Platelet membrane biomimetic nanoparticle-targeted delivery of TGF-ß1 siRNA attenuates renal inflammation and fibrosis.

The progression of renal fibrosis to end-stage renal disease (ESRD) is significantly influenced by transforming growth factor-beta (TGF-beta) signal pathway. This study aimed to develop nanoparticles (PMVs@PLGA complexes) with platelet membrane camouflage, which can transport interfering RNA to target and regulate the TGF-ß1 pathway in damaged renal tissues. The aim is to reduce the severity of acute kidney injury and to reduce fibrosis in chronic kidney disease. Hence, we formulated PMVs@TGF-ß1-siRNA NP complexes and employed them for both in vitro and in vivo therapy. From the experimental findings we know that the PMVs@siRNA NPs could effectively target the kidneys in unilateral ureteral obstruction (UUO) mice and ischemia/reperfusion injury (I/R) mice. In animal models of treatment, PMVs@siRNA NP complexes effectively decreased the expression of TGF-ß1 and mitigated inflammation and fibrosis in the kidneys by blocking the TGF-ß1/Smad3 pathway. Therefore, these PMVs@siRNA NP complexes can serve as a promising biological delivery system for treating kidney diseases.

Quercetin-loaded Human Umbilical cord Mesenchymal Stem Cell-derived sEVs for Spinal Cord Injury Recovery.

Following spinal cord injury, the inflammatory environment at the injury site causes local microglia and astrocytes to activate, which worsens the nerve damage in the affected area. Quercetin, an anti-inflammatory agent, has been limited in spinal cord injury due to its poor water solubility and easy degradation. Stem cell-derived extracellular vesicles can go through the blood-brain barrier and are an ideal drug delivery system. In this study, umbilical cord mesenchymal stem cell-derived extracellular vesicles were used to load quercetin to prevent its degradation and allow it to accumulate at the site of spinal cord injury. Our results showed that quercetin-loaded extracellular vesicles could inhibit the activation of microglia to M1 phenotype through the TLR4/NF-κB pathway, and the activation of astrocytes to A1 phenotype through the JAK2/STAT3 pathway. This reduced the production of inflammatory factors, mitigated neuronal damage, and inhibited the growth of astroglial scar, but promoted the recovery of motor function in rats with spinal cord injury.

Reconstruction the feedback regulation of amino acid metabolism to develop a non-auxotrophic L-threonine producing Corynebacterium glutamicum.

L-Threonine is an important feed additive with the third largest market size among the amino acids produced by microbial fermentation. The GRAS (generally regarded as safe) industrial workhorse Corynebacterium glutamicum is an attractive chassis for L-threonine production. However, the present L-threonine production in C. glutamicum cannot meet the requirement of industrialization due to the relatively low production level of L-threonine and the accumulation of large amounts of by-products (such as L-lysine, L-isoleucine, and glycine). Herein, to enhance the L-threonine biosynthesis in C. glutamicum, releasing the aspartate kinase (LysC) and homoserine dehydrogenase (Hom) from feedback inhibition by L-lysine and L-threonine, respectively, and overexpressing four flux-control genes were performed. Next, to reduce the formation of by-products L-lysine and L-isoleucine without the cause of an auxotrophic phenotype, the feedback regulation of dihydrodipicolinate synthase (DapA) and threonine dehydratase (IlvA) was strengthened by replacing the native enzymes with heterologous analogues with more sensitive feedback inhibition by L-lysine and L-isoleucine, respectively. The resulting strain maintained the capability of synthesizing enough amounts of L-lysine and L-isoleucine for cell biomass formation but exhibited almost no extracellular accumulation of these two amino acids. To further enhance L-threonine production and reduce the by-product glycine, L-threonine exporter and homoserine kinase were overexpressed. Finally, the rationally engineered non-auxotrophic strain ZcglT9 produced 67.63 g/L (17.2% higher) L-threonine with a productivity of 1.20 g/L/h (108.0% higher) in fed-batch fermentation, along with significantly reduced by-product accumulation, representing the record for L-threonine production in C. glutamicum. In this study, we developed a strategy of reconstructing the feedback regulation of amino acid metabolism and successfully applied this strategy to de novo construct a non-auxotrophic L-threonine producing C. glutamicum. The main end by-products including L-lysine, L-isoleucine, and glycine were almost eliminated in fed-batch fermentation of the engineered C. glutamicum strain. This strategy can also be used for engineering producing strains for other amino acids and derivatives.

