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Pharmacophores such as hydroxyethylamine (HEA) and phthalimide (PHT) have been identified as potential synthons for the development of compounds against various parasitic infections. In order to further advance our progress, we conducted an experiment utilising a collection of PHT and HEA derivatives through phenotypic screening against a diverse set of protist parasites. This approach led to the identification of a number of compounds that exhibited significant effects on the survival of Entamoeba histolytica, Trypanosoma brucei, and multiple life-cycle stages of Leishmania spp. The Leishmania hits were pursued due to the pressing necessity to expand our repertoire of reliable, cost-effective, and efficient medications for the treatment of leishmaniases. Antileishmanials must possess the essential capability to efficiently penetrate the host cells and their compartments in the disease context, to effectively eliminate the intracellular parasite. Hence, we performed a study to assess the effectiveness of eradicating L. infantum intracellular amastigotes in a model of macrophage infection. Among eleven L. infantum growth inhibitors with low-micromolar potency, PHT-39, which carries a trifluoromethyl substitution, demonstrated the highest efficacy in the intramacrophage assay, with an EC50 of 1.2 +/- 3.2 μM. Cytotoxicity testing of PHT-39 in HepG2 cells indicated a promising selectivity of over 90-fold. A chemogenomic profiling approach was conducted using an orthology-based method to elucidate the mode of action of PHT-39. This genome-wide RNA interference library of T. brucei identified sensitivity determinants for PHT-39, which included a P-type ATPase that is crucial for the uptake of miltefosine and amphotericin, strongly indicating a shared route for cellular entry. Notwithstanding the favourable properties and demonstrated efficacy in the Plasmodium berghei infection model, PHT-39 was unable to eradicate L. major infection in a murine infection model of cutaneous leishmaniasis. Currently, PHT-39 is undergoing derivatization to optimize its pharmacological characteristics. Author summary: Two novel compound series, based on hydroxyethylamine (HEA) and phthalimide (PHT) pharmacophores, previously led to the discovery of antiplasmodial lead compounds, both with therapeutic efficacy in a murine Plasmodium infection model. Here we employed these compound libraries, supplemented with newly designed HEA derivatives, for phenotypic screening against a wide range of protist parasites associated with unmet medical needs. We report potent hit compounds for Entamoeba histolytica, Trypanosoma brucei and Leishmania spp., with limited overlap in their structure–activity relation. PHT-39 efficiently penetrated host macrophages to effectively eliminate Leishmania intracellular amastigotes, while displaying high selectivity. Leveraging an orthology-based genome-wide RNAi library screen, we propose an uptake route for the PHT-39 that relies on a transmembrane flippase, known as crucial uptake transporter for the two frontline antileishmanials miltefosine and amphotericin. Despite favourable drug properties of PHT-39, experimental PHT-39 treatment failed to eliminate the Leishmania infection in a cutaneous leishmaniasis animal model. Considering PHT-39 high selectivity and the ability of the drug to effectively reach the intracellular stage of the parasite, we suggest PHT-39 for further optimization. [ABSTRACT FROM AUTHOR]

Training LiDAR point clouds object detectors requires a significant amount of annotated data, which is time-consuming and effort-demanding. Although weakly supervised 3D LiDAR-based methods have been proposed to reduce the annotation cost, their performance could be further improved. In this work, we propose a weakly supervised LiDAR-based point clouds vehicle detector that does not require any labels for the proposal generation stage and needs only a few labels for the refinement stage. It comprises two primary modules. The first is an unsupervised proposal generation module based on the geometry of point clouds. The second is the pseudo-label refinement module. We validate our method on two point clouds based object detection datasets, namely KITTI and ONCE, and compare it with various existing weakly supervised point clouds object detection methods. The experimental results demonstrate the method's effectiveness with a small amount of labeled LiDAR point clouds. [ABSTRACT FROM AUTHOR]

