Determination of optimal NH4+/K + concentration and corresponding ratio critical for growth of tobacco seedlings in a hydroponic system

Inherently, ammonium (NH4+) is critical for plant growth; however, its toxicity suppresses potassium (K+) uptake and vice-versa. Hence, attaining a nutritional balance between these two ions (NH4+ and K+) becomes imperative for the growth of tobacco seedlings. Therefore, we conducted a 15-day experimental study on tobacco seedlings exposed to different concentrations (47 treatments) of NH4+/K+ at different corresponding 12 ratios simultaneously in a hydroponic system. Our study aimed at establishing the optimal NH4+-K+ concentration and the corresponding ratio required for optimal growth of different tobacco plant organs during the seedling stage. The controls were the baseline for comparison in this study. Plants with low or excessive NH4+-K+ concentration had leaf chlorosis or dark greenish colouration, stunted whole plant part biomass, and thin roots. We found that adequate K+ supply is a pragmatic way to mitigate NH4+-induced toxicity in tobacco plants. The optimal growth for tobacco leaf and root was attained at NH4+-K+ concentrations 2-2 mM (ratio 1:1), whereas stem growth was optimal at NH4+-K+ 1-2 mM (1:2). The study provided an insight into the right combination of NH4+/K+ that could mitigate or prevent NH4+ or K+ stress in the tobacco seedlings

Prognostic value and immune-infiltration pattern of FOXD3-AS1 in patients with glioma

Gliomas are difficult-to-treat brain tumors due to their aggressive nature, rapid proliferation, and high invasiveness (Zhang et al., J Cell Biochem, 2019, 120 (9), 15106–15118; Ge et al., Int J Biochem Cell Biol, 2021, 139, 106054). FOXD3-AS1 has been identified as an emerging potential target for tumor prediction and treatment in many studies (Qin et al., Front Oncol, 2021, 11, 688027). However, the utility of FOXD3-AS1 has not been reported in glioma patients (Li et al., Cancer Manag Res, 2021, 13, 9037–9048). The differential profiles of FOXD3-AS1 in TCGA–GBMLGG database were analyzed across clinical subgroups. The analysis of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) revealed that a high level of FOXD3-AS1 was associated with a poor prognosis and survival outcome. Based on the Cox regression analysis, FOXD3-AS1 was found to be a high-risk factor for glioma that affects prognosis outcomes independently. More importantly, because oxidative stress is closely linked to glioma prognosis, we focused on the potential mechanisms of six oxidative stress co-expressed genes with FOXD3-AS1. In addition, the predictive value of FOXD3-AS1 was determined for each clinical subgroup status. The ROC curve results showed that FOXD3-AS1 had a good predictive performance. A stratified clinicopathological subgroup analysis revealed that high expression of FOXD3-AS1 is associated with a poor prognosis. This also indicates a link between FOXD3-AS1 and tumorigenesis and prognosis, which has potential application value. Furthermore, the immune cell infiltration of FOXD3-AS1 and the signal marker correlation suggested that immune cell infiltration differed significantly between immune cell subsets. To the best of our knowledge, this is the first report to investigate FOXD3-AS1 in glioma and how it may modulate GBM and LGG immune microenvironments. Furthermore, FOXD3-AS1 was detected in tumor and paraneoplastic tissues using RT–qPCR. Transwell analysis verified the migration and invasion of the FOXD3-AS1 knockout group in vitro to a certain extent. In conclusion, FOXD3-AS1 can be used as a prognostic indicator for GBM and LGG, and it is closely related to immune infiltration and response to oxidative stress, which may contribute to the advancement of glioma immunotherapy research

Changes in the mental health status of the general Chinese population during the COVID-19 pandemic: A longitudinal study

The study is based on a longitudinal evaluation of the public, during the initial COVID-19 outbreak in China and 8 months after. It aimed to explore the changes in the mental health of the public at the beginning of the pandemic and during the regular epidemic prevention and control. An online survey questionnaire was used to collect data during the initial COVID-19 outbreak (February 10, 2020–February 18, 2020; T1) and 8 months after the outbreak (October 21, 2020–December 29, 2020; T2). Psychological distress was assessed using the Patient Health Questionnaire-9 (PHQ-9), Self-rating Anxiety Scale (SAS), and Post-traumatic Stress Disorder Checklist (PCL-5). A chi-square test was used to compare the changes in the depression and anxiety scores at T1 and T2, and the correlation between symptoms was analyzed through Spearman's rank correlation. In T1, 1,200 people were recruited, while 168 people responded in T2. Depression (48.2–31.0%; p=0.001) and anxiety (17.9–9.5%; p = 0.026) symptoms decreased over time; two participants developed post-traumatic stress disorder (PTSD) in T2. The scores of the PHQ-9 scale and the SAS scale were both positively correlated with the score of the PCL-5 scale and negatively correlated with sleep time. During the COVID-19 pandemic, part of the general population's anxiety and depression significantly reduced with time, and they rarely developed PTSD. PTSD occurrence was related to severe depression and anxiety