Osthole Activates the Cholinergic Anti-Inflammatory Pathway via α7nAChR Upregulation to Alleviate Inflammatory Responses.

Osthole (also known as Osthol) is the main anti-inflammatory coumarin found in Cnidium monnieri and severs as the exclusive quality-controlled component according the Chinese Pharmacopoeia. However, its underlying anti-inflammatory mechanism remains unknown. In this study, we demonstrated that Osthole treatment significantly inhibited the generation of TNF-α, but not IL-6 in the classical LPS-stimulated RAW264.7 macrophage model. In addition, LPS induced the activation of both MAPK and NF-κB signalling pathways, of which the former was dose-dependently restrained by Osthole via suppressing the phosphorylation of JNK and P38 proteins, while the phosphorylation of IκB and P65 proteins remained unaffected. Interestingly, Osthole dose-dependently up-regulated the expression of the key cholinergic anti-inflammatory pathway regulator α7nAChR, and the TNF-α inhibition effect of Osthole was also significantly alleviated by the treatment of α7nAChR antagonist methylbetaine. These results demonstrate that Osthole may regulate TNF-α by promoting the expression of α7nAChR, thereby activate the vagus nerve-dependent cholinergic anti-inflammatory pathway.

Evaluation of cross-immunity among major porcine circovirus type 2 genotypes by infection with PCV2b and PCV2d circulating strains.

There are three main genotypes of porcine circovirus type 2 (PCV2), namely PCV2a, PCV2b and PCV2d, of which PCV2b and PCV2d are currently the most common. There are antigenic differences between these different genotypes. To explore the effect of PCV2 antigen differences on the immune protection provided by vaccines, a cross-immune protection test was carried out in pigs. Three genotype strains, PCV2a-CL, PCV2b-MDJ and PCV2d-LNHC, were inactivated and emulsified to prepare inactivated vaccines to immunize pigs, who were then challenged with the circulating strains PCV2b-BY and PCV2d-LNHC. Immunoperoxidase monolayer assays (IPMAs) and micro-neutralization assays were used to detect antibodies against the three different genotypes of PCV2. The results showed that the three genotype vaccines induced pigs to produce antibodies against the same and different genotypes of PCV2, but the levels of IPMA and neutralizing antibodies against the same genotype were higher than those against different genotypes. Quantitative Polymerase Chain Reaction (qPCR), virus titration and immunohistochemistry were used to detect PCV2 genomic DNA, live virus and antigen, respectively, in inguinal lymph nodes of experimental pigs. Following challenge with the PCV2b-BY strain, the viral DNA load in the inguinal lymph nodes of pigs immunized with the three genotype vaccines was reduced by more than 99 % compared to the unimmunized group. Following challenge with the PCV2d-LNHC strain, the viral DNA loads in the inguinal lymph nodes of pigs immunized with PCV2a, PCV2b and PCV2d genotype vaccines were reduced by 93.8 %, 99.8 % and 98.3 %, respectively, compared to unimmunized controls. In addition, neither live PCV2 virus nor antigen were detected in the inguinal lymph nodes of pigs immunized with any of the genotype vaccines (0/18), but both were detected in the lymph nodes of experimental pigs in the unimmunized control group (6/6). These findings suggest that, although the antigenic differences of the three genotype strains induce significant differences in antibody levels, they seem to have little effect on cross-protection between different genotypes.

Impact of porcine circovirus type 2 on porcine epidemic diarrhea virus replication in the IPI-FX cell line depends on the order of infection.

