A Synopsis of Dicranum Hedw. (Dicranaceae, Bryophyta) in China, with Special References to Four Species Newly Reported and Re-Evaluation of Dicranum psathyrum Klazenga.

Dicranum Hedw. is a highly diverse and widely distributed genus within Dicranaceae. The species diversity and distribution of this genus in China, however, remain not well known. A new revision of Dicranum in China using morphological and molecular phylogenetic methods confirms that China has 39 species, including four newly reported species, D. bardunovii Tubanova & Ignatova, D. dispersum Engelmark, D. schljakovii Ignatova & Tubanova, and D. spadiceum J.E.Zetterst. Dicranum psathyrum Klazenga is transferred to Dicranoloma (Renauld) Renauld as a new synonym of Dicranoloma fragile Broth. Two species, Dicranum brevifolium (Lindb.) Lindb. and D. viride (Sull. & Lesq.) Lindb. are excluded from the bryoflora of China. A key to the Chinese Dicranum species is also provided. These results indicate an underestimation of the distribution range of numerous Dicranum species, underscoring the need for further in-depth investigations into the worldwide Dicranum diversity.

Measurement and spatio-temporal heterogeneity analysis of coupling coordination between development of digital economy and agricultural carbon emission performance.

The new development pattern has identified two key avenues for the sustained advancement of high-quality agricultural and rural development: digitalisation and low-carbon development. The measurement of the digital economy and the agricultural carbon emission performance, and their spatial and temporal heterogeneity, is a crucial step in promoting the spatial coordination and sustainable development of digitalisation and low-carbon agriculture. This paper employs the entropy value method, SBM model, and coupling coordination degree model to investigate the coupling coordination measurement and spatial-temporal heterogeneity of the performance of the digital economy and agricultural carbon emissions. The data used are provincial panel data from 2013 to 2021. The simulation results demonstrate that, between 2013 and 2021, the digital economy of all provinces exhibited varying degrees of growth, yet the development of the digital economy between provinces exhibited a more pronounced tendency to diverge. Concurrently, the agricultural carbon emission efficiency in China exhibited a fluctuating upward trend. The development of the digital economy and the efficiency of agricultural carbon emission were found to be highly coupled. Their coupling and coordination relationship showed a downward trend followed by an upward trend. In general, it is suggested that we should increase investment in digital economy infrastructure and technology, promote digital agricultural applications, strengthen policy guidance and financial support, establish a coupling coordination mechanism and strengthen farmers' digital literacy and environmental awareness.

Spatio-temporal heterogeneity of China's import and export trade, factors influencing it, and its implications for developing countries' trade.

This study constructed a multidimensional indicator system to evaluate spatio-temporal heterogeneity of China's import and export trade of 31 provinces from 2000 to 2022. This study describes the distribution of China's import and export trade by using location Gini coefficient and exploratory spatial analysis. Additionally, Multiple linear regression was used to ascertain the extent of contribution by various factors on the spatio-temporal heterogeneity of import and export trade. The simulation results show that inter-provincial import and export trade displayed distinct spatio-temporal differentiation characteristics with a prominent east-to-west disparity from 2000 to 2022. The trade links between various regions of the country have gradually strengthened, with a corresponding high correlation to the level of economic development. GDP, financial expenditure, freight transportation volume, technology market turnover, foreign investment, and disposable income of all residents, significantly influence the per capita export and import volume. In general, it is suggested that China and developing countries should take effective measures to promote balanced trade development, strengthen regional cooperation and coordination, and promote green trade and sustainable development.

Comparison of Flavonoid Content, Antioxidant Potential, Acetylcholinesterase Inhibition Activity and Volatile Components Based on HS-SPME-GC-MS of Different Parts from Matteuccia struthiopteris (L.) Todaro.

Matteuccia struthiopteris is one of the most globally consumed edible ferns and widely used in folk medicine. Reports mainly focus on young fronds and the rhizome which are common edible medicinal parts. However, there are few detailed reports on other parts. Therefore, the volatile components of different parts based on HS-SPME-GC-MS were identified, and total flavonoid contents, antioxidant activities and acetylcholinesterase inhibitory activities were compared in order to reveal the difference of volatile components and potential medicinal value of different parts. The results showed that total flavonoid contents, antioxidant activities and volatile components of different parts were obviously different. The crozier exhibited the strongest antioxidant activities, but only underground parts exhibited a dose-dependent inhibition potential against AChE. Common volatile compounds were furfural and 2-furancarboxaldehyde, 5-methyl-. In addition, it was found that some volatile components from adventitious root, trophophyll, sporophyll and petiole were important ingredients in food, cosmetics, industrial manufacturing and pharmaceutical applications.