A Companion Cell–Dominant and Developmentally Regulated H3K4 Demethylase Controls Flowering Time in Arabidopsis via the Repression of FLC Expression

Flowering time relies on the integration of intrinsic developmental cues and environmental signals. FLC and its downstream target FT are key players in the floral transition in Arabidopsis. Here, we characterized the expression pattern and function of JMJ18, a novel JmjC domain-containing histone H3K4 demethylase gene in Arabidopsis. JMJ18 was dominantly expressed in companion cells; its temporal expression pattern was negatively and positively correlated with that of FLC and FT, respectively, during vegetative development. Mutations in JMJ18 resulted in a weak late-flowering phenotype, while JMJ18 overexpressors exhibited an obvious early-flowering phenotype. JMJ18 displayed demethylase activity toward H3K4me3 and H3K4me2, and bound FLC chromatin directly. The levels of H3K4me3 and H3K4me2 in chromatins of FLC clade genes and the expression of FLC clade genes were reduced, whereas FT expression was induced and the protein expression of FT increased in JMJ18 overexpressor lines. The early-flowering phenotype caused by the overexpression of JMJ18 was mainly dependent on the functional FT. Our findings suggest that the companion cell–dominant and developmentally regulated JMJ18 binds directly to the FLC locus, reducing the level of H3K4 methylation in FLC chromatin and repressing the expression of FLC, thereby promoting the expression of FT in companion cells to stimulate flowering

Micromechanical Observation and Numerical Simulation for Local Deformation Evolution of Duplex Stainless Steel

The characteristics of local strain distribution and evolution of duplex stainless steel during the tensile process were studied using the digital image correlation (DIC) technique. In addition, the finite element inversion of nanoindentation experiments of austenitic and ferrite phases in duplex stainless steel was carried out to obtain the stress–strain response of the two phases. Further, based on the representative volume element (RVE) and the material parameters obtained from the finite element inversion method, the local stress and strain behavior of duplex stainless steel at microscale was simulated numerically. The results fit well with the experiments, showing that the austenite phase is softer than ferrite phase, with the larger strain zone concentrated in the austenite phase and the larger stress zone concentrated in the ferrite phase. The grain boundaries are prone to obvious stress and strain concentrations. The local stress and strain distributions are influenced by the shape and interaction of the grains, while the distribution features become more obvious as the load increases. The research results effectively reveal the two-phase interaction and local failure mechanism of duplex stainless steel, and may provide a reference for material preparation and safety design of related structures

Biocompatible Chitosan Nanobubbles for Ultrasound-Mediated Targeted Delivery of Doxorubicin

Abstract Ultrasound-targeted delivery of nanobubbles (NBs) has become a promising strategy for noninvasive drug delivery. The biosafety and drug-transporting ability of NBs have been a research hotspot, especially regarding chitosan NBs due to their biocompatibility and high biosafety. Since the drug-carrying capacity of chitosan NBs and the performance of ultrasound-assisted drug delivery remain unclear, the aim of this study was to synthesize doxorubicin hydrochloride (DOX)-loaded biocompatible chitosan NBs and assess their drug delivery capacity. In this study, the size distribution of chitosan NBs was measured by dynamic light scattering, while their drug-loading capacity and ultrasound-mediated DOX release were determined by a UV spectrophotometer. In addition, a clinical ultrasound imaging system was used to evaluate the ability of chitosan NBs to achieve imaging enhancement, while the biosafety profile of free chitosan NBs was evaluated by a cytotoxicity assay in MCF-7 cells. Furthermore, NB-mediated DOX uptake and the apoptosis of Michigan Cancer Foundation-7 (MCF-7) cells were measured by flow cytometry. The results showed that the DOX-loaded NBs (DOX-NBs) exhibited excellent drug-loading ability as well as the ability to achieve ultrasound enhancement. Ultrasound (US) irradiation promoted the release of DOX from DOX-NBs in vitro. Furthermore, DOX-NBs effectively delivered DOX into mammalian cancer cells. In conclusion, biocompatible chitosan NBs are suitable for ultrasound-targeted DOX delivery and are thus a promising strategy for noninvasive and targeted drug delivery worthy of further investigation