Introduction: A study in 2006 showed that the clinical course of PEDV disease was markedly aggravated by transplacental infection of PCV2. Therefore, we investigated whether the small intestine supports PCV2 replication and the effect of PCV2 infection on PEDV replication in epithelial cells in vitro. Methods: To confirm the intestinal tropism of PCV2, the viral loads in the small-intestinal tissues after PCV2 infection were determined with virus titration, and the viral titers in the infected pig jejunum, ileum, ileocecal valve, and colon were 104.86, 104.09, 102.52, and 102.35 TCID50/g, respectively. We then determined the propagation characteristics of PCV2 in ileal epithelial cells (IPI-FX) and jejunal epithelial cells (IPEC-J2) with an immunoperoxidase monolayer assay, virus titration, and an immunofluorescence assay. Both IPI-FX and IPEC-J2 cells supported the replication of PCV2, with titers of 105.5 and 105.0 TCID50/ml, respectively. We established an infection model of PCV2 and PEDV in IPI-FX cells and found that PEDV and PCV2 infected the cells individually and together. The effects of PCV2 infection on PEDV replication were determined with reverse transcription-quantitative PCR (qPCR), western blotting, and virus titration. When PCV2 infected IPI-FX cells before PEDV, PCV2 significantly inhibited the replication of PEDV in a dose- and time-dependent manner and that the mRNAs of IFN-ß, TNF-α, IL1ß, and OASL were downregulated (detected with qPCR). Surprisingly, when IPI-FX cells were co-infected with PCV2 and PEDV, PCV2 promoted the replication of PEDV, the expression of the host IFN-ß, TNF-α, IL1ß, and OASL mRNAs was upregulated. Discussion: These findings demonstrate that the co-infection of IPI-FX cells with PCV2 and PEDV represents an excellent in vitro model in which to investigate their combined pathogenic mechanisms.

Underwater Acoustic Target Recognition Based on Attention Residual Network.

Underwater acoustic target recognition is very complex due to the lack of labeled data sets, the complexity of the marine environment, and the interference of background noise. In order to enhance it, we propose an attention-based residual network recognition method (AResnet). The method can be used to identify ship-radiated noise in different environments. Firstly, a residual network is used to extract the deep abstract features of three-dimensional fusion features, and then a channel attention module is used to enhance different channels. Finally, the features are classified by the joint supervision of cross-entropy and central loss functions. At the same time, for the recognition of ship-radiated noise in other environments, we use the pre-training network AResnet to extract the deep acoustic features and apply the network structure to underwater acoustic target recognition after fine-tuning. The two sets of ship radiation noise datasets are verified, the DeepShip dataset is trained and verified, and the average recognition accuracy is 99%. Then, the trained AResnet structure is fine-tuned and applied to the ShipsEar dataset. The average recognition accuracy is 98%, which is better than the comparison method.

Rapid detection of porcine circovirus type 2 by a red latex microsphere immunochromatographic strip.

To establish a rapid and specific antigen detection method for porcine circovirus type 2 (PCV2), monoclonal antibodies (mAbs) were produced against the PCV2 epidemic strains and a red latex microsphere immunochromatographic strip was established. A total of eight anti-PCV2b and four anti-PCV2d mAbs were produced, and seven mAbs were confirmed to react with PCV2a, PCV2b, and PCV2d strains using an immunoperoxidase monolayer assay. The results of micro-neutralization tests showed that the mAbs 2C8, 9H4, 10G7, 7B9, and 7C7 had good neutralizing activity, whereas the neutralizing activity of the mAbs 4B3, 4C9, 6H9, and 7E2 was lower than 50%. Three mAbs, 4B3, 7C7, and 9H4, and PCV2 pAb were selected for the establishment of a red latex microsphere immunochromatographic strip, and the combination of mAb 7C7 labeled with red latex microspheres and mAb 9H4 exhibited the greatest detection ability. The immunochromatographic strip had minimum detection limits of 102.5 TCID50/0.1 ml, 100.7 TCID50/0.1 ml, and 101.5 TCID50/0.1 ml for PCV2a/CL, PCV2b/MDJ, and PCV2d/LNHC, respectively. Furthermore, no cross-reactivity was found for African swine fever virus, classical swine fever virus, porcine respiratory and reproductive syndrome virus, porcine parvovirus, porcine pseudorabies virus, porcine circovirus type 1, transmissible gastroenteritis virus, porcine epidemic diarrhea virus, porcine rotavirus, or porcine deltacoronavirus using the immunochromatographic strip. Using PCR as a reference standard, the detection sensitivity, specificity, and overall coincidence rate of the immunochromatographic strip were 81.13%, 100%, and 90.00%. Additionally, the detection ability of the immunochromatographic strip was correlated with that of virus titration. The immunochromatographic strip was used to detect 183 clinical disease samples, and the average positive detection rate was 22.95%. In summary, this method has good sensitivity and specificity and is simple, convenient, and quick to operate. It has high application value for on-site diagnosis of PCV2 and virus quantification. KEY POINTS: • A red latex microsphere immunochromatographic strip for PCV2 detection was developed. • The method was not only simple to operate, but also takes less time. • The method had good sensitivity and specificity.

