Exploring the multifaceted role of GCN1: Implications in cellular responses and disease pathogenesis.

GCN1 is a highly conserved protein present widely across eukaryotes. As an upstream activator of protein kinase GCN2, GCN1 plays a pivotal role in integrated stress responses, such as amino acid starvation and oxidative stress. Through interaction with GCN2, GCN1 facilitates the activation of GCN2, thus initiating downstream signaling cascades in response to cellular stressors. In these contexts, the activation of GCN2 necessitates the presence and action of GCN1. Notably, GCN1 also operates as a ribosome collision sensor, contributing significantly to the translation quality control pathway. These discoveries offer valuable insights into cellular responses to internal stresses, vital for maintaining cellular homeostasis. Additionally, GCN1 exhibits the ability to regulate the cell cycle and suppress inflammation, among other processes, independently of GCN2. Our review outlines the structural characteristics and biological functions of GCN1, shedding light on its significant involvement in the onset and progression of various cancer and non-cancer diseases. Our work underscores the role of GCN1 in the context of drug therapeutic effects, hinting at its potential as a promising drug target. Furthermore, our work delves deep into the functional mechanisms of GCN1, promising innovative avenues for the diagnosis and treatment of diseases in the future. The exploration of GCN1's multifaceted roles not only enhances our understanding of its mechanisms but also paves the way for novel therapeutic interventions. The ongoing quest to unveil additional functions of GCN1 holds the promise of further enriching our comprehension of its mode of action.

Cuproptosis-associated ncRNAs predict breast cancer subtypes.

BACKGROUND: Cuproptosis is a novel copper-dependent mode of cell death that has recently been discovered. The relationship between Cuproptosis-related ncRNAs and breast cancer subtypes, however, remains to be studied. METHODS: The aim of this study was to construct a breast cancer subtype prediction model associated with Cuproptosis. This model could be used to determine the subtype of breast cancer patients. To achieve this aim, 21 Cuproptosis-related genes were obtained from published articles and correlation analysis was performed with ncRNAs differentially expressed in breast cancer. Random forest algorithms were subsequently utilized to select important ncRNAs and build breast cancer subtype prediction models. RESULTS: A total of 94 ncRNAs significantly associated with Cuproptosis were obtained and the top five essential features were chosen to build a predictive model. These five biomarkers were differentially expressed in the five breast cancer subtypes and were closely associated with immune infiltration, RNA modification, and angiogenesis. CONCLUSION: The random forest model constructed based on Cuproptosis-related ncRNAs was able to accurately predict breast cancer subtypes, providing a new direction for the study of clinical therapeutic targets.

Disulfidptosis-associated lncRNAs predict breast cancer subtypes.

Disulfidptosis is a newly discovered mode of cell death. However, its relationship with breast cancer subtypes remains unclear. In this study, we aimed to construct a disulfidptosis-associated breast cancer subtype prediction model. We obtained 19 disulfidptosis-related genes from published articles and performed correlation analysis with lncRNAs differentially expressed in breast cancer. We then used the random forest algorithm to select important lncRNAs and establish a breast cancer subtype prediction model. We identified 132 lncRNAs significantly associated with disulfidptosis (FDR < 0.01, |R|> 0.15) and selected the first four important lncRNAs to build a prediction model (training set AUC = 0.992). The model accurately predicted breast cancer subtypes (test set AUC = 0.842). Among the key lncRNAs, LINC02188 had the highest expression in the Basal subtype, while LINC01488 and GATA3-AS1 had the lowest expression in Basal. In the Her2 subtype, LINC00511 had the highest expression level compared to other key lncRNAs. GATA3-AS1 had the highest expression in LumA and LumB subtypes, while LINC00511 had the lowest expression in these subtypes. In the Normal subtype, GATA3-AS1 had the highest expression level compared to other key lncRNAs. Our study also found that key lncRNAs were closely related to RNA methylation modification and angiogenesis (FDR < 0.05, |R|> 0.1), as well as immune infiltrating cells (P.adj < 0.01, |R|> 0.1). Our random forest model based on disulfidptosis-related lncRNAs can accurately predict breast cancer subtypes and provide a new direction for research on clinical therapeutic targets for breast cancer.

Rice pest identification based on multi-scale double-branch GAN-ResNet.