The Necessity to Investigate In Vivo Fate of Nanoparticle-Loaded Dissolving Microneedles.

Transdermal drug delivery systems are rapidly gaining prominence and have found widespread application in the treatment of numerous diseases. However, they encounter the challenge of a low transdermal absorption rate. Microneedles can overcome the stratum corneum barrier to enhance the transdermal absorption rate. Among various types of microneedles, nanoparticle-loaded dissolving microneedles (DMNs) present a unique combination of advantages, leveraging the strengths of DMNs (high payload, good mechanical properties, and easy fabrication) and nanocarriers (satisfactory solubilization capacity and a controlled release profile). Consequently, they hold considerable clinical application potential in the precision medicine era. Despite this promise, no nanoparticle-loaded DMN products have been approved thus far. The lack of understanding regarding their in vivo fate represents a critical bottleneck impeding the clinical translation of relevant products. This review aims to elucidate the current research status of the in vivo fate of nanoparticle-loaded DMNs and elaborate the necessity to investigate the in vivo fate of nanoparticle-loaded DMNs from diverse aspects. Furthermore, it offers insights into potential entry points for research into the in vivo fate of nanoparticle-loaded DMNs, aiming to foster further advancements in this field.

Revisiting Computer-Aided Tuberculosis Diagnosis.

Tuberculosis (TB) is a major global health threat, causing millions of deaths annually. Although early diagnosis and treatment can greatly improve the chances of survival, it remains a major challenge, especially in developing countries. Recently, computer-aided tuberculosis diagnosis (CTD) using deep learning has shown promise, but progress is hindered by limited training data. To address this, we establish a large-scale dataset, namely the Tuberculosis X-ray (TBX11 K) dataset, which contains 11 200 chest X-ray (CXR) images with corresponding bounding box annotations for TB areas. This dataset enables the training of sophisticated detectors for high-quality CTD. Furthermore, we propose a strong baseline, SymFormer, for simultaneous CXR image classification and TB infection area detection. SymFormer incorporates Symmetric Search Attention (SymAttention) to tackle the bilateral symmetry property of CXR images for learning discriminative features. Since CXR images may not strictly adhere to the bilateral symmetry property, we also propose Symmetric Positional Encoding (SPE) to facilitate SymAttention through feature recalibration. To promote future research on CTD, we build a benchmark by introducing evaluation metrics, evaluating baseline models reformed from existing detectors, and running an online challenge. Experiments show that SymFormer achieves state-of-the-art performance on the TBX11 K dataset.

Preparation and In Vitro and In Vivo Evaluation of Rectal In Situ Gel of Meloxicam Hydroxypropyl-ß-cyclodextrin Inclusion Complex.

Meloxicam (MLX) is one of the most effective NSAIDs, but its poor water solubility and low bioavailability limit its clinical application. In this study, we designed a thermosensitive in situ gel of the hydroxypropyl-ß-cyclodextrin inclusion complex (MLX/HP-ß-CD-ISG) for rectal delivery to improve bioavailability. The best method for preparing MLX/HP-ß-CD was the saturated aqueous solution method. The optimal inclusion prescription was optimized using an orthogonal test, and the inclusion complex was evaluated via PXRD, SEM, FTIR and DSC. Then, MLX/HP-ß-CD-ISG was characterized regarding the gel properties, release in vitro, and pharmacokinetics in vivo. The inclusion rate of the inclusion complex obtained via the optimal preparation process was 90.32 ± 3.81%. The above four detection methods show that MLX is completely embedded in the HP-ß-CD cavity. The developed MLX/HP-ß-CD-ISG formulation has a suitable gelation temperature of 33.40 ± 0.17 °C, a gelation time of 57.33 ± 5.13 s, pH of 7.12 ± 0.05, good gelling ability and meets the requirements of rectal preparations. More importantly, MLX/HP-ß-CD-ISG significantly improved the absorption and bioavailability of MLX in rats, prolonging the rectal residence time without causing rectal irritation. This study suggests that the MLX/HP-ß-CD-ISG can have a wide application prospect with superior therapeutic benefits.

