Microfluidic chemistry assisted synthesis of cobalt quantum dot embedded nitrogen doped carbon with oxidase-like properties toward ascorbic acid detection.

Ascorbic acid (AA) is a powerful antioxidant in food safety and disease treatment. It is of great significance to develop a low-cost, high-stability, and easy-to-operate colorimetric method for quantitative detection of AA in food or human body. Although various nanozymes have been developed for the colorimetric detection of AA, the size regulation of the catalytic center of nanozymes remains a challenge. In this work, we propose a combined strategy of flow chemistry synthesis and pyrolysis to realize the controllable adjustment of the catalytic center size of nanozymes. Zinc-cobalt zeolitic imidazole frameworks (ZnCo-ZIFs) with different sizes are synthesized by flow chemistry. Nitrogen-doped carbon materials with different Co catalytic centers (80 nm-10 nm) are then obtained by pyrolysis of ZnCo-ZIFs precursors. Among them, cobalt quantum dot embedded nitrogen-doped carbon (Co QDs/N-C) exhibits excellent oxidase activity, with Vmax and Km of 4.19 × 10-7 M s-1 and 0.12 mM. Therefore, a simple, low-cost, and stable colorimetric method for the detection of AA is established with a good linear relationship (3-500 µM) and low detection limit (0.40 µM). This work has certain guiding significance for the size regulation of catalytic center of nanozyme, and the detection method has broad application prospects in biochemical sensing field.

Design and application of Cd2+ polypeptide fluorescent probes based on Aggregation Induced Emission (AIE).

Cadmium is a toxic heavy metal, which is both an environmental pollutant, and a threat to human health. A fluorescent probe was developed to detect Cd2+ selectively, sensitively, and quickly. This study reports the successful development of a polypeptide fluorescent probe TPE-HC (TPE-His-Pro-Gly-Cys) which selectively detects Cd2+ by Aggregation-Induced Emission effect. After fluorescence excitation, Cd2+ can be effectively detected based on the change of fluorescence intensity. The detection limit of Cd2+ in buffer solution was determined to be 151 nM (R2 = 0.9933). This probe exhibits high sensitivity, high cell permeabilit y, and low biological toxicity, and can perform live cell imaging under biological conditions. This study indicates that TPE-HC can detect Cd2+ in biological environments.

A new resorcylic acid lactone from the endophytic fungus Chaetosphaeronema sp.

A new 14-membered resorcylic acid lactone (RAL14), chaetolactone A (1), along with three known ones (2-4), was obtained from the fermentation of the soil-derived fungus Chaetosphaeronema sp. SSJZ001. Their structures were established based on extensive spectroscopic data analyses (UV, IR, HRESIMS, 1D, and 2D NMR),13C NMR chemical shifts calculations coupled with the DP4+ probability method, theoretical calculations of ECD spectra, as well as X-ray diffraction analysis. All compounds were evaluated for their cytotoxic effects against A549, HO-8910, and MCF-7 cell lines.

Diversity Patterns of Eukaryotic Phytoplankton in the Medog Section of the Yarlung Zangbo River.

As one of the important biodiversity conservation areas in China, the ecosystem in the lower reaches of the Yarlung Zangbo River is fragile, and is particularly sensitive to global changes. To reveal the diversity pattern of phytoplankton, the metabarcode sequencing was employed in the Medog section of the lower reaches of the Yarlung Zangbo River during autumn 2019 in present study. The phytoplankton assemblies can be significantly divided into the main stem and the tributaries; there are significant differences in the phytoplankton biomass, alpha and beta diversity between the main stem and the tributaries. While both the main stem and the tributaries are affected by dispersal limitation, the phytoplankton assemblages in the entire lower reaches are primarily influenced by heterogeneous selection. Community dissimilarity and assembly process were significantly correlated with turbidity, electrical conductivity, and nitrogen nutrition. The tributaries were the main source of the increase in phytoplankton diversity in the lower reaches of the Yarlung Zangbo River. Such diversity pattern of phytoplankton in the lower reach may be caused by the special habitat in Medog, that is, the excessive flow velocity, and the significant spatial heterogeneity in physical and chemical factors between stem and tributaries. Based on the results and conclusions obtained in present study, continuous long-term monitoring is essential to assess and quantify the impact of global changes on phytoplankton.