The sustainability and efficiency of the wind energy industry rely significantly on the accuracy and reliability of wind speed forecasting, a crucial concern for optimal planning and operation of wind power generation. In this study, we comprehensively evaluate the performance of eight wind speed prediction models, spanning statistical, traditional machine learning, and deep learning methods, to provide insights into the field of wind energy forecasting. These models include statistical models such as ARIMA (AutoRegressive Integrated Moving Average) and GM (Grey Model), traditional machine learning models like LR (Linear Regression), RF (random forest), and SVR (Support Vector Regression), as well as deep learning models comprising ANN (Artificial Neural Network), LSTM (Long Short-Term Memory), and CNN (Convolutional Neural Network). Utilizing five common model evaluation metrics, we derive valuable conclusions regarding their effectiveness. Our findings highlight the exceptional performance of deep learning models, particularly the Convolutional Neural Network (CNN) model, in wind speed prediction. The CNN model stands out for its remarkable accuracy and stability, achieving the lowest mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and the higher coefficient of determination ( R 2 ). This underscores the CNN model's outstanding capability to capture complex wind speed patterns, thereby enhancing the sustainability and reliability of the renewable energy industry. Furthermore, we emphasized the impact of model parameter tuning and external factors, highlighting their potential to further improve wind speed prediction accuracy. These findings hold significant implications for the future development of the wind energy industry. [ABSTRACT FROM AUTHOR]

Loss of bone mass can occur in mammals after prolonged disuse but the situation for hibernators that are in a state of torpor for many months of the year is not yet fully understood. The present study assesses the bone remodeling mechanisms present in Daurian ground squirrels (Spermophilus dauricus) during hibernation as compared with a model of hindlimb disuse. Differences in microstructure, mechanical properties, bone remodeling-related proteins (Runx2, OCN, ALP, RANKL, CTK and MMP-9) and key proteins of Wnt/β-catenin signaling pathway (GSK-3β and phospho-β-catenin) were evaluated in ground squirrels under 3 conditions: summer active (SA) vs. hibernation (HIB) vs. hindlimb unloaded (HLU). The results indicated that the body weight in HLU ground squirrels was lower than the SA group, and the middle tibia diameter in the HLU group was lower than that in SA and HIB groups. The thickness of cortical and trabecular bone in femurs from HLU ground squirrels was lower than in SA and HIB groups. Most parameters of the tibia in the HLU group were lower than those in SA and HIB groups, which indicated cortical bone loss in ground squirrels. Moreover, our data showed that the changes in microscopic parameters in the femur were more obvious than those in the tibia in HLU and HIB ground squirrels. The levels of Runx2 and ALP were lower in HLU ground squirrels than SA and HIB groups. The protein levels of OCN were unchanged in the three groups, but the protein levels of ALP were lower in the HLU group than in SA and HIB groups. RANKL, CTK and MMP-9 protein levels were significantly decreased in tibia of HLU ground squirrels as compared with SA and HIB groups. In addition, the protein expression levels of RANKL, CTK and MMP-9 showed no statistical difference between SA and HIB ground squirrels. Thus, the mechanisms involved in the balance between bone formation and resorption in hibernating and hindlimb unloading ground squirrels may be different. The present study showed that in femur, the Wnt signaling pathway was inhibited, the protein level of GSK-3β was increased, and the protein expression of phospho-β-catenin was decreased in the HIB group as compared with the SA group, which indicates that the Wnt signaling pathway has a great influence on the femur of the HIB group. In conclusion, the natural anti-osteoporosis properties of Daurian ground squirrels are seasonal. The squirrels do not experience bone loss when they are inactive for a long time during hibernation, but the mechanisms of anti-osteoporosis did not work in HLU summer active squirrels. [ABSTRACT FROM AUTHOR]

