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Recent researches on long noncoding RNAs (lncRNAs) have expanded our horizon of gene regulation and the cellular complexity. However, the number, characteristics and expression patterns of lncRNAs remain poorly characterized and how these lncRNAs biogenesis are regulated in response to drought stress in cotton are still largely unclear. In the study, using a reproducibility-based RNA-sequencing and bioinformatics strategy to analyze the lncRNAs of 9 samples under three different environment stresses (control, drought stress and re-watering, three replications), we totally identified 10,820 lncRNAs of high-confidence through five strict steps filtration, of which 9,989 were lincRNAs, 153 were inronic lncRNAs, 678 were anti-sense lncRNAs. Coding function analysis showed 6,470 lncRNAs may have the ability to code proteins. Small RNAs precursor analysis revealed that 196 lncRNAs may be the precursors to small RNAs, most of which (35.7%, 70) were miRNAs. Expression patterns analysis showed that most of lncRNAs were expressed at a low level and most inronic lncRNAs (75.95%) had a consistent expression pattern with their adjacent protein-coding genes. Further analysis of transcriptome data uncovered that lncRNAs XLOC_063105 and XLOC_115463 probably function in regulating two adjacent coding genes CotAD_37096 and CotAD_12502, respectively. Investigations of the content of plant hormones and proteomics analysis under drought stress also complemented the prediction. We analyzed the characteristics and the expression patterns of lncRNAs under drought stress and re-watering treatment, and found lncRNAs may be likely to involve in regulating plant hormones pathway in response to drought stress.

As one of the cash crops, cotton is facing the threat of abiotic stress during its growth and development. It has been reported that melatonin is involved in plant defense against salt stress, but whether melatonin can improve cotton salt tolerance and its molecular mechanism remain unclear. We investigated the role of melatonin in cotton salt tolerance by silencing melatonin synthesis gene and exogenous melatonin application in upland cotton. In this study, applicating of melatonin can improve salt tolerance of cotton seedlings. The content of endogenous melatonin was different in cotton varieties with different salt tolerance. The inhibition of melatonin biosynthesis related genes and endogenous melatonin content in cotton resulted in the decrease of antioxidant enzyme activity, Ca 2+ content and salt tolerance of cotton. To explore the protective mechanism of exogenous melatonin against salt stress by RNA-seq analysis. Melatonin played an important role in the resistance of cotton to salt stress, improved the salt tolerance of cotton by regulating antioxidant enzymes, transcription factors, plant hormones, signal molecules and Ca 2+ signal transduction. This study proposed a regulatory network for melatonin to regulate cotton’s response to salt stress, which provided a theoretical basis for improving cotton’s salt tolerance.

Background Cotton ( Gossypium hirsutum ) is considered a fairly salt tolerant crop however, salinity can still cause significant economic losses by affecting the yield and deteriorating the fiber quality. We studied a salt-tolerant upland cotton cultivar under temporal salt stress to unfold the salt tolerance molecular mechanisms. Biochemical response to salt stress (400 mM) was measured at 0 h, 3 h, 12 h, 24 h and 48 h post stress intervals and single-molecule long-read sequencing technology from Pacific Biosciences (PacBio) combined with the unique molecular identifiers approach was used to identify differentially expressed genes (DEG). Results Antioxidant enzymes including, catalase (CAT), peroxidase (POD), superoxide dismutase (SOD) were found significantly induced under temporal salt stress, suggesting that reactive oxygen species scavenging antioxidant machinery is an essential component of salt tolerance mechanism in cotton. We identified a wealth of novel transcripts based on the PacBio long reads sequencing approach. Prolonged salt stress duration induces high number of DEGs. Significant numbers of DEGs were found under key terms related to stress pathways such as “response to oxidative stress”, “response to salt stress”, “response to water deprivation”, “cation transport”, “metal ion transport”, “superoxide dismutase”, and “reductase”. Key DEGs related to hormone (abscisic acid, ethylene and jasmonic acid) biosynthesis, ion homeostasis (CBL-interacting serine/threonine-protein kinase genes, calcium-binding proteins, potassium transporter genes, potassium channel genes, sodium/hydrogen exchanger or antiporter genes), antioxidant activity (POD, SOD, CAT, glutathione reductase), transcription factors (myeloblastosis , WRKY , Apetala 2) and cell wall modification were found highly active in response to salt stress in cotton. Expression fold change of these DEGs showed both positive and negative responses, highlighting the complex nature of salt stress tolerance mechanisms in cotton. Conclusion Collectively, this study provides a good insight into the regulatory mechanism under salt stress in cotton and lays the foundation for further improvement of salt stress tolerance.