Deep-Learning Based Injection Attacks Detection Method for HTTP

In the context of the new era of high digitization and informatization, the emergence of the internet and artificial intelligence technologies has profoundly changed people’s lifestyles. The traditional cyber attack detection has become increasingly weak in the context of the increasingly complex network environment in the new era, and deep learning technology has begun to play a significant role in the field of network security. There are many kinds of attacks against web applications, which are very harmful, including SQL (Structured Query Language) injection, XSS (Cross-Site Scripting), and command injection. Based on the detection of SQL injection and XSS attacks, this paper combines the detection of command injection attacks, which are also very harmful, and proposes a multi-classification detection method for web injection attacks. We extract features in the URL (Uniform Resource Locator) and request body of HTTP (Hyper Text Transfer Protocol) requests and combine deep learning technology to build a multi-classification model for injection attacks. Firstly, aiming at the problem of imbalanced distribution of training samples and low detection accuracy of command injection attack, a sample generation method is proposed. The experimental results show that the proposed method ensures a higher detection rate of command injection attacks and lower false alarms. Secondly, we propose a more expressive feature fusion model, which effectively combines the features extracted by deep learning with the discrete features extracted manually. The experimental results show that the feature fusion model proposed in this work is more effective compared with a single deep learning model. The accuracy of the model is improved by about 1%

DoSGuard: Mitigating Denial-of-Service Attacks in Software-Defined Networks

Software-defined networking (SDN) is a new networking paradigm that realizes the fast management and optimal configuration of network resources by decoupling control logic and forwarding functions. However, centralized network architecture brings new security problems, and denial-of-service (DoS) attacks are among the most critical threats. Due to the lack of an effective message-verification mechanism in SDN, attackers can easily launch a DoS attack by faking the source address information. This paper presents DoSGuard, an efficient and protocol-independent defense framework for SDN networks to detect and mitigate such attacks. DoSGuard is a lightweight extension module on SDN controllers that mainly consists of three key components: a monitor, a detector, and a mitigator. The monitor maintains the information between the switches and the hosts for anomaly detection. The detector utilizes OpenFlow message and flow features to detect the attack. The mitigator protects networks by filtering malicious packets. We implement a prototype of DoSGuard in the floodlight controller and evaluate its effectiveness in a simulation environment. Experimental results show the DoSGuard achieves 98.72% detecion precision, and the average CPU utilization of the controller is only around 8%. The results demonstrate that DoSGuard can effectively mitigate DoS attacks against SDN with limited overhead

KRRecover: An Auto-Recovery Tool for Hijacked Devices and Encrypted Files by Ransomwares on Android

Ransomwares on Android have become a challenging threat, performing tasks such as hijacking screen resources, locking devices, and encrypting files. Even worse, with the evolution of ransomwares, many ransomwares can disable USB interfaces of mobile devices. It is difficult for users to recover their devices or decrypt files with the help of other equipment and gives monetary damages to victims. In this paper, we analyse the symmetry between the ransom behaviours and the source code of screen resource hijacked ransomwares, devices locked ransomwares and files encrypted ransomwares. We also propose strategies of recovering hijacked resources, recovering hijacked devices and decrypting encrypted files. To protect mobile devices and private files from ransomwares, we design and implement an automatic recovery application—KRRecover—which is used to recover the hijacked devices and decrypt encrypted files on Android

Effect of B on microstructure and properties of joints brazed by In-situ Ag-Cu-Zn-Sn filler metal with high Sn content

The copper brazed joints were obtained by induction brazing using in situ synthetic high Sn content silver filler metals with different B contents and the effect of element B on the wettability of filler metals and microstructure and mechanical properties of the joints were studied. With the addition of element B, the spreading area of the filler metals on the copper increases. The microstructure of the joints mainly consists of silver-based solid solution and copper-based solid solution, and the distribution of silver-based solid solution in the brazing seam becomes dispersed with the addition of B. The width of the brazing seam increases significantly with the increase in B content. Meanwhile, the B element was mainly distributed in the Ag-based solid solution. The tensile strength firstly increased and then sharply decreased with B added. The maximum average tensile strength of 206.83 MPa was obtained with a 2% addition of B and the joint fracture pattern is a brittle fracture