Quantitative comparison and evaluation between aerial and underground parts of Gentiana straminea through simultaneous determination of five major compounds by RP-HPLC.

Herbal Gentiana straminea Maxim. (Family Gentianaceae), "Ma Hua Jiao" in Chinese, is a commonly used Chinese medicine. Secoiridoids and flavonoids have been identified as the major active components of herbal medicines used in the treatment of hepatitis, rheumatism and many other diseases. It is the overharvesting of the roots of this plant for medicinal purposes that has led to a drastic decline in its population. In the present study, the above and below ground parts of Gentian Bitter Glycine were quantitatively compared and evaluated for the determination of the major active constituents. Five major compounds, loganic acid, swertiamarin, gentiopicroside, sweorside and isoorientin, were extracted by solvent extraction technique and analyzed by Reversed-phase High Performance Liquid Chromatography (RP-HPLC). By analysing the principal components and calculating the composite scores, the results show that the aboveground component in different areas ranked higher compared to the underground component, with the former being able to substitute to some extent for the latter's underground component. Finally, based on hierarchical cluster analysis, we identified the ideal natural growing region for aerial parts of G. straminea distributed on the Qinghai-Tibetan Plateau. The significance of this work is that we can balance the demand for herbs with environmental preservation by selectively picking the aerial parts, which can regrow next year, instead of removing the whole plant. It protects the fragile ecological environment of the Tibetan Plateau and is important for sustainable development.

Oleanane and 30-noroleanane triterpenoids from the roots of Paeonia lactiflora.

An investigation of EtOAc extract from the roots of Paeonia lactiflora yielded three new 30-noroleanane triterpenoids paeonenoides L-N (1-3) and one new oleanane triterpenoid paeonenoide O (4) together with 7 known compounds (5-11). Extensive spectrographic experiments were applied to identify the structures of 1-4, and their absolute configurations were unambiguously determined by theoretical calculations of ECD spectra, as well as the single-crystal X-ray diffraction analysis. Compounds 8, 9 and 10 were isolated from the Paeonia genus for the first time. Moreover, compounds 8, 9 and 11 showed inhibitory activities against LPS-induced nitric oxide (NO) production in RAW264.7 macrophages with the IC50 values of 72. 17 ± 4.74, 30.02 ± 2.03 and 28.34 ± 1.85 µM, respectively.

Effectiveness of opportunistic osteoporosis screening on chest CT using the DCNN model.

OBJECTIVE: To develop and evaluate a deep learning model based on chest CT that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images, and explore the feasibility and effectiveness of the model based on the lumbar 1 vertebral body alone. MATERIALS AND METHODS: The chest CT images of 1048 health check subjects from January 2021 to June were retrospectively collected as the internal dataset (the segmentation model: 548 for training, 100 for tuning and 400 for test. The classification model: 530 for training, 100 for validation and 418 for test set). The subjects were divided into three categories according to the quantitative CT measurements, namely, normal, osteopenia and osteoporosis. First, a deep learning-based segmentation model was constructed, and the dice similarity coefficient(DSC) was used to compare the consistency between the model and manual labelling. Then, two classification models were established, namely, (i) model 1 (fusion feature construction of lumbar vertebral bodies 1 and 2) and (ii) model 2 (feature construction of lumbar 1 alone). Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of the models, and the Delong test was used to compare the areas under the curve. RESULTS: When the number of images in the training set was 300, the DSC value was 0.951 ± 0.030 in the test set. The results showed that the model 1 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.990, 0.952 and 0.980; the model 2 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.983, 0.940 and 0.978. The Delong test showed that there was no significant difference in area under the curve (AUC) values between the osteopenia group and osteoporosis group (P = 0.210, 0.546), while the AUC value of normal model 2 was higher than that of model 1 (0.990 vs. 0.983, P = 0.033). CONCLUSION: This study proposed a chest CT deep learning model that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images. We further constructed the comparable model based on the lumbar 1 vertebra alone which can shorten the scan length, reduce the radiation dose received by patients, and reduce the training cost of technologists.