Rice production is crucial to the food security of all human beings, and how rice pests and diseases can be effectively prevented in and timely detected is a hotspot issue in the field of smart agriculture. Deep learning has become the preferred method for rice pest identification due to its excellent performance, especially in the aspect of autonomous learning of image features. However, in the natural environment, the dataset is too small and vulnerable to the complex background, which easily leads to problems such as overfitting, and too difficult to extract the fine features during the process of training. To solve the above problems, a Multi-Scale Dual-branch structural rice pest identification model based on a generative adversarial network and improved ResNet was proposed. Based on the ResNet model, the ConvNeXt residual block was introduced to optimize the calculation ratio of the residual blocks, and the double-branch structure was constructed to extract disease features of different sizes in the input disease images, which it adjusts the size of the convolution kernel of each branch. In the complex natural environment, data pre-processing methods such as random brightness and motion blur, and data enhancement methods such as mirroring, cropping, and scaling were used to allow the dataset of 5,932 rice disease images captured from the natural environment to be expanded to 20,000 by the dataset in this paper. The new model was trained on the new dataset to identify four common rice diseases. The experimental results showed that the recognition accuracy of the new rice pest recognition model, which was proposed for the first time, improved by 2.66% compared with the original ResNet model. Under the same experimental conditions, the new model had the best performance when compared with classical networks such as AlexNet, VGG, DenseNet, ResNet, and Transformer, and its recognition accuracy could be as high as 99.34%. The model has good generalization ability and excellent robustness, which solves the current problems in rice pest identification, such as the data set is too small and easy to lead to overfitting, and the picture background is difficult to extract disease features, and greatly improves the recognition accuracy of the model by using a multi-scale double branch structure. It provides a superior solution for crop pest and disease identification.

Recent advances in plant disease severity assessment using convolutional neural networks.

In modern agricultural production, the severity of diseases is an important factor that directly affects the yield and quality of plants. In order to effectively monitor and control the entire production process of plants, not only the type of disease, but also the severity of the disease must be clarified. In recent years, deep learning for plant disease species identification has been widely used. In particular, the application of convolutional neural network (CNN) to plant disease images has made breakthrough progress. However, there are relatively few studies on disease severity assessment. The group first traced the prevailing views of existing disease researchers to provide criteria for grading the severity of plant diseases. Then, depending on the network architecture, this study outlined 16 studies on CNN-based plant disease severity assessment in terms of classical CNN frameworks, improved CNN architectures and CNN-based segmentation networks, and provided a detailed comparative analysis of the advantages and disadvantages of each. Common methods for acquiring datasets and performance evaluation metrics for CNN models were investigated. Finally, this study discussed the major challenges faced by CNN-based plant disease severity assessment methods in practical applications, and provided feasible research ideas and possible solutions to address these challenges.

ZNF655 accelerates progression of pancreatic cancer by promoting the binding of E2F1 and CDK1.

Pancreatic cancer has an extremely terrible prognosis and is a common cause of cancer death. In this study, the clinic value, biological function and underlying mechanisms of Zinc finger protein 655 (ZNF655) in human pancreatic cancer were evaluated. The expression level of ZNF655 in pancreatic cancer was determined by immunohistochemistry (IHC) staining. The biological effects of ZNF655 in pancreatic cancer cells was investigated by loss/gain-of-function assays in vitro and in vivo. The downstream molecular mechanism of ZNF655 was explored using co-immunoprecipitation (Co-IP), dual-luciferase reporter and chromatin immunoprecipitation (Ch-IP). ZNF655 expression was significantly elevated in human pancreatic cancer and possessed clinical value in predicting poor prognosis. Functionally, ZNF655 knockdown inhibited the biological progression of pancreatic cancer cells, which was characterized by weaken proliferation, enhanced apoptosis, arrested cell cycle in G2, impeded migration, and suppressed tumor growth. Mechanistically, ZNF655 played an important role in promoting the binding of E2F transcription factor 1 (E2F1) to the cyclin-dependent kinase 1 (CDK1) promoter. Furthermore, knockdown of CDK1 alleviated the promoting effects of ZNF655 overexpression in pancreatic cancer cells. The promotive role of ZNF655 in pancreatic cancer via CDK1 was determined, which drew further interest regarding its clinical application as a promising therapeutic target.