Neutrophil to lymphocyte ratio is associated with the epilepsy after primary intracerebral hemorrhage.

BACKGROUND: Post-stroke epilepsy (PSE) is one of the major sequelae of stroke. Inflammation has been implicated in the development of stroke. The study aimed to explore the relationship between neutrophil-to-lymphocyte ratio (NLR) levels and epilepsy in patients with primary intracerebral hemorrhage (ICH). METHODS: A retrospective study was performed on 1132 patients with first-time ICH. Blood samples were obtained at admission after ICH. Patients included in the study were classified into three groups according to NLR tertiles. Logistic regression was used to analyze the relationship between NLR levels and the occurrence of PSE. RESULTS: The occurrence of PSE was significantly correlated with NLR levels (r = 0.118, P < 0.001). Patients with PSE had higher NLR levels than those without PSE. After adjusting for potential confounders, high NLR was independently associated with an increased risk of PSE (OR = 1.861, 95% CI 1.032-3.355, P = 0.039). Neutrophil-to-lymphocyte ratio levels were independently associated with the occurrence of PSE in the poor functional outcome group, while this association was not significant in the favorable functional outcome group. The model (cortical involvement + hematoma volume + early seizures + NLR) showed good prognostic performance. CONCLUSION: High NLR at admission is associated with an increased risk of PSE, which suggests that NLR may play a role in risk stratification in patients with ICH.

[Physiological regulation of salicylic acid on Helianthus tubeuosus upon copper stress and root FTIR analysis].

Phytoremediation plays an important role in the treatment of heavy metal pollution in soil. In order to elucidate the mechanism of salicylic acid (SA) on copper absorption, seedlings from Xuzhou (with strong Cu-tolerance) and Weifang Helianthus tuberosus cultivars (with weak Cu-tolerance) were selected for pot culture experiments. 1 mmol/L SA was sprayed upon 300 mg/kg soil copper stress, and the photosynthesis, leaf antioxidant system, several essential mineral nutrients and the changes of root upon copper stress were analyzed to explore the mechanism of copper resistance. The results showed that Pn, Tr, Gs and Ci upon copper stress decreased significantly compared to the control group. Meanwhile, chlorophyll a, chlorophyll b and carotenoid decreased with significant increase in initial fluorescence (F0), maximum photochemical quantum yield of PSⅡ (Fv/Fm), electron transfer rate (ETR) and photochemical quenching coefficient (qP) content all decreased. The ascorbic acid (AsA) content was decreased, the glutathione (GSH) value was increased, the superoxide dismutase (SOD), catalase (CAT) and ascorbate peroxidase (APX) activity in the leaves were decreased, and the peroxidase (POD) activity was significantly increased. SA increased the Cu content in the ground and root system, and weakened the nutrient uptake capacity of K, Ca, Mg, and Zn in the root stem and leaves. Spray of exogenous SA can maintain the opening of leaf stomata, improve the adverse effect of copper on photosynthetic pigment and PSⅡ reaction center. Mediating the SOD and APX activity started the AsA-GSH cycle process, effectively regulated the antioxidant enzyme system in chrysanthemum taro, significantly reduced the copper content of all parts of the plant, and improved the ion exchange capacity in the body. External SA increased the content of the negative electric group on the root by changing the proportion of components in the root, promoted the absorption of mineral nutrient elements and the accumulation of osmoregulatory substances, strengthened the fixation effect of the root on metal copper, and avoided its massive accumulation in the H. tuberosus body, so as to alleviate the inhibitory effect of copper on plant growth. The study revealed the physiological regulation of SA upon copper stress, and provided a theoretical basis for planting H. tuberosus to repair soil copper pollution.

P2T: Pyramid Pooling Transformer for Scene Understanding.