Background Cotton is an important industrial crop and a pioneer crop for saline-alkali land restoration. However, the molecular mechanism underlying the cotton response to salt is not completely understood. Methods Here, we used metabolome data and transcriptome data to analyze the salt tolerance regulatory network of cotton and metabolic biomarkers. Results In this study, cotton was stressed at 400 m M NaCl for 0 h, 3 h, 24 h and 48 h. NaCl interfered with cotton gene expression, altered metabolite contents and affected plant growth. Metabolome analysis showed that NaCl stress increased the contents of amino acids, sugars and ABA, decreased the amount of vitamin and terpenoids. K-means cluster analysis of differentially expressed genes showed that the continuously up-regulated genes were mainly enriched in metabolic pathways such as flavonoid biosynthesis and amino acid biosynthesis. Conclusion The four metabolites of cysteine (Cys), ABA(Abscisic acid), turanose, and isopentenyladenine-7-N-glucoside (IP7G) were consistently up-regulated under salt stress, which may indicate that they are potential candidates for cotton under salt stress biomarkers. Combined transcriptome and metabolome analysis revealed accumulation of cysteine, ABA, isopentenyladenine-7-N-glucoside and turanose were important for salt tolerance in cotton mechanism. These results will provide some metabolic insights and key metabolite biomarkers for salt stress tolerance, which may help to understanding of the metabolite response to salt stress in cotton and develop a foundation for cotton to grow better in saline soil.

Background DNA methylation, with a cryptic role in genome stability, gene transcription and expression, is involved in the drought response process in plants, but the complex regulatory mechanism is still largely unknown. Results Here, we performed whole-genome bisulfite sequencing (WGBS) and identified long non-coding RNAs on cotton leaves under drought stress and re-watering treatments. We obtained 31,223 and 30,997 differentially methylated regions (representing 2.48% of the genome) after drought stress and re-watering treatments, respectively. Our data also showed that three sequence contexts, including m CpG, m CHG, m CHH, all presented a hyper-methylation pattern under drought stress and were nearly restored to normal levels after the re-watering treatment. Among all the methylation variations, asymmetric CHH methylation was the most consistent with external environments, suggesting that methylation/demethylation in a CHH context may constitute a novel epigenetic modification in response to drought stress. Combined with the targets of long non-coding RNAs, we found that long non-coding RNAs may mediate variations in methylation patterns by splicing into microRNAs. Furthermore, the many hormone-related genes with methylation variations suggested that plant hormones might be a potential mechanism in the drought response. Conclusions Future crop-improvement strategies may benefit by taking into account not only the DNA genetic variations in cotton varieties but also the epigenetic modifications of the genome.

Anxiety disorders are highly prevalent psychiatric conditions that impair quality of life and daily functioning. Despite the availability of pharmacological and psychotherapeutic treatments, limitations such as suboptimal efficacy, adverse effects, and high relapse rates remain unresolved. Traditional Chinese Medicine (TCM) has emerged as a complementary approach, yet its theoretical complexity and lack of standardized evidence hinder broader clinical integration. This review provides a comprehensive synthesis of the role of TCM in the management of anxiety disorders, covering classical theories, epidemiological features, diagnostic principles, therapeutic strategies, and modern innovations. It outlines the pathogenesis of anxiety from a TCM perspective, including syndrome types such as liver Qi stagnation and heart-spleen deficiency, and discusses personalized treatment modalities such as herbal prescriptions, acupuncture, and five-element music therapy. Importantly, it highlights advances in TCM standardization through data mining, integration with metabolomics and neuroimaging, and emerging tools for objective evaluation, such as fNIRS. Clinical trials suggest that TCM interventions may achieve comparable or superior symptom control with fewer adverse effects than conventional treatments. This review offers a structured reference for clinicians and researchers aiming to understand the evolving role of TCM in anxiety management and its potential contribution to future integrative care models.