The Xiaogu San Attenuates Pain and Cartilage Damage in Rats with Monosodium Iodoacetate Induced Osteoarthritis.

BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease with an increasing incidence associated with increased life expectancy. The application of traditional Chinese medicine in the treatment of OA has become a research hotspot. OBJECTIVE: This study investigated the effects of XGS externally applied to osteoarthritic joints and analyze its effect on pain in monosodium iodoacetate (MIA)-induced OA rats. This study also evaluates potential mechanisms behind the anti-osteoarthritic effects of XGS. METHODS: A total of 24 Sprague Dawley rats were evenly and randomly divided into three separate groups, including the normal control (NC), OA and XGS groups. MIA (50 µL, 10 mg/mL) was injected into the left knee joints of the rats to induce OA. After 7 days, The rats of XGS group were given XGS (0.45 g) that was externally applied to the left knee joint, were fixed with gauze, and continuously administered XGS for 28 days. Morphological changes in tissues and organs were examined using H&E staining. Biochemical indicators were measured using an automatic biochemical analyzer. Inflammatory cytokines were detected using ELISA kits and immunohistochemistry. RNA-based high-throughput sequencing (RNA-seq) was performed to detect differential expression of mRNAs in normal and MIA-induced OA rats. RESULTS: Stride of the left leg was extended in rats, matrix increased on cartilage tissue surfaces, and inflammatory cytokines were reduced when treated with XGS. RNA-seq results revealed that the PI3K-Akt signaling pathway is activated in the OA model. The qRT-PCR showed that the expression levels of Tnn, Col6a6, Igf1 and Lamb1 were up-regulated by XGS. CONCLUSION: Altogether, this work demonstrated the potential therapeutic effects of XGS in rats with OA induced by MIA. The XGS may be considered an alternative therapy to manage OA.

A Routing Algorithm Based on Real-Time Information Traffic in Sparse Environment for VANETs.

Because of the specific characteristics, like high vehicular mobility, unstable topology, and interruption of inter-vehicle wireless communication, it is hard to make a perfect decision on packet forwarding in highly dynamic topology VANETs. Especially in a sparse urban environment, the poor connectivity of nodes will mostly cause problems such as data packet loss and routing redundancy. Therefore, how to choose the best relay node becomes a key challenge in the design of fast and reliable routing protocols. This paper presents real-time effective information traffic routing (RTEIT), which provides an optimal route for forwarding the data packets toward their destination when choosing the relay node. RTEIT introduces a new network parameter named effective information traffic which can estimate the connectivity of nodes by the path that has been successfully created. Moreover, for avoiding unexpected communication interruption, we propose a new formula to evaluate the status of the links via considering the speed, direction, and location information. Finally, the node utility, as the criterion of routing decision, is calculated by effective information traffic and link status. We use the simulator of SUMO and NS-3 platform to evaluate RTEIT, and the results are compared with GPSR MOPR, and MM-GPSR. The evaluation results demonstrate that RTEIT outperforms in terms of packet loss rate, end-to-end delay, and network yield.

Relative-path-based algorithm for link prediction on complex networks using a basic similarity factor.