Motivation: Elucidating functionally similar orthologous regulatory regions for human and model organism genomes is critical for exploiting model organism research and advancing our understanding of results from genome-wide association studies (GWAS). Sequence conservation is the de facto approach for finding orthologous non-coding regions between human and model organism genomes. However, existing methods for mapping non-coding genomic regions across species are challenged by the multi-mapping, low precision, and low mapping rate issues. Results: We develop Adaptive liftOver (AdaLiftOver), a large-scale computational tool for identifying functionally similar orthologous non-coding regions across species. AdaLiftOver builds on the UCSC liftOver framework to extend the query regions and prioritizes the resulting candidate target regions based on the conservation of the epigenomic and the sequence grammar features. Evaluations of AdaLiftOver with multiple case studies, spanning both genomic intervals from epigenome datasets across a wide range of model organisms and GWAS SNPs, yield AdaLiftOver as a versatile method for deriving hard-to-obtain human epigenome datasets as well as reliably identifying orthologous loci for GWAS SNPs. Availability and implementation: The R package and the data for AdaLiftOver is available from https://github.com/keleslab/AdaLiftOver. [ABSTRACT FROM AUTHOR]

The widespread spread of antibiotic resistance genes (ARGs) in hyporheic zone (HZ) has become an emerging environmental problem due to their potentially harmful nature. In this research, three different oxygen treatment systems were set up to study the effects of oxygen changes on the abundance of ARGs in the HZ. In addition, the effects of temperature and salinity on ARGs were investigated under aerobic and anaerobic systems, respectively. The bacterial community composition of sediment samples and the relationship with ARGs were analyzed. The explanation ratio and causality of the driving factors affecting ARGs were analyzed using variation partitioning analysis (VPA) and structural equation model (SEM). The relative abundance of ARGs and mobile genetic elements (MGEs) in the anaerobic system increased significantly, which was higher than that in the aerobic system and the aerobic-anaerobic interaction system. The experiment of salinity and temperature also further proved this result. There were many bacterial communities that affected tetracycline and sulfonamide ARGs in sediments, and these host bacteria are mainly concentrated in Proteobacteria, Firmicutes and Bacteroidetes. VPA and SEM further revealed that the abundance of ARGs was mainly influenced by changes in bacterial communities and oxygen conditions, and horizontal gene transfer (HGT) of MGEs also had a positive effect on the spread of ARGs. Those findings suggest that complex oxygen conditions in the HZ alter bacterial communities and promote MGEs-mediated horizontal transfer, which together lead to the spread of ARGs. This study has value as a reference for formulating effective strategies to minimize the propagation of ARGs in underground environment. Highlights: Multidrug resistance of ARGs is more likely to be generated under interactive conditions in hyporheic zone. The anaerobic system had the fastest proliferation rate of ARGs, which was more conducive to the spread of ARGs than the aerobic and aerobic-anaerobic interactive systems. During the dynamics of ARGs, mexF was more sensitive to oxygen conditions, and sul1 and tnpA-04 also had significant differences under different temperature and salinity conditions. Most of the bacteria in the sediments of the hyporheic zone were strongly correlated with ARGs, and most of them had effects on tetracyclines and sulfonamides ARGs. [ABSTRACT FROM AUTHOR]

In this paper, we propose a fixed-size object encoding method called FOE-VRD to improve performance of visual relationship detection tasks. For each relationship triplet in a given image, FOE-VRD not only considers the subject and object, but also uses one fixed-size vector to encoding all background objects of the image. In this way, we introduce more background knowledge to assist the relationship detector for better performance. We firstly use a regular convolution neural network as a feature extractor to generate high-level features of input images. Then, for each relationship triplet, we apply ROI-pooling as the feature generator on the bounding boxes of subject and object to get two corresponding feature vectors. Moreover, we propose a novel method to encode all background objects in each image by using one fixed-size vector (i.e., FBE vector). By concatenating the 3 generated feature vectors, we successfully encode the relationship using one fixed-size vector. The generated feature vector is then feed into a fully connected neural network to get the predicate classification result. Experimental results on VRD and Visual Genome databases show that the proposed method works well on both predicate classification and relationship detection tasks, especially on the situation of zero-shot detection. [ABSTRACT FROM AUTHOR]