Time-Course Transcriptome Analysis of Lungs From Mice Infected With Hypervirulent Klebsiella pneumoniae via Aerosolized Intratracheal Inoculation.

Hypervirulent Klebsiella pneumoniae (hvKp) can cause life-threatening community-acquired infections among healthy young individuals and is thus of concern for global dissemination. In this study, a mouse model of acute primary hvKp pneumonia was established via aerosolized intratracheal (i.t.) inoculation, laying the foundation for conducting extensive studies related to hvKp. Subsequently, a time-course transcriptional profile was created of the lungs from the mouse model at 0, 12, 24, 48 and 60 hours post-infection (hpi) using RNA Sequencing (RNA-Seq). RNA-Seq data were analyzed with the use of Mfuzz time clustering, weighted gene co-expression network analysis (WGCNA) and Immune Cell Abundance Identifier for mouse (ImmuCellAI-mouse). A gradual change in the transcriptional profile of the lungs was observed that reflected expected disease progression. At 12 hpi, genes related to acute phase inflammatory response increased in expression and lipid metabolism appeared to have a pro-inflammatory effect. At 24 hpi, exacerbation of inflammation was observed and active IFN-γ suggested that signaling promoted activation and recruitment of macrophages occurred. Genes related to maintaining the structural integrity of lung tissues showed a sustained decrease in expression after infection and the decrease was especially marked at 48 hpi. TNF, IL-17, MAPK and NF-kB signaling pathways may play key roles in the immunopathogenesis mechanism at all stages of infection. Natural killer (NK) cells consistently decreased in abundance after infection, which has rarely been reported in hvKp infection and could provide a new target for treatment. Genes Saa1 and Slpi were significantly upregulated during infection. Both Saa1, which is associated with lipopolysaccharide (LPS) that elicits host inflammatory response, and Slpi, which encodes an antimicrobial protein, have not previously been reported in hvKp infections and could be important targets for subsequent studies. To t our knowledge, this paper represents the first study to investigate the pulmonary transcriptional response to hvKp infection. The results provide new insights into the molecular mechanisms underlying the pathogenesis of hvKp pulmonary infection that can contribute to the development of therapies to reduce hvKp pneumonia.

An experimental method for efficiently evaluating the size-resolved sampling efficiency of liquid-absorption aerosol samplers.

Aerosol samplers are critical tools for studying indoor and outdoor aerosols. Development and evaluation of samplers is often labor-intensive and time-consuming due to the need to use monodisperse aerosols spanning a range of sizes. This study develops a rapid experimental methodology using polydisperse solid aerosols to evaluate size-resolved aerosol-to-aerosol (AtoA) and aerosol-to-hydrosol (AtoH) sampling efficiencies. Arizona Test Dust (diameter 0.5-20 µm) was generated and dispersed into an aerosol test chamber and two candidate samplers were tested. For the AtoA test, aerosols upstream and downstream of a sampler were measured using an online aerodynamic particle sizer. For the AtoH test, aerosols collected in sampling medium were mixed with a reference sample and then measured by the laser diffraction method. The experimental methodology were validated as an impressive time-saving procedure, with reasonable spatial uniformity and time stability of aerosols in the test chamber and an acceptable accuracy of absolute mass quantification of collected particles. Evaluation results showed that the AGI-30 and the BioSampler sampler had similar size-resolved sampling efficiencies and that efficiencies decreased with decreasing sampling flow rate. The combined evaluation of AtoA and AtoH efficiency provided more comprehensive performance indicators than either test alone. The experimental methodology presented here can facilitate the design and choice of aerosol sampler.

Complete Protection Against Yersinia pestis in BALB/c Mouse Model Elicited by Immunization With Inhalable Formulations of rF1-V10 Fusion Protein via Aerosolized Intratracheal Inoculation.