Complex networks have found many applications in various fields. An important problem in theories of complex networks is to find factors that aid link prediction, which is needed for network reconstruction and to study network evolution mechanisms. Though current similarity-based algorithms study factors of common neighbors and local paths connecting a target node pair, they ignore factor information on paths between a node and its neighbors. Therefore, this paper first supposes that paths between nodes and neighbors provide basic similarity features. Accordingly, we propose a so-called relative-path-based method. This method utilizes factor information on paths between nodes and neighbors, besides paths between node pairs, in similarity calculation for link prediction. Furthermore, we solve the problem of determining the parameters in our algorithm as well as in other algorithms after a series of discoveries and validations. Experimental results on six disparate real networks demonstrate that the relative-path-based method can obtain greater prediction accuracy than other methods, as well as performance robustness.

MCSM-Wri: A Small-Scale Motion RecognitionMethod Using WiFi Based on Multi-ScaleConvolutional Neural Network.

environmental perception technology based onWiFi, and some state-of-the-art techniques haveemerged. The wide application of small-scale motion recognition has aroused people's concern.Handwritten letter is a kind of small scale motion, and the recognition for small-scale motion basedon WiFi has two characteristics. Small-scale action has little impact on WiFi signals changes inthe environment. The writing trajectories of certain uppercase letters are the same as the writingtrajectories of their corresponding lowercase letters, but they are different in size. These characteristicsbring challenges to small-scale motion recognition. The system for recognizing small-scale motion inmultiple classes with high accuracy urgently needs to be studied. Therefore, we propose MCSM-Wri,a device-free handwritten letter recognition system using WiFi, which leverages channel stateinformation (CSI) values extracted from WiFi packets to recognize handwritten letters, includinguppercase letters and lowercase letters. Firstly, we conducted data preproccessing to provide moreabundant information for recognition. Secondly, we proposed a ten-layers convolutional neuralnetwork (CNN) to solve the problem of the poor recognition due to small impact of small-scaleactions on environmental changes, and it also can solve the problem of identifying actions with thesame trajectory and different sizes by virtue of its multi-scale characteristics. Finally, we collected6240 instances for 52 kinds of handwritten letters from 6 volunteers. There are 3120 instances fromthe lab and 3120 instances are from the utility room. Using 10-fold cross-validation, the accuracyof MCSM-Wri is 95.31%, 96.68%, and 97.70% for the lab, the utility room, and the lab+utility room,respectively. Compared with Wi-Wri and SignFi, we increased the accuracy from 8.96% to 18.13% forrecognizing handwritten letters.

Similarity-based future common neighbors model for link prediction in complex networks.

Link prediction aims to predict the existence of unknown links via the network information. However, most similarity-based algorithms only utilize the current common neighbor information and cannot get high enough prediction accuracy in evolving networks. So this paper firstly defines the future common neighbors that can turn into the common neighbors in the future. To analyse whether the future common neighbors contribute to the current link prediction, we propose the similarity-based future common neighbors (SFCN) model for link prediction, which accurately locate all the future common neighbors besides the current common neighbors in networks and effectively measure their contributions. We also design and observe three MATLAB simulation experiments. The first experiment, which adjusts two parameter weights in the SFCN model, reveals that the future common neighbors make more contributions than the current common neighbors in complex networks. And two more experiments, which compares the SFCN model with eight algorithms in five networks, demonstrate that the SFCN model has higher accuracy and better performance robustness.

A Novel Joint Power and Feedback Bit Allocation Interference Alignment Scheme for Wireless Sensor Networks.

It is necessary to improve the energy efficiency of batteries in wireless sensor networks (WSNs). The multiple-input multiple-output (MIMO) technique has become an important means to ameliorate WSNs, and interference management is the core of improving energy efficiency. A promising approach is interference alignment (IA), which effectively reduces the interference and improves the throughput of a system in the MIMO interference channels. However, the IA scheme requires perfect channel state information (CSI) at all transceivers in practice, which results in considerable feedback overhead. Thus, limited IA feedback has attracted much attention. In this paper, we analyze the throughput loss of the K-user MIMO interference channels when each transmitter delivers multiple streams in one slot, and derives the upper-bound of the system interference leakage and throughput loss. Then, to reduce the interference leakage and throughput loss for the MIMO interference alignment with limited feedback, a joint power and feedback bit allocation optimization scheme is proposed. The simulation results show that, compared with the conventional schemes, the presented optimal scheme achieves less residual interference and better performance in the system throughput.