The hyporheic zone (HZ) is an active biogeochemical region where groundwater and surface water mix and a potential reservoir for antibiotic resistance genes (ARGs). In this paper, the relative abundance and spatial distribution of ARGs in the HZ media were investigated, taking into consideration both the five speciation of six metals and the local characteristics. The samples of surface water, groundwater, and sediment were collected from Zaohe–Weihe Rivers of Xi'an City, which is a representative city with characteristics of the northwest region of China. Of 271 ARGs associated with 9 antibiotics, 228 ARGs were detected, with a total detection rate of 84%. Sulfonamide and aminoglycoside ARGs were the dominant types of ARGs. The top 6 ARGs and mobile genetic elements (MGEs) in terms of abundance were tnpA-04, cepA, sul1, aadA2-03, sul2 and intI1. The results of principal component analysis (PCA) showed that the distribution characteristics of ARGs were not associated with the sampling sites but with the environmental medias. Similarity in the water phases and significant differences in the water and sediment phases were found. The redundancy analysis (RDA) identified the key factors controlling ARG pollution, including dissolved oxygen (DO) in surface water, total nitrogen (TN) in groundwater, and total organic carbon (TOC) in sediment. In terms of the speciation of heavy metals, we further revealed the promotion effect between ARGs and heavy metals, especially the residual fraction of Ni. In terms of horizontal transfer mechanism, ARGs were significantly correlated with tnpA-03 in water phase and tnpA-04 in sediment. In the three media, intI1 and ARGs all show a significant correlation. These findings showed that hyporheic zone exerted a bottleneck effect on the distribution and transfer of ARGs. [ABSTRACT FROM AUTHOR]

Cyclic GMP-AMP synthase (cGAS) binds to microbial and self-DNA in the cytosol and synthesizes cyclic GMP-AMP (cGAMP), which activates stimulator of interferon genes (STING) and downstream mediators to elicit an innate immune response. Regulation of cGAS activity is essential for immune homeostasis. Here, we identified the E3 ubiquitin ligase MARCH8 (also known as MARCHF8, c-MIR, and RNF178) as a negative regulator of cGAS-mediated signaling. The immune response to double-stranded DNA was attenuated by overexpression of MARCH8 and enhanced by knockdown or knockout of MARCH8. MARCH8 interacted with the enzymatically active core of cGAS through its conserved RING-CH domain and catalyzed the lysine-63 (K63)–linked polyubiquitylation of cGAS at Lys411. This polyubiquitylation event inhibited the DNA binding ability of cGAS, impaired cGAMP production, and attenuated the downstream innate immune response. Furthermore, March8-deficient mice were less susceptible than their wild-type counterparts to herpes simplex virus 1 (HSV-1) infection. Together, our findings reveal a mechanism underlying the functional regulation of cGAS and the fine-tuning of the innate immune response. MARCHing against cGAS: The cytosolic DNA sensor cGAS responds to both microbial and host DNA to generate the cyclic nucleotide cGAMP, which activates the adaptor protein STING and leads to the production of type I interferons (IFNs). Although cGAS is important for the innate immune response, its inappropriate activation leads to autoimmune responses. Yang et al. found that the E3 ubiquitin ligase MARCH8 suppressed the binding of cGAS to DNA. This effect was mediated by the ubiquitylation of cGAS at Lys411 by MARCH8, resulting in inhibition of the production of cGAMP and type I IFN. Compared to their wild-type counterparts, mice deficient in MARCH8 had enhanced IFN responses to the DNA virus HSV-1. These results suggest that therapeutically enhancing the activity of MARCH8 or the interaction of MARCH8 with cGAS may be a strategy to treat some autoimmune disorders. [ABSTRACT FROM AUTHOR]