Recently, the vision transformer has achieved great success by pushing the state-of-the-art of various vision tasks. One of the most challenging problems in the vision transformer is that the large sequence length of image tokens leads to high computational cost (quadratic complexity). A popular solution to this problem is to use a single pooling operation to reduce the sequence length. This paper considers how to improve existing vision transformers, where the pooled feature extracted by a single pooling operation seems less powerful. To this end, we note that pyramid pooling has been demonstrated to be effective in various vision tasks owing to its powerful ability in context abstraction. However, pyramid pooling has not been explored in backbone network design. To bridge this gap, we propose to adapt pyramid pooling to Multi-Head Self-Attention (MHSA) in the vision transformer, simultaneously reducing the sequence length and capturing powerful contextual features. Plugged with our pooling-based MHSA, we build a universal vision transformer backbone, dubbed Pyramid Pooling Transformer (P2T). Extensive experiments demonstrate that, when applied P2T as the backbone network, it shows substantial superiority in various vision tasks such as image classification, semantic segmentation, object detection, and instance segmentation, compared to previous CNN- and transformer-based networks. The code will be released at https://github.com/yuhuan-wu/P2T.

Preparation, In Vitro and In Vivo Evaluation of Nanoemulsion In Situ Gel for Transnasal Delivery of Traditional Chinese Medicine Volatile Oil from Ligusticum sinense Oliv.cv. Chaxiong.

Ischemic stroke is a difficult-to-treat brain disease that may be attributed to a limited therapeutic time window and lack of effective clinical drugs. Nasal-brain administration is characterized by low systemic toxicity and is a direct and non-invasive brain targeting route. Preliminary studies have shown that the volatile oil of Chaxiong (VOC) has an obvious anti-ischemic stroke effect. In this work, we designed a nanoemulsion thermosensitive in situ gel (VOC-NE-ISG) loaded with volatile oil of Chaxiong for ischemia via intranasal delivery to rat brain treatment of cerebral ischemic stroke. The developed VOC-NE-ISG formulation has a suitable particle size of 21.02 ± 0.25 nm and a zeta potential of -20.4 ± 1.47 mV, with good gelling ability and prolonged release of the five components of VOC. The results of in vivo pharmacokinetic studies and brain targeting studies showed that intranasal administration of VOC-NE-ISG could significantly improve the bioavailability and had excellent brain-targeting efficacy of nasal-to-brain delivery. In addition, the results of pharmacodynamics experiments showed that both VOC-NE and VOC-NE-ISG could reduce the neurological deficit score of model rats, reducing the size of cerebral infarction, with a significant effect on improving ischemic stroke. Overall, VOC-NE-ISG may be a promising intranasal nanomedicine for the effective treatment of ischemic stroke.

Jia-ga-song-tang protection against alcoholic liver and intestinal damage.

Gut-liver axis and cellular homeostasis play key roles in alcohol liver disease (ALD). Nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is a stress-sensitive guarantor of cellular homeostasis. We investigated whether the beneficial effects and underlying mechanisms of Jia-ga-song Tang (JGST) against ALD were associated with gut-liver axis and cellular homeostasis. A predictive network depicting the relationship between Jia-Ga-Song-Tang (JGST) and alcoholic liver disease (ALD) was designed by Network pharmacology. Next, 5% v/v Lieber-DeCarli alcohol liquid diet was used to establish the ALD. JGST protected the liver damage, repaired the intestines to alleviate the Two-hit on the liver, and balanced the cellular homeostasis. It was manifested in repairing the liver and intestinal pathological structure, reducing serum ALT, AST, and liver TG, TC, MDA, CAT, and increasing liver GSH, and intestine GSH-Px. JGST mainly inhibited the liver mRNA levels of HO-1, NQO1, GCLC, FASN, and PPARα and activated the intestinal mRNA levels of HO-1 and NQO1, while inhibiting the liver protein levels of HO-1, NQO1. Furthermore, LPS and LBP in the plasma and the expression of inflammatory factors such as IL-1ß, TNF-α, IL-6, TGFß1, CD14, and Myd88 were reduced after treatment to prove that JGST protects the liver from Two-hit. Ethanol was used to intervene in HepG2 and IEC-6 to establish an ALD cell model and treated by Germacrone, ML385, and TBHQ. repaired the intestinal barrier, and inhibited Nrf2 in IEC-6, but protect the HepG2 by activating Nrf2 to balance cellular homeostasis. Our results reinforce that JGST provides an effective protective method for alcoholic liver disease (ALD) by regulating Gut-liver axis and cellular homeostasis.

Dynamic genome evolution in a model fern.