Pneumonic plague, caused by Yersinia pestis, is an infectious disease with high mortality rates unless treated early with antibiotics. Currently, no FDA-approved vaccine against plague is available for human use. The capsular antigen F1, the low-calcium-response V antigen (LcrV), and the recombinant fusion protein (rF1-LcrV) of Y. pestis are leading subunit vaccine candidates under intense investigation; however, the inability of recombinant antigens to provide complete protection against pneumonic plague in animal models remains a significant concern. In this study, we compared immunoprotection against pneumonic plague provided by rF1, rV10 (a truncation of LcrV), and rF1-V10, and vaccinations delivered via aerosolized intratracheal (i.t.) inoculation or subcutaneous (s.c.) injection. We further considered three vaccine formulations: conventional liquid, dry powder produced by spray freeze drying, or dry powder reconstituted in PBS. The main findings are: (i) rF1-V10 immunization with any formulation via i.t. or s.c. routes conferred 100% protection against Y. pestis i.t. infection; (ii) rF1 or rV10 immunization using i.t. delivery provided significantly stronger protection than rF1 or rV10 immunization via s.c. delivery; and (iii) powder formulations of subunit vaccines induced immune responses and provided protection equivalent to those elicited by unprocessed liquid formulations of vaccines. Our data indicate that immunization with a powder formulation of rF1-V10 vaccines via an i.t. route may be a promising vaccination strategy for providing protective immunity against pneumonic plague.

The effect of ultrasound-guided intraperitoneal injection of ulinastatin on lung development in intrauterine growth-restricted fetal rabbits.

OBJECTIVES: To investigate the effect and mechanism of ulinastatin (UTI) on development of lungs in fetal rabbits with intrauterine growth retardation (IUGR). METHODS: Twenty pregnant rabbits were equally divided into normal, IUGR, UTI, and LY groups. The normal group was only injected with saline and marked with tattoo ink. IUGR models were established by injecting N-nitro-L-arginine methyl ester in the rabbits of IUGR, UTI, and LY groups. The three groups were injected with saline, UTI, or UTI + LY294002 (PI3K inhibitor) respectively, and then marked with tattoo ink. After cesarean section, neonatal weights, and levels of dipalmitoyl phosphatidylcholine (DPPC), nitric oxide (NO), P-Akt, P-eNOS, and pulmonary surfactant-associated protein A (SP-A) were determined in tissues of the lungs. Radial alveoli count (RAC), pulmonary interstitial ratio, and ultrastructural changes in type II alveolar epithelial cells (AEC II) were also determined through light and electron microscopy. RESULTS: Compared with control, the IUGR group showed significantly decreased weight, RAC, lamellar bodies in AEC II, and levels of P-Akt, P-eNOS, DPPC, NO, and SP-A, and increased pulmonary interstitial ratio (p < .05). The UTI treatment did not affect the weight; however, all other parameters were opposite to those observed in the IUGR group (p < .05). Furthermore, these UTI-mediated changes were inhibited by LY294002. CONCLUSIONS: Intraperitoneal UTI injection can promote the development of lungs and increase pulmonary surfactant production in IUGR fetal rabbits, potentially by activating PI3K/Akt/eNOS/NO signaling.

Role of apolipoprotein E in suppressing oxidative stress in gestational diabetes mellitus patients and mouse model.

OBJECTIVE: To address the relationship between apolipoprotein E (ApoE) and oxidative stress in gestational diabetes mellitus (GDM). METHODS: Fifty pregnant women diagnosed with GDM and normal pregnant women were recruited separately and their blood and placental tissue were collected. Western blot assay, qRT-PCR assay and ELISA were used to detect the expression levels of ApoE and other oxidative stress factors in these samples. ApoE-/- mice with a C57BL/6J background were used to evaluate the relationship between ApoE deficiency and oxidative stress during GDM. RESULTS: Serum and placental ApoE were both down-regulated in GDM patients (serum: 45.25 ± 19.27 µg/ml for GDM and 96.34 ± 24.05 µg/ml for control; placental: 14.49 ± 6.52 ng/mg tissue for GDM and 48.76 ± 13.59 ng/mg tissue for control). There was a statistical correlation between placental ApoE level and oxidative stress in GDM (r = -0.4904 with MDA, -0.4258 with NO, 0.4476 with SOD, 0.6316 with GSH). ApoE deficiency exacerbated blood glucose, insulin anomaly and oxidative stress in placenta in GDM mouse models. Placental Apo E deficiency correlates to oxidative stress in GDM. CONCLUSION: In conclusion, we innovatively revealed the relationship between ApoE and GDM oxidative stress among GDM patients in this study.

Ultrasound Characteristics of Cystadenofibromas: A Retrospective Multicenter Study.

