Chinese Medicine for Treatment of COVID-19: A Review of Potential Pharmacological Components and Mechanisms.

Coronavirus disease 2019 (COVID-19) is an acute infectious respiratory disease that has been prevalent since December 2019. Chinese medicine (CM) has demonstrated its unique advantages in the fight against COVID-19 in the areas of disease prevention, improvement of clinical symptoms, and control of disease progression. This review summarized the relevant material components of CM in the treatment of COVID-19 by searching the relevant literature and reports on CM in the treatment of COVID-19 and combining with the physiological and pathological characteristics of the novel coronavirus. On the basis of sorting out experimental methods in vivo and in vitro, the mechanism of herb action was further clarified in terms of inhibiting virus invasion and replication and improving related complications. The aim of the article is to explore the strengths and characteristics of CM in the treatment of COVID-19, and to provide a basis for the research and scientific, standardized treatment of COVID-19 with CM.

COVID-19 transmission and control in land public transport: A literature review.

Land public transport is an important link within and between cities, and how to control the transmission of COVID-19 in land public transport is a critical issue in our daily lives. However, there are still many inconsistent opinions and views about the spread of SARS-CoV-2 in land public transport, which limits our ability to implement effective interventions. The purpose of this review is to overview the literature on transmission characteristics and routes of the epidemic in land public transport, as well as to investigate factors affecting its spread and provide feasible measures to mitigate the infection risk of passengers. We obtained 898 papers by searching the Web of Science, Pubmed, and WHO global COVID database by keywords, and finally selected 45 papers that can address the purpose of this review. Land public transport is a high outbreak area for COVID-19 due to characteristics like crowding, inadequate ventilation, long exposure time, and environmental closure. Different from surface touch transmission and drop spray transmission, aerosol inhalation transmission can occur not only in short distances but also in long distances. Insufficient ventilation is the most important factor influencing long-distance aerosol transmission. Other transmission factors (e.g., interpersonal distance, relative orientation, and ambient conditions) should be noticed as well, which have been summarized in this paper. To address various influencing factors, it is essential to suggest practical and efficient preventive measures. Among these, increased ventilation, particularly the fresh air (i.e., natural ventilation), has proven to effectively reduce indoor infection risk. Many preventive measures are also effective, such as enlarging social distance, avoiding face-to-face orientation, setting up physical partitions, disinfection, avoiding talking, and so on. As research on the epidemic has intensified, people have broken down many perceived barriers, but more comprehensive studies on monitoring systems and prevention measures in land public transport are still needed.

Selenium nanoparticles decorated with polysaccharides from Sargassum fusiforme protects against 6-OHDA-induced neurotoxicity in PC12 cells and rat model of Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder and identifying disease-causing pathways and drugs that target them has remained challenging. Herein, selenium nanoparticles decorated with polysaccharides from Sargassum fusiforme (SFPS-SeNPs) were investigated on 6-OHDA-induced neurotoxicity in PC12 cells and rats. 6-OHDA can significantly increase neurotoxicity, oxidative stress and decrease the activity of superoxide dismutase (SOD) and glutathione peroxidase (GPx) both in vitro and vivo. In vitro, treatment with SFPS-SeNPs can significantly decrease 6-OHDA cytotoxicity, reactive oxygen species (ROS) production or malondialdehyde (MDA) levels, and cell apoptosis, significantly increased the activity of SOD and GPx. In vivo, 6-OHDA exposure could also decrease the expression of Nrf2 and OH-1, while treatment with SFPS-SeNPs (1 mg Se/kg) increased. SFPS-SeNPs can protect neurons from 6-OHDA-induced neurotoxicity by regulating apoptosis and Nrf2/ARE pathway. The present study demonstrated that SFPS-SeNPs is a good candidate for developing a new drug against neurodegenerative diseases such as PD.

Novel Multitarget ACE Inhibitory Peptides from Bovine Colostrum Immunoglobulin G: Cellular Transport, Efficacy in Regulating Endothelial Dysfunction, and Network Pharmacology Studies.

In this study, we used traditional laboratory methods, bioinformatics, and cellular models to screen novel ACE inhibitory (ACEI) peptides with strong ACEI activity, moderate absorption rates, and multiple targets from bovine colostrum immunoglobulin G (IgG). The purified fraction of the compound proteinase hydrolysate of IgG showed good ACEI activity. After nano-UPLC-MS/MS identification and in silico analysis, eight peptides were synthesized and verified. Among them, SFYPDY, TSFYPDY, FSWF, WYQQVPGSGL, and GVHTFP were identified as ACEI peptides, as they exhibited strong ACEI activity (with IC50 values of 104.7, 80.0, 121.2, 39.8, and 86.3 µM, respectively). They displayed good stability in an in vitro simulated gastrointestinal digestion assay. In a Caco-2 monolayer model, SFYPDY, FSWF, and WYQQVPGSGL exhibited better absorption rates and lower IC50 values than the other peptides and were thereby identified as novel ACEI peptides. Subsequently, in a H2O2-induced endothelial dysfunction (ED) model based on HUVECs, SFYPDY, FSWF, and WYQQVPGSGL regulated ED by reducing apoptosis and ROS accumulation while upregulating NOS3 mRNA expression. Network pharmacology analysis and RT-qPCR confirmed that they regulated multiple targets. Overall, our results suggest that SFYPDY, FSWF, and WYQQVPGSGL can serve as novel multitarget ACEI peptides.

Family-Specific Training Improves Linear B Cell Epitope Prediction for Emerging Viruses.

The rational design of vaccines and antibody-based therapeutics against newly emerging viruses relies on B cell epitopes mainly. To predict the B cell epitopes of a novel virus, several algorithms have been developed. While most existing algorithms are trained on a dataset in which B cell epitopes are classified as 'Positive' or 'Negative'. However, we found that training on such data contaminates the target pattern of specific viruses, leading to inaccurate predictions in some cases. In this paper, we introduce a novel framework for predicting linear B cell epitopes of novel viruses by exclusively using highly similar viruses for training data. We employed kernel regression based on seropositive rates, which are the percentages of seropositive samples among the population, to predict the potential epitopes. To assess our method, we conducted simulations and utilized two