Transition metal (TM) single atomic catalysts (MSAC-N-C) derived from doped zeolite imidazolate frameworks (ZIF-8) are considered attractive oxygen reduction reaction (ORR) catalysts for fuel cells and metal-air batteries due to their advantages of high specific surface area, more active catalytic sites, adjustable pore size, and coordination topology features. This review provides an updated overview of the latest advances of MSAC-N-C catalysts derived from ZIF-8 precursors in ORR electrocatalysis. Particularly, some key challenges, including coordination environments regulation of catalysis center in MSAC-N-C, the active sites loading optimization and synergistic effects between TM nanoclusters/nanoparticles and the single atoms on MSAC-N-C catalysis activity, as well as their adaptability in various devices, are summarized for improving future development and application of MSAC-N-C catalysts. In addition, this review puts forward future research directions, making it play a better role in ORR catalysis for fuel cells and metal air batteries. [ABSTRACT FROM AUTHOR]

Unsaturated fatty acids (UFAs) are essential for functional membrane phospholipids in most bacteria. The bifunctional dehydrogenase/isomerase FabX is an essential UFA biosynthesis enzyme in the widespread human pathogen Helicobacter pylori, a bacterium etiologically related to 95% of gastric cancers. Here, we present the crystal structures of FabX alone and in complexes with an octanoyl-acyl carrier protein (ACP) substrate or with holo-ACP. FabX belongs to the nitronate monooxygenase (NMO) flavoprotein family but contains an atypical [4Fe-4S] cluster absent in all other family members characterized to date. FabX binds ACP via its positively charged α7 helix that interacts with the negatively charged α2 and α3 helices of ACP. We demonstrate that the [4Fe-4S] cluster potentiates FMN oxidation during dehydrogenase catalysis, generating superoxide from an oxygen molecule that is locked in an oxyanion hole between the FMN and the active site residue His182. Both the [4Fe-4S] and FMN cofactors are essential for UFA synthesis, and the superoxide is subsequently excreted by H. pylori as a major resource of peroxide which may contribute to its pathogenic function in the corrosion of gastric mucosa. Helicobacter pylori FabX, a dehydrogenase/isomerase flavoprotein, is required for unsaturated fatty acid synthesis. Here, the authors characterize FabX substrate recognition and catalytic mechanism, and reveal that it contains an atypical [4Fe-4S] cluster, which is essential and participates in the catalytic cycle. [ABSTRACT FROM AUTHOR]

Summary Quantitative tools are needed to leverage the unprecedented resolution of single-cell high-throughput chromatin conformation (scHi-C) data and integrate it with other single-cell data modalities. We present single-cell gene associating domain (scGAD) scores as a dimension reduction and exploratory analysis tool for scHi-C data. scGAD enables summarization at the gene unit while accounting for inherent gene-level genomic biases. Low-dimensional projections with scGAD capture clustering of cells based on their 3D structures. Significant chromatin interactions within and between cell types can be identified with scGAD. We further show that scGAD facilitates the integration of scHi-C data with other single-cell data modalities by enabling its projection onto reference low-dimensional embeddings. This multi-modal data integration provides an automated and refined cell-type annotation for scHi-C data. Availability and implementation scGAD is part of the BandNorm R package at https://sshen82.github.io/BandNorm/articles/scGAD-tutorial.html. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Although Ti3AlC2Tx has been widely studied in applications such as electrical storage devices, there are very few reports about the field emission properties of Ti3AlC2Tx. In this work, 2-D Ti3AlC2Tx MXene was fabricated by simple etching Al layer from Ti3AlC2 in hydrofluoric acid (HF) at room temperature and employed as a cold cathode for field emission devices. The device presents a high field emission performance with a low turn-on field of 2.7 V/μm and excellent stability, much lower than the reported value of the former work (around 5 V/μm), its relative 1-D TiC nanowires (7.1 V/μm), and most of other 2-D cathode materials, such as MoS2 and graphene, which is found due to its unique accordion structure with evenly distributed sharp edges and enlarged layer spacing reducing the field screening effect. The results confirmed by numerical simulation demonstrate that the local electric intensity at sharp edges indeed significantly higher than that of elsewhere. In other words, more sharp edges owning to the increased interlayer spacing exposed, which can considerably boost field emission performance. Based on experimental data and simulation analysis, the edge effect was found to correspond well with other former reports. Hence, 2-D MXene can be a promising candidate for vacuum electronic applications other than energy storage and conversion devices. [ABSTRACT FROM AUTHOR]