A Novel Modification of PSO Algorithm for SML Estimation of DOA.

This paper addresses the issue of reducing the computational complexity of Stochastic Maximum Likelihood (SML) estimation of Direction-of-Arrival (DOA). The SML algorithm is well-known for its high accuracy of DOA estimation in sensor array signal processing. However, its computational complexity is very high because the estimation of SML criteria is a multi-dimensional non-linear optimization problem. As a result, it is hard to apply the SML algorithm to real systems. The Particle Swarm Optimization (PSO) algorithm is considered as a rather efficient method for multi-dimensional non-linear optimization problems in DOA estimation. However, the conventional PSO algorithm suffers two defects, namely, too many particles and too many iteration times. Therefore, the computational complexity of SML estimation using conventional PSO algorithm is still a little high. To overcome these two defects and to reduce computational complexity further, this paper proposes a novel modification of the conventional PSO algorithm for SML estimation and we call it Joint-PSO algorithm. The core idea of the modification lies in that it uses the solution of Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT) and stochastic Cramer-Rao bound (CRB) to determine a novel initialization space. Since this initialization space is already close to the solution of SML, fewer particles and fewer iteration times are needed. As a result, the computational complexity can be greatly reduced. In simulation, we compare the proposed algorithm with the conventional PSO algorithm, the classic Altering Minimization (AM) algorithm and Genetic algorithm (GA). Simulation results show that our proposed algorithm is one of the most efficient solving algorithms and it shows great potential for the application of SML in real systems.

A Cooperative Downloading Method for VANET Using Distributed Fountain Code.

Cooperative downloading is one of the effective methods to improve the amount of downloaded data in vehicular ad hoc networking (VANET). However, the poor channel quality and short encounter time bring about a high packet loss rate, which decreases transmission efficiency and fails to satisfy the requirement of high quality of service (QoS) for some applications. Digital fountain code (DFC) can be utilized in the field of wireless communication to increase transmission efficiency. For cooperative forwarding, however, processing delay from frequent coding and decoding as well as single feedback mechanism using DFC cannot adapt to the environment of VANET. In this paper, a cooperative downloading method for VANET using concatenated DFC is proposed to solve the problems above. The source vehicle and cooperative vehicles encodes the raw data using hierarchical fountain code before they send to the client directly or indirectly. Although some packets may be lost, the client can recover the raw data, so long as it receives enough encoded packets. The method avoids data retransmission due to packet loss. Furthermore, the concatenated feedback mechanism in the method reduces the transmission delay effectively. Simulation results indicate the benefits of the proposed scheme in terms of increasing amount of downloaded data and data receiving rate.

A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks.

Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU) vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR) environments.

A population-based study of acquired bilateral nevus-of-Ota-like macules in Shanghai, China.

Acquired bilateral nevus-of-Ota-like macule (ABNOM) is a common skin dyspigmentation in Asian females. Although its clinical characteristics are well defined, its epidemiology and pathogenesis remain unclear. A large population-based cross-sectional study was conducted to determine the prevalence and risk factors of ABNOM. A total of 8,680 subjects (ages ranging from newborn to 99 years old; 54% female) were selected from urban areas in Shanghai, China, using a multistage sampling method. All participants (response rate=97%) were interviewed and examined for the presence of various pigmentary disorders by board-certified dermatologists. ABNOM was found in 2.5% of the study population (0.5% of males and 4.2% of females), and 90% of cases observed were female. In females, prevalence rose after the age of 15 years and sharply declined after the age of 50 years, with nearly half of the cases observed within ages 45-55 years (prevalence=8.5%). Age, contraceptive use, and sun exposure were independently associated with ABNOM. Women with ABNOM were less likely to have facial nevomelanocytic nevi and seborrheic keratoses. These findings indicate that sex hormone alteration and UV exposure may independently have an important role on the pathogenesis of ABNOM.