ABSTRACT: Cystadenofibromas (CAFs) are relatively rare benign ovarian tumors. This study was to describe the ultrasound (US) findings of CAFs. Preoperative US information of 86 CAFs was retrospectively collected. To better illustrate their characteristic, 173 cystadenomas (CADs), 103 borderline ovarian tumors (BOTs), and 129 cystadenocarcinomas (CACs) were recruited as match groups. Besides morphology evaluation, tumors were categorized by the Ovarian-Adnexal Reporting and Data System US system. Higher-risk stratification in CAFs was more often being seen than CADs (63% of CAFs classified as Ovarian-Adnexal Reporting and Data System 4 or 5 vs 35% in CADs). Cystadenofibromas more commonly appeared as unilocular or multilocular solid than CADs. Solid components presented in 59% of CAFs and papillary projections presented in 45%. More CAFs contained solid components and papillary projections than CADs (P < 0.0001). When compared with BOTs and CACs, less CAFs contained solid components (P < 0.017 and P < 0.0001). However, no significant difference was found in CAFs versus BOTs or CACs about the presence of papillary projections. Shadowing was identified in 58% of CAFs; however, in CADs, BOTs, and CACs, the proportion was 2%, 11%, and 11%, respectively. Presence of shadowing in CAFs was noticeably more than CADs, BOTs, and CACs (P < 0.017 or P < 0.0001). Similar to CADs, most CAFs were avascular (76%) and without ascites (99%), which were significantly different from BOTs and CACs. We concluded that the sonographic markers for CAFs that differ from malignant were presence of shadowing, avascular, and absence of ascites.

Synthesis of polyethylene glycol functional bonded silica gel for selective recognition and separation of α-cyclodextrin.

In this work, we for the first time synthesized the polyethylene glycol (PEG) bonded silica gel via KH-560 as a silane coupling reagent for column chromatography by a solid/liquid surface continuous reaction method. The molecular interaction, structure, morphology, and thermostability was characterized by fourier transform infrared spectroscopy (FTIR), elemental analysis (EA), scanning electronic microscope (SEM) and thermogravimetric analysis (TGA). Given that PEG is capable to self-assemble with α-CD, the PEG bonded silica gel was used as packing of column chromatography to achieve the selective separation of α-cyclodextrin (α-CD) at room temperature and atmospheric pressure. The bonded silica gel column could realize the effective separation of α-CD in the enzymatic hydrolysis mixture, which provides support for industrial separation of α-CD.

Microcystic pattern and shadowing are independent predictors of ovarian borderline tumors and cystadenofibromas in ultrasound.

OBJECTIVES: To determine the sonographic characteristics of borderline tumors (BoTs) and cystadenofibromas (CAFs). METHODS: Preoperative sonograms from consecutive patients who had at least one primary epithelial tumor in the adnexa were retrospectively collected. All tumors were described using the International Ovarian Tumor Analysis terminology. Ultrasound variables were tested using multinomial logistic regression after univariate analysis. RESULTS: A total of 650 patients were included in this study. Of these, 110 had a CAF, 128 had a BoT, 249 had a cystadenoma (CAD), and 163 had a cystadenocarcinoma (CAC). Nearly half of CAFs and more than half of BoTs and CACs appeared to be unilocular and multilocular solid on the ultrasound images, while CADs were predominantly uni- or multilocular (p < 0.001). Overall, shadowing was identified in 82/650 cases. Sixty-five of 110 (59.1%) CAFs exhibited an acoustic shadow, compared with only 4/249 (1.6%) in CADs, 7/128 (5.5%) in BoTs, and 6/163 (3.7%) in CACs (p < 0.001). Furthermore, 112/650 cases demonstrated microcystic pattern (MCP). Sixty-eight of 128 (53.1%) BoTs exhibited MCP, compared with only 5/249 (2.0%) in CADs, 19/163 (11.7%) in CACs, and 20/110 (18.2%) in CAFs (p < 0.001). Logistic regression analysis revealed that shadowing is an independent predictor of CAFs, while MCP is an independent predictor of BoTs. CONCLUSIONS: Sonographic findings for CAFs and BoTs were complex and partly overlapped with those for CACs. However, proper recognition and utilization of shadowing or MCP may help to correctly discriminate CAFs and BoTs. KEY POINTS: • Sonographic findings for borderline tumors and cystadenofibromas are complex and mimic malignancy. • Microcystic pattern and shadowing are independent predictors of borderline tumors and cystadenofibromas respectively.

