, uncertainty in market and business decisions hinders the EDI diffusion process in China. Therefore, this research aims to solve the uncertainty problem of EDI diffusion by examining market demand and government policy coordination. First, we utilize complex network game theory and establish a technology-organization-environment framework for the factors that influence the elements of EDI transformation by combining evidence from existing studies. Second, the network game model is constructed to analyze and optimize the updating rules in the network as a diffusion strategy that enterprises under the uncertain market can adopt. Finally, the impact of adjusting government subsidies and different premiums on the diffusion of EDI transformation strategies is examined. The degree of market diffusion and average revenue of EDI are higher after the optimization of network node strategy updating rules compared to before optimization. Further analysis reveals that only the premium effect of product pricing and inverted U-shaped subsidy support from the government affect the degree of market diffusion and the average revenue of EDI, while the other premium effects are not significant. These findings enrich research related to complex networks and nonlinear dynamic strategies. They also indicate recommendations for government policies to enhance diffusion efficiency and reasonable pricing for enterprises to promote returns.

Spatial-temporal distribution and potential risk of pesticides in ambient air in the North China Plain.

The intensive use of pesticides in the North China Plain (NCP) has resulted in widespread contamination of pesticides in the local atmosphere, posing risks to air quality and human health. However, the occurrence and distribution of atmospheric pesticides in the NCP as well as their risk assessment have not been well investigated. In this study, 300 monthly samples were collected using passive air samplers with polyurethane foam at ten rural sites with different crop systems in Quzhou county, the NCP, from June 2021 to May 2022. The pesticides were quantified using mass-spectrometric techniques. Our results revealed that chlorpyrifos, carbendazim, and atrazine were the most frequently found pesticides in the air samples, with detection frequencies of ≥ 87 % across the samples. The average concentrations of atmospheric pesticides during spring (7.47 pg m-3) and summer (16.05 pg m-3) were significantly higher than those during autumn (2.04 pg m-3) and winter (1.71 pg m-3), attributable to the intensified application of pesticides during the warmer seasons. Additionally, cash crop sites exhibited higher concentrations (10.26 pg m-3) of atmospheric pesticides compared to grain crop (5.59 pg m-3) and greenhouse sites (3.81 pg m-3), primarily due to more frequent pesticides spraying events in cash crop fields. These findings indicate a distinct spatial-temporal distribution pattern of atmospheric pesticides influenced by both seasons and crop systems. Furthermore, the model-based inhalation risk assessment indicates that inhalation exposure to atmospheric pesticides is unlikely to pose a significant public concern.

The role of miRNAs in Behçet's disease.

The symptoms of Behçet's disease (BD), a multisystemic condition with autoimmune and inflammation as hallmarks, include arthritis, recurring oral and vaginal ulcers, skin rashes and lesions, and involvement of the nervous, gastrointestinal, and vascular systems. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), may be important regulators of inflammation and autoimmune disease. These ncRNAs are essential to the physiological and pathophysiological disease course, and miRNA in particular has received significant attention for its role and function in BD and its potential use as a diagnostic biomarker in recent years. Although promising as therapeutic targets, miRNAs must be studied further to fully comprehend how miRNAs in BD act biologically.

Deep graph reconstruction for multi-view clustering.

Graph-based multi-view clustering methods have achieved impressive success by exploring a complemental or independent graph embedding with low-dimension among multiple views. The majority of them, however, are shallow models with limited ability to learn the nonlinear information in multi-view data. To this end, we propose a novel deep graph reconstruction (DGR) framework for multi-view clustering, which contains three modules. Specifically, a Multi-graph Fusion Module (MFM) is employed to obtain the consensus graph. Then node representation is learned by the Graph Embedding Network (GEN). To assign clusters directly, the Clustering Assignment Module (CAM) is devised to obtain the final low-dimensional graph embedding, which can serve as the indicator matrix. In addition, a simple and powerful loss function is designed in the proposed DGR. Extensive experiments on seven real-world datasets have been conducted to verify the superior clustering performance and efficiency of DGR compared with the state-of-the-art methods.