Ketogenic diet-produced ß-hydroxybutyric acid accumulates brain GABA and increases GABA/glutamate ratio to inhibit epilepsy.

Ketogenic diet (KD) alleviates refractory epilepsy and reduces seizures in children. However, the metabolic/cell biologic mechanisms by which the KD exerts its antiepileptic efficacy remain elusive. Herein, we report that KD-produced ß-hydroxybutyric acid (BHB) augments brain gamma-aminobutyric acid (GABA) and the GABA/glutamate ratio to inhibit epilepsy. The KD ameliorated pentetrazol-induced epilepsy in mice. Mechanistically, KD-produced BHB, but not other ketone bodies, inhibited HDAC1/HDAC2, increased H3K27 acetylation, and transcriptionally upregulated SIRT4 and glutamate decarboxylase 1 (GAD1). BHB-induced SIRT4 de-carbamylated and inactivated glutamate dehydrogenase to preserve glutamate for GABA synthesis, and GAD1 upregulation increased mouse brain GABA/glutamate ratio to inhibit neuron excitation. BHB administration in mice inhibited epilepsy induced by pentetrazol. BHB-mediated relief of epilepsy required high GABA level and GABA/glutamate ratio. These results identified BHB as the major antiepileptic metabolite of the KD and suggested that BHB may serve as an alternative and less toxic antiepileptic agent than KD.

Follicle stimulating hormone controls granulosa cell glutamine synthesis to regulate ovulation.

Polycystic ovary syndrome (PCOS) is the leading cause of anovulatory infertility. Inadequate understanding of the ovulation drivers hinders PCOS intervention. Herein, we report that follicle stimulating hormone (FSH) controls follicular fluid (FF) glutamine levels to determine ovulation. Murine ovulation starts from FF-exposing granulosa cell (GC) apoptosis. FF glutamine, which decreases in pre-ovulation porcine FF, elevates in PCOS patients FF. High-glutamine chow to elevate FF glutamine inhibits mouse GC apoptosis and induces hormonal, metabolic, and morphologic PCOS traits. Mechanistically, follicle-development-driving FSH promotes GC glutamine synthesis to elevate FF glutamine, which maintain follicle wall integrity by inhibiting GC apoptosis through inactivating ASK1-JNK apoptotic pathway. FSH and glutamine inhibit rapture of cultured murine follicles. Glutamine removal or ASK1-JNK pathway activation with metformin or AT-101 reversed PCOS traits in PCOS models that are induced with either glutamine or EsR1-KO. These suggest that glutamine, FSH and ASK1-JNK pathway are targetable to alleviate PCOS.

Risk factors and predicting nomogram for the clinical deterioration of non-severe community-acquired pneumonia.

BACKGROUND: Currently, there remains insufficient focus on non-severe community-acquired pneumonia (CAP) patients who are at risk of clinical deterioration, and there is also a dearth of research on the related risk factors. Early recognition of hospitalized patients at risk of clinical deterioration will be beneficial for their clinical management. METHOD: A retrospective study was conducted in The First Affiliated Hospital of Wenzhou Medical University, China, spanning from January 1, 2018 to April 30, 2022, and involving a total of 1,632 non-severe CAP patients. Based on whether their condition worsened within 72 h of admission, patients were divided into a clinical deterioration group and a non-clinical deterioration group. Additionally, all patients were randomly assigned to a training set containing 75% of patients and a validation set containing 25% of patients. In the training set, risk factors for clinical deterioration in patients with non-severe CAP were identified by using LASSO regression analysis and multivariate logistic regression analysis. A nomogram was developed based on identified risk factors. The effectiveness of the nomogram in both the training and validation sets was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). RESULTS: Age, body mass index (BMI), body temperature, cardiovascular comorbidity, respiratory rate, LDH level, lymphocyte count and D-dimer level were identified as risk factors associated with the clinical deterioration of non-severe CAP within 72 h of admission. The area under curve (AUC) value of the nomogram was 0.78 (95% CI: 0.74-0.82) in the training set and 0.75 (95% CI: 0.67-0.83) in the validation set. Furthermore, the calibration curves for both the training and validation sets indicated that the predicted probability of clinical deterioration aligned with the actual probability. Additionally, DCA revealed clinical utility for the nomogram at a specific threshold probability. CONCLUSION: The study successfully identified the risk factors linked to the clinical deterioration of non-severe CAP and constructed a nomogram for predicting the probability of deterioration. The nomogram demonstrated favorable predictive performance and has the potential to aid in the early identification and management of non-severe CAP patients at elevated risk of deterioration.