Developing highly porous and conductive carbon electrodes is crucial for high-performance electrochemical double-layer capacitors. We provide a method for preparing supercapacitor electrode materials using zeolitic imidazolate framework-8 (ZIF-8)-coated wood fibers. The material has high nitrogen (N)-doping content and a specific surface area of 593.52 m2 g−1. When used as a supercapacitor electrode, the composite exhibits a high specific capacitance of 270.74 F g−1, with an excellent capacitance retention rate of 98.4% after 10,000 cycles. The symmetrical supercapacitors (SSCs) with two carbon fiber electrodes (CWFZ2) showed a high power density of 2272.73 W kg−1 (at an energy density of 2.46 W h kg−1) and an energy density of 4.15 Wh kg−1 (at a power density of 113.64 W kg−1). Moreover, the SSCs maintained 81.21% of the initial capacitance after 10,000 cycles at a current density of 10 A g−1, which proves that the SSCs have good cycle stability. The excellent capacitance performance is primarily attributed to the high conductivity and N source provided by the zeolite imidazole framework. Because of this carbon material’s unique structural features and N-doping, our obtained CWFZ2 electrode material could be a candidate for high-performance supercapacitor electrode materials.

Upland cotton (Gossypium hirsutum L.), an important source of natural fiber, can tolerate relatively high salinity and drought stresses. In the present study, a plasma membrane Na+/H+ antiporter gene, GhSOS1, was cloned from a salt-tolerant genotype of G. hirsutum, Zhong 9807. The expression level of GhSOS1 in cotton roots was significantly upregulated in the presence of high concentrations of NaCl (200 mM), while its transcript abundance was increased when exposed to low temperature and drought stresses. Localization analysis using onion epidermal cells showed that the GhSOS1 protein was localized to the plasma membrane. The overexpression of GhSOS1 in Arabidopsis enhanced tolerance to salt stress, as indicated by a lower MDA content and decreased Na+/K+ ratio in transgenic plants. Moreover, the transcript levels of stress-related genes were significantly higher in GhSOS1 overexpression lines than in wild-type plants under salt treatment. Hence, GhSOS1 may be a potential target gene for enhancing salt tolerance in transgenic plants.

The Lagrangian vortex method has the advantage of producing highly detailed simulations of fluids such as turbulent smoke. However, this method has two problems: the construction of the velocity field from the vorticity field is inefficient, and handling the boundary condition is difficult. We present a pure Lagrangian vortex method, including a nested grid to accelerate the construction of the velocity field, and a novel boundary treatment method for the vorticity field. Based on a tree structure, the nested grid algorithm considerably improves the efficiency of the velocity computation while producing visual results that are comparable with the original flow. Based on the vortex-generating method, the least square method is used to compute the vorticity strength of the new vortex elements. Further, we consider the mutual influence between the generated vortex particles. We demonstrate our method’s benefits by using a vortex ring and various examples of interaction between the smoke and obstacles.

In this study, we propose a real-time ship anomaly detection method driven by Automatic Identification System (AIS) data. The method uses ship trajectory clustering classes as a normal model and a deep learning algorithm as an anomaly detection tool. The method is divided into three main steps: (1) quality maintenance of the original AIS data, (2) extraction of normal ship trajectory clusters using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), in which a segmented improved Dynamic Time Warping (DTW) algorithm is used to measure the degree of trajectory similarity, (3) the clustering results are used as a normative model to train a Bi-directional Gated Recurrent Unit (BiGRU) recurrent neural network, which is used as a trajectory predictor to achieve real-time ship anomaly detection. Experiments were conducted using real AIS data from the port of Tianjin, China. The experimental results are manifold. Firstly, the data pre-processing process effectively improves the quality of raw AIS data. Secondly, the ship trajectory clustering model can accurately classify the traffic flow of different modes in the sea area. Moreover, the trajectory prediction result of the BiGRU model has the smallest error with the actual ship trajectory and has a better trajectory prediction performance compared with the Long Short-Term Memory Network model (LSTM) and Gated Recurrent Unit (GRU). In the final anomaly detection experiment, the detection accuracy and timeliness of the BiGRU model are also higher than LSTM and GRU. Therefore, the proposed method can achieve effective and timely detection of ship anomalous behaviors in terms of position, heading and speed during ship navigation, which provides insight to enhance the intelligence of marine traffic supervision and improve the safety of marine navigation.