The large size and complexity of most fern genomes have hampered efforts to elucidate fundamental aspects of fern biology and land plant evolution through genome-enabled research. Here we present a chromosomal genome assembly and associated methylome, transcriptome and metabolome analyses for the model fern species Ceratopteris richardii. The assembly reveals a history of remarkably dynamic genome evolution including rapid changes in genome content and structure following the most recent whole-genome duplication approximately 60 million years ago. These changes include massive gene loss, rampant tandem duplications and multiple horizontal gene transfers from bacteria, contributing to the diversification of defence-related gene families. The insertion of transposable elements into introns has led to the large size of the Ceratopteris genome and to exceptionally long genes relative to other plants. Gene family analyses indicate that genes directing seed development were co-opted from those controlling the development of fern sporangia, providing insights into seed plant evolution. Our findings and annotated genome assembly extend the utility of Ceratopteris as a model for investigating and teaching plant biology.

EDN: Salient Object Detection via Extremely-Downsampled Network.

Recent progress on salient object detection (SOD) mainly benefits from multi-scale learning, where the high-level and low-level features collaborate in locating salient objects and discovering fine details, respectively. However, most efforts are devoted to low-level feature learning by fusing multi-scale features or enhancing boundary representations. High-level features, which although have long proven effective for many other tasks, yet have been barely studied for SOD. In this paper, we tap into this gap and show that enhancing high-level features is essential for SOD as well. To this end, we introduce an Extremely-Downsampled Network (EDN), which employs an extreme downsampling technique to effectively learn a global view of the whole image, leading to accurate salient object localization. To accomplish better multi-level feature fusion, we construct the Scale-Correlated Pyramid Convolution (SCPC) to build an elegant decoder for recovering object details from the above extreme downsampling. Extensive experiments demonstrate that EDN achieves state-of-the-art performance with real-time speed. Our efficient EDN-Lite also achieves competitive performance with a speed of 316fps. Hence, this work is expected to spark some new thinking in SOD. Code is available at https://github.com/yuhuan-wu/EDN.

Leveraging Instance-, Image- and Dataset-Level Information for Weakly Supervised Instance Segmentation.

Weakly supervised semantic instance segmentation with only image-level supervision, instead of relying on expensive pixel-wise masks or bounding box annotations, is an important problem to alleviate the data-hungry nature of deep learning. In this article, we tackle this challenging problem by aggregating the image-level information of all training images into a large knowledge graph and exploiting semantic relationships from this graph. Specifically, our effort starts with some generic segment-based object proposals (SOP) without category priors. We propose a multiple instance learning (MIL) framework, which can be trained in an end-to-end manner using training images with image-level labels. For each proposal, this MIL framework can simultaneously compute probability distributions and category-aware semantic features, with which we can formulate a large undirected graph. The category of background is also included in this graph to remove the massive noisy object proposals. An optimal multi-way cut of this graph can thus assign a reliable category label to each proposal. The denoised SOP with assigned category labels can be viewed as pseudo instance segmentation of training images, which are used to train fully supervised models. The proposed approach achieves state-of-the-art performance for both weakly supervised instance segmentation and semantic segmentation. The code is available at https://github.com/yun-liu/LIID.

MobileSal: Extremely Efficient RGB-D Salient Object Detection.

The high computational cost of neural networks has prevented recent successes in RGB-D salient object detection (SOD) from benefiting real-world applications. Hence, this article introduces a novel network, MobileSal, which focuses on efficient RGB-D SOD using mobile networks for deep feature extraction. However, mobile networks are less powerful in feature representation than cumbersome networks. To this end, we observe that the depth information of color images can strengthen the feature representation related to SOD if leveraged properly. Therefore, we propose an implicit depth restoration (IDR) technique to strengthen the mobile networks' feature representation capability for RGB-D SOD. IDR is only adopted in the training phase and is omitted during testing, so it is computationally free. Besides, we propose compact pyramid refinement (CPR) for efficient multi-level feature aggregation to derive salient objects with clear boundaries. With IDR and CPR incorporated, MobileSal performs favorably against state-of-the-art methods on six challenging RGB-D SOD datasets with much faster speed (450fps for the input size of 320×320) and fewer parameters (6.5M). The code is released at https://mmcheng.net/mobilesal.

Genome-Wide Identification of the HMA Gene Family and Expression Analysis under Cd Stress in Barley.