Ligand reaction-based fluorescent peptide probes for the detection of Cu2+ and glutathione.

Copper is a critical element in both human and animal metabolic processes. Its role includes supporting connective tissue cross-linking, as well as iron and lipid metabolism; at the same time, copper is also a toxic heavy metal that can cause harm to both the environment and human health. Glutathione (GSH) is a tripeptide composed of glutamic acid, cysteine, and glycine combined with sulfhydryl groups. Its properties include acting as an antioxidant and facilitating integrative detoxification. GSH is present in both plant and animal cells and has a fundamental role in maintaining living organisms. GSH is the most abundant thiol antioxidant in the human body. It exists in reduced and oxidized forms within cells and provides significant biochemical functions, such as regulating vitamins such as vitamins D, E, and C, and facilitating detoxification. A fluorescent probe has been developed to detect copper ions selectively, sensitively, and rapidly. This report outlines the successful work on creating a peptide probe, TGN (TPE-Trp-Pro-Gly-Cln-His-NH2 ), with specific Cu2+ detection capabilities, and a significant fluorescence recovery occurred with the addition of GSH. This indicates that the probe can detect Cu2+ and GSH concurrently. The detection limit for Cu2+ in the buffer solution was 264 nM (R2 = 0.9992), and the detection limit for GSH using the TGN-Cu2+ complex was 919 nM (R2 = 0.9917). The probe exhibits high cell permeability and low biotoxicity that make it ideal for live cell imaging in biological conditions. This peptide probe has the capability to detect Cu2+ and GSH in biological cells.

Reduced Graphene Oxide/Cellulose Sodium Aerogel-Supported Eutectic Phase Change Material Gel Demonstrating Superior Energy Conversion and Storage Capacity toward High-Performance Personal Thermal Management.

By virtue of their capacity to absorb and release energy during the phase change process, phase change materials (PCMs) are ideal for personal thermal management (PTM). The combination of reduced graphene oxide/cellulose sodium aerogel (rGCA) and lauric acid/myristic acid binary eutectic phase change gel (LMG) creates a composite phase change material that possesses outstanding photothermal conversion capabilities, electro-thermal conversion capabilities, energy storage capabilities, and shape-stable performance. The results showed that rGCA had a maximum adsorption efficiency of 99.7% with a melting latent heat of 124.6 J g-1. The high absorption rate of rGCA to LMG is a result of the capillary force, pore characteristics, hydrogen bonding, and the π-π interaction. Notably, rGCA and LMG composite material (rGCG) exhibited an excellent photothermal conversion efficiency of 96.5% and electro-thermal conversion of 82.3%. Results indicate that binary eutectic phase change materials are more suitable for temperature regulation than single phase change materials, making them more suitable for PTM. It is anticipated that the innovative thermal comfort solution, which provides thermal shielding, thermal energy storage, self-supporting characteristics, and wearability, will offer new possibilities for the next generation of wearable PTMs.

DeepmdQCT: A multitask network with domain invariant features and comprehensive attention mechanism for quantitative computer tomography diagnosis of osteoporosis.

In the medical field, the application of machine learning technology in the automatic diagnosis and monitoring of osteoporosis often faces challenges related to domain adaptation in drug therapy research. The existing neural networks used for the diagnosis of osteoporosis may experience a decrease in model performance when applied to new data domains due to changes in radiation dose and equipment. To address this issue, in this study, we propose a new method for multi domain diagnostic and quantitative computed tomography (QCT) images, called DeepmdQCT. This method adopts a domain invariant feature strategy and integrates a comprehensive attention mechanism to guide the fusion of global and local features, effectively improving the diagnostic performance of multi domain CT images. We conducted experimental evaluations on a self-created OQCT dataset, and the results showed that for dose domain images, the average accuracy reached 91%, while for device domain images, the accuracy reached 90.5%. our method successfully estimated bone density values, with a fit of 0.95 to the gold standard. Our method not only achieved high accuracy in CT images in the dose and equipment fields, but also successfully estimated key bone density values, which is crucial for evaluating the effectiveness of osteoporosis drug treatment. In addition, we validated the effectiveness of our architecture in feature extraction using three publicly available datasets. We also encourage the application of the DeepmdQCT method to a wider range of medical image analysis fields to improve the performance of multi-domain images.