The past few years have witnessed the fast development of regularization methods for deep learning models such as fully-connected deep neural networks (DNNs) and convolutional neural networks (CNNs). Part of previous methods mainly consider to drop features from input data and hidden layers, such as Dropout, Cutout and DropBlocks. DropConnect select to drop connections between fully-connected layers. By randomly discard some features or connections, the above mentioned methods relieve the overfitting problem and improve the performance of neural networks. In this paper, we proposed a novel regularization methods, namely DropFilterR, for the learning of CNNs. The basic idea of DropFilterR is to relax the rule of weight-sharing in CNNs by randomly drop elements in convolution filters. Specifically, we drop different elements in convolution filters along with their moving on input feature maps. Moreover, we may apply random drop rate to further increase the randomness of the proposed method. Also, we find a suitable way to accelerate the computation for DropFilterR based on theoretical analysis. Experimental results on several widely-used image databases such as MNIST, CIFAR-10 and Pascal VOC 2012 show that using DropFilterR improves performance on image classification tasks. [ABSTRACT FROM AUTHOR]

To reveal the adsorption mechanism of sediment to antibiotics with the presence of dissolved organic matter (DOM), batch experiments were carried out by oxytetracycline (OTC) on sediments with decayed plants (PDOM) and composted chicken manure (MDOM), and the zeta potential in the system before and after adsorption was measured. Results showed that the PDOM promoted the adsorption process, while the MDOM inhibited the adsorption. Adding PDOM, the change of zeta potential (Δζ) increased by 40.08% for first terrace sediments (FT) and 63.98% for riverbed sediments (RB), respectively; meanwhile, MDOM decreased by 20.04% for FT and 28.39% for RB, respectively. The results of kinetic fitting models of replacing the adsorption amount with Δζ were consistent with the initial. It indicated that there was a positive correlation between the adsorption amount and Δζ, and the zeta potential can be used to quickly judge the degree of adsorption process. The Derjaguin-Landau-Verwey-Overbeek (DLVO) theory describes the interactions of sediment particles. In terms of adsorption amount, zeta potential (absolute value) and total interaction energy all followed the order: RB > FT, RB-PDOM > FT-PDOM, and RB-MDOM > FT-MDOM. The more negative the zeta potential is, the better the dispersion of the particles is. Stronger repulsion is more conducive to adsorbing positively charged OTC. The site energy distribution theory further explained that the distribution of adsorption site in the various states of sediments increased while adding the PDOM and decreased while adding the MDOM. [ABSTRACT FROM AUTHOR]

Online cloud services need to fulfill clients’ requests scalably and fast. State-of-the-art cloud services are increasingly deployed as a distributed service mesh. Service to service communication is frequent in the mesh. Unfortunately, problematic events may occur between any pair of nodes in the mesh, therefore, it is vital to maximize the network visibility. A state-of-the-art approach is to model pairwise RTTs based on a latent factor model represented as a low-rank matrix factorization. A latent factor corresponds to a rank-1 component in the factorization model, and is shared by all node pairs. However, different node pairs usually experience a skewed set of hidden factors, which should be fully considered in the model. In this paper, we propose a skewness-aware matrix factorization method named SMF. We decompose the matrix factorization into basic units of rank-one latent factors, and progressively combine rank-one factors for different node pairs. We present a unifying framework to automatically and adaptively select the rank-one factors for each node pair, which not only preserves the low rankness of the matrix model, but also adapts to skewed network latency distributions. Over real-world RTT data sets, SMF significantly improves the relative error by a factor of 0.2 $\times$ to 10 $\times$ , converges fast and stably, and compactly captures fine-grained local and global network latency structures. [ABSTRACT FROM AUTHOR]