In recent years, cadmium (Cd) pollution in soil has increased with increasing industrial activities, which has restricted crop growth and agricultural development. The heavy metal ATPase (HMA) gene family contributes to heavy metal stress resistance in plants. In this study, 21 HMA genes (HvHMAs) were identified in barley (Hordeumvulgare L., Hv) using bioinformatics methods. Based on phylogenetic analysis and domain distribution, barley HMA genes were divided into five groups (A-E), and complete analyses were performed in terms of physicochemical properties, structural characteristics, conserved domains, and chromosome localization. The expression pattern analysis showed that most HvHMA genes were expressed in barley and exhibited tissue specificity. According to the fragments per kilobase of exon per million fragments values in shoots from seedlings at the 10 cm shoot stage (LEA) and phylogenetic analysis, five HvHMA genes were selected for expression analysis under Cd stress. Among the five HvHMA genes, three (HvHMA1, HvHMA3, and HvHMA4) were upregulated and two (HvHMA2 and HvHMA6) were downregulated following Cd treatments. This study serves as a foundation for clarifying the functions of HvHMA proteins in the heavy metal stress resistance of barley.

H2A.B is a cancer/testis factor involved in the activation of ribosome biogenesis in Hodgkin lymphoma.

Testis-specific regulators of chromatin function are commonly ectopically expressed in human cancers, but their roles are poorly understood. Examination of 81 primary Hodgkin lymphoma (HL) samples showed that the ectopic expression of the eutherian testis-specific histone variant H2A.B is an inherent feature of HL. In experiments using two HL cell lines derived from different subtypes of HL, H2A.B knockdown inhibited cell proliferation. H2A.B was enriched in both nucleoli of these HL cell lines and primary HL samples. We found that H2A.B enhanced ribosomal DNA (rDNA) transcription, was enriched at the rDNA promoter and transcribed regions, and interacted with RNA Pol I. Depletion of H2A.B caused the loss of RNA Pol I from rDNA chromatin. Remarkably, H2A.B was also required for high levels of ribosomal protein gene expression being located at the transcriptional start site and within the gene body. H2A.B knockdown reduced gene body chromatin accessibility of active RNA Pol II genes concurrent with a decrease in transcription. Taken together, our data show that in HL H2A.B has acquired a new function, the ability to increase ribosome biogenesis.

Intrahepatic cholestasis induced by α-naphthylisothiocyanate can cause gut-liver axis disorders.

Clinical studies have shown that Intrahepatic cholestasis is closely related to intestinal injury. The gut-liver axis theory suggests that the intestine and liver are closely related, and that bile acids are important mediators linking the intestine and liver. We compared two cholestasis models: a single injection model that received a single subcutaneous ANIT injection (75 mg/kg), and a multiple subcutaneous injection model that received an injection of ANIT (50 mg/kg) every other day for 2 weeks. We used Transmetil (ademetionine 1,4-butanedisulfonate) to relieve intrahepatic cholestasis in the multiple injection group. In the multiple injection group, we found increased hepatic bile duct hyperplasia, increased fibrosis of the liver, increased small intestine inflammation and oxidative damage, increased harmful bile acids, decreased bile acids transporter levels. After treatment with Transmetil, the liver and gut injuries were relieved. These results suggest that intrahepatic cholestasis can cause disorders of the gut-liver axis.

Regularized Densely-Connected Pyramid Network for Salient Instance Segmentation.

Much of the recent efforts on salient object detection (SOD) have been devoted to producing accurate saliency maps without being aware of their instance labels. To this end, we propose a new pipeline for end-to-end salient instance segmentation (SIS) that predicts a class-agnostic mask for each detected salient instance. To better use the rich feature hierarchies in deep networks and enhance the side predictions, we propose the regularized dense connections, which attentively promote informative features and suppress non-informative ones from all feature pyramids. A novel multi-level RoIAlign based decoder is introduced to adaptively aggregate multi-level features for better mask predictions. Such strategies can be well-encapsulated into the Mask R-CNN pipeline. Extensive experiments on popular benchmarks demonstrate that our design significantly outperforms existing state-of-the-art competitors by 6.3% (58.6% vs. 52.3%) in terms of the AP metric. The code is available at https://github.com/yuhuan-wu/RDPNet.