Hypoxia induces mitochondrial protein lactylation to limit oxidative phosphorylation.

Oxidative phosphorylation (OXPHOS) consumes oxygen to produce ATP. However, the mechanism that balances OXPHOS activity and intracellular oxygen availability remains elusive. Here, we report that mitochondrial protein lactylation is induced by intracellular hypoxia to constrain OXPHOS. We show that mitochondrial alanyl-tRNA synthetase (AARS2) is a protein lysine lactyltransferase, whose proteasomal degradation is enhanced by proline 377 hydroxylation catalyzed by the oxygen-sensing hydroxylase PHD2. Hypoxia induces AARS2 accumulation to lactylate PDHA1 lysine 336 in the pyruvate dehydrogenase complex and carnitine palmitoyltransferase 2 (CPT2) lysine 457/8, inactivating both enzymes and inhibiting OXPHOS by limiting acetyl-CoA influx from pyruvate and fatty acid oxidation, respectively. PDHA1 and CPT2 lactylation can be reversed by SIRT3 to activate OXPHOS. In mouse muscle cells, lactylation is induced by lactate oxidation-induced intracellular hypoxia during exercise to constrain high-intensity endurance running exhaustion time, which can be increased or decreased by decreasing or increasing lactylation levels, respectively. Our results reveal that mitochondrial protein lactylation integrates intracellular hypoxia and lactate signals to regulate OXPHOS.

Saccharina japonica Ethanol Extract Ameliorates Dextran Sulfate Sodium-Induced Colitis via Reshaping Intestinal Microenvironment and Alleviating Inflammatory Response.

Saccharina japonica belongs to brown macro-alga with various potential health benefits; its antioxidant and anti-inflammatory activities indicate the potential to improve inflammatory bowel diseases. Here, the potential anti-colitis effect of Saccharina japonica extract (SJE) was evaluated on dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in C57B/L6 mice. The mice were treated with mesalazine (MES) and various doses of SJE by gavage for 14 days. Results showed that both MES and SJE treatment decreased the disease activity index scores, relieving the short colon. SJE increased the occludin and zonula occludens-1 levels, and the beneficial effects were better than MES. MES and SJE exerted similar effects in decreasing inflammatory cytokines and oxidative stress. Moreover, SJE reshaped the intestinal microbiota by increasing α-diversity and reducing plenty of harmful bacteria. Dietary SJE was significant to relieving the reduction in short-chain fatty acids. The results revealed the protective effect of SJE on colitis and potential mechanisms, which is important for the rational use of SJE in UC prevention.

End to End Multitask Joint Learning Model for Osteoporosis Classification in CT Images.

Osteoporosis is a significant global health concern that can be difficult to detect early due to a lack of symptoms. At present, the examination of osteoporosis depends mainly on methods containing dual-energyX-ray, quantitative CT, etc., which are high costs in terms of equipment and human time. Therefore, a more efficient and economical method is urgently needed for diagnosing osteoporosis. With the development of deep learning, automatic diagnosis models for various diseases have been proposed. However, the establishment of these models generally requires images with only lesion areas, and annotating the lesion areas is time-consuming. To address this challenge, we propose a joint learning framework for osteoporosis diagnosis that combines localization, segmentation, and classification to enhance diagnostic accuracy. Our method includes a boundary heat map regression branch for thinning segmentation and a gated convolution module for adjusting context features in the classification module. We also integrate segmentation and classification features and propose a feature fusion module to adjust the weight of different levels of vertebrae. We trained our model on a self-built dataset and achieved an overall accuracy rate of 93.3% for the three label categories (normal, osteopenia, and osteoporosis) in the testing datasets. The area under the curve for the normal category is 0.973; for the osteopenia category, it is 0.965; and for the osteoporosis category, it is 0.985. Our method provides a promising alternative for the diagnosis of osteoporosis at present.