Omega-3 fatty acids reduce post-operative risk of deep vein thrombosis and pulmonary embolism after surgery for elderly patients with proximal femoral fractures: a randomized placebo-controlled, double-blind clinical trial.

BACKGROUND: Elderly patients with proximal femoral fractures face elevated risk of post-operative deep vein thrombosis and pulmonary embolism, due to the lack of suitable treatment plans after surgery and hospital discharge. This study aimed to investigate the effect of omega-3 fatty acid supplementation in the above-described clinical setting. METHODS: Five hundred and seven elderly patients (> 60 years of age) suffering from proximal femoral fractures were recruited. After exclusion, 452 eligible patients were assigned in a random manner to receive either omega-3 fatty acids at the daily dose of 1000 mg or placebo, via oral administration for a period of 30 days after surgery. At the end of intervention, the incidences of pulmonary embolism, deep vein thrombosis, and other related complications were compared between the two study groups. RESULTS: Incidences of pulmonary embolism as well as deep vein thrombosis, including events leading to fatality, were significantly reduced by the 30-day omega-3 fatty acid intervention. But other related complications, such as haematoma evacuation, post-operative wound bleed, wound infection with frank pus, and other bleed events that required transfusion, were not affected after omega-3 fatty acid consumption. CONCLUSION: Daily supplementation of omega-3 fatty acids decreases the risk of pulmonary embolism as well as symptomatic deep vein thrombosis, after surgery among elderly patients with proximal femoral fractures, without causing elevated risk of bleeding episodes.

[Effect of beryllium on the morphology and chemical elements of cell membrane of Porphyromonas gingivalis].

PURPOSE: To evaluate the effect of beryllium (Be²âº) on the morphology and chemical elements on cell membrane of Porphyromonas gingivalis (P. gingivalis), thus to explore the microbiologic mechanisms of periodontal diseases. METHODS: P. gingivalis was put into the culture with different Be²âº concentrations and anaerobically cultured for 24 hours. The morphologic change of P. gingivalis was observed under microscope and scanning electronic microscope (SEM), and chemical elements of cell membrane were observed by X-ray energy dispersion spectrum (EDS). The data was statistically analyzed with SPSS13.0 software package. RESULTS: The morphology of P.gingivalis altered obviously at the concentration greater than 2.5 mg/L, which was manifested by the sharpness of border and depression on the surface. With the increased concentration of beryllium, the Na and Ca peak descended on the surface of P. gingivalis. CONCLUSIONS: Beryllium can interfere with the morphology of P. gingivalis, and lead to the changes of chemical elements on cell membrane of P. gingivalis, which may result in a disturbance in the microecologic balance of subgingival microbes and eventually contribute to periodontal diseases.

A complete hierarchical key management scheme for heterogeneous wireless sensor networks.

Heterogeneous cluster-based wireless sensor networks (WSN) attracted increasing attention recently. Obviously, the clustering makes the entire networks hierarchical; thus, several kinds of keys are required for hierarchical network topology. However, most existing key management schemes for it place more emphasis on pairwise key management schemes or key predistribution schemes and neglect the property of hierarchy. In this paper, we propose a complete hierarchical key management scheme which only utilizes symmetric cryptographic algorithms and low cost operations for heterogeneous cluster-based WSN. Our scheme considers four kinds of keys, which are an individual key, a cluster key, a master key, and pairwise keys, for each sensor node. Finally, the analysis and experiments demonstrate that the proposed scheme is secure and efficient; thus, it is suitable for heterogeneous cluster-based WSN.

A secure RFID authentication protocol adopting error correction code.

RFID technology has become popular in many applications; however, most of the RFID products lack security related functionality due to the hardware limitation of the low-cost RFID tags. In this paper, we propose a lightweight mutual authentication protocol adopting error correction code for RFID. Besides, we also propose an advanced version of our protocol to provide key updating. Based on the secrecy of shared keys, the reader and the tag can establish a mutual authenticity relationship. Further analysis of the protocol showed that it also satisfies integrity, forward secrecy, anonymity, and untraceability. Compared with other lightweight protocols, the proposed protocol provides stronger resistance to tracing attacks, compromising attacks and replay attacks. We also compare our protocol with previous works in terms of performance.