Metal–organic frameworks (MOFs) have been demonstrated as advanced adsorbents with efficient adsorption ability for removal of heavy metal and radioactive ions from wastewater, but the instability of MOFs severely limits their development and application. To address this issue, we propose a facile hydrothermal method to modify Fe-based MOF MIL-101(Fe) with graphene oxide (GO) presenting a typical sandwich structure, which can increase the active site utilization rate. Benefiting from large specific surface area and abundant active sites, the prepared MIL-101(Fe)/GO exhibits high adsorption capacity of 128.6 mg g−1 and fast adsorption equilibrium time (＜15 min) for removal of Pb(ii) from aqueous solution. The initial concentration effect and adsorption time study directly illustrates the characteristics of the Langmuir isotherm model (R2 = 0.994) and pseudo-second-order model (R2 = 0.997), supplying the basic adsorption mechanism of ion exchange. In particular, the comparative investigation and recycling adsorption of our adsorbent before and after adsorption show outstanding stabilities, implying a huge development potential of the material in adsorbing heavy metals from wastewater. [ABSTRACT FROM AUTHOR]

Understanding the social structures that people implicitly form when playing networked games helps developers create innovative gaming services to benefit both players and operators. But how can we extract and analyze this implicit social structure? The authors' proposed formalism suggests various ways to map interactions to social structure. Applying this formalism to real-world data collected from three game genres reveals the implications of the mappings on in-game and gaming-related services, ranging from network and socially aware player matchmaking to an investigation of social network robustness against player departure. [ABSTRACT FROM AUTHOR]

A correction to the article "Ubiquitin-conjugating enzyme complex Uev1A-Ubc13 promotes breast cancer metastasis through nuclear factor-кB mediated matrix metalloproteinase-1 gene regulation" that was published on March 28, 2017 is presented.

Introduction: UEV1A encodes a ubiquitin-conjugating enzyme variant (Ubc13), which is required for Ubc13-catalyzed Lys63-linked polyubiquitination of target proteins and nuclear factor κB (NF-кB) activation. Previous reports have correlated the level of UEV1A expression with tumorigenesis; however, the detailed molecular events leading to tumors particularly breast cancer and metastasis are unclear. This study is to investigate roles of different UEV1 splicing variants, and its close homolog MMS2, in promoting tumorigenesis and metastasis in breast cancer cells.Methods: We experimentally manipulated the UEV1 and MMS2 levels in MDA-MB-231 breast cancer cells and monitored their effects on cell invasion and migration, as well as tumor formation and metastasis in xenograft mice. The underlying molecular mechanisms leading to metastasis were also examined.Results: It was found that overexpression of UEV1A alone, but not UEV1C or MMS2, is sufficient to induce cell invasion in vitro and metastasis in vivo. This process is mediated by NF-κB activation and requires functional Ubc13. Our experimental data establish that among NF-κB target genes, UEV1A-regulated matrix metalloproteinase-1 (MMP1) expression plays a critical role in cell invasion and metastasis. Interestingly, experimental depletion of UEV1 in MDA-MB-231 cells reduces MMP1 expression and prevents tumor formation and metastasis in a xenograft mouse model, while overexpression of MMP1 overrides the metastasis effects in UEV1-depleted cells.Conclusions: These results identify UEV1A as a potential therapeutic target in the treatment of metastasic breast cancers. [ABSTRACT FROM AUTHOR]