Massive Fabrication of Flexible, Form-Stable, and Self-Repairing Brine Phase Change Material Gels toward Smart Cold Chain Logistics.

Cold chain logistics plays an extremely important role in the storage and transportation of perishable products. Nowadays, phase change materials (PCMs) have been applied in emerging cold chain logistics to overcome the problems of low stability, high energy consumption, and high cost in mechanical refrigeration-based cold chain logistics. Mass production of high-performance phase change cold storage materials toward cold chain logistics is still a major challenge. Herein, self-repairing brine phase change gels (BPCMGs) massively fabricated by ionic cross-linking, covalent cross-linking, and hydrogen bond cross-linking are proposed. Brine containing 23.3% sodium chloride (NaCl) is selected as the phase change component because its phase change temperature is suitable for the cold storage demand of aquatic products. The proposed BPCMGs demonstrate superior thermophysical properties in terms of no phase separation, no supercooling, high form stability, high latent heat, high thermal conductivity, high cyclic stability, and high self-repairing rate. Meanwhile, the BPCMGs present high cost-effectiveness. Given these advantages, BPCMGs are utilized to assemble smart cold storage equipment for the storage and transportation of aquatic products. The cold storage time reaches 36.73 h for aquatic products when the stored cold energy is 364078 J. The location and temperature of the refrigerated products are monitored in real-time. The state-of-the-art BPCMGs provide diversified possibilities for the advanced smart cold chain.

[Mn/Al-layered Double Oxide-loaded Biochar Reduced the Toxic Effects of Heavy Metals on Ryegrass in Soil].

The combined pollution of heavy metal Cu and Cd in soil induced by the e-waste dismantling process has become a severe problem. To deal with this issue, crab shell biochar (BC) and Mn/Al-layered double oxide-loaded crab shell biochar (LDO/BC) were prepared using coprecipitation and co-pyrolysis of discarded crab shells and manganese aluminum salt. The experimental results showed that not only were the soil pH, available phosphorus, available potassium, and soil enzymatic activity enhanced, but the contents of DTPA-Cu and DTPA-Cd in the soil were also reduced after remediation by BC and LDO/BC. Microbial community analysis indicated that BC-1% could promote the relative abundance of Gemmatimonadota and Acidobacteriota; meanwhile, LDO/BC-1% could promote the relative abundance of Proteobacteria, which could reduce the accumulation of Cd in plants. Ryegrass was planted for further investigating the toxic effect of heavy metals in soil after remediation. The results demonstrated that after remediating with BC-5% and LDO/BC-1%, ryegrass grew more vigorously and with a lower content of the heavy metals Cu and Cd in the plants than that of CK, and the germination rate increased by 29% and 60%, respectively. Further, LDO/BC-1% had a more excellent remediation performance than that of the other groups, and the Mn in LDO/BC could reduce the content of heavy metal Cd adsorbed by ryegrass in soil.

Sb-doped FeOCl nanozyme-based biosensor for highly sensitive colorimetric detection of glutathione.

Nanozymes have been emerging as substitutes for natural enzymes to construct biosensors towards biomolecular detection. However, the detection of glutathione (GSH) by nanozyme-based biosensors still remains a great challenge for research on catalytic activity enhancement and the detection mechanism. In this work, Sb-doped iron oxychloride (Sb-FeOCl) with a well-defined nanorod-like structure is prepared by high-temperature calcination. Sb-FeOCl nanorods have high peroxidase-like activity, which can catalyze the decomposition of H2O2 into ·OH and then oxidize 3,3',5,5'-tetramethylbenzidine (TMB). In view of these intriguing observations, a reliable colorimetric method with a simple mixing and detection strategy is developed for the detection of GSH. The linear range of GSH detection is 1-36 µM. The detection limit of GSH reaches a low level of 0.495 µM (3σ/slope). The GSH sensing system also exhibits excellent specificity and anti-interference. Taking advantage of the advantages of the Sb-FeOCl nanorod-based biosensor, it can be used to quantitatively detect GSH levels in human serum. It can be anticipated that the Sb-FeOCl nanorods have broad prospects in the field of enzymatic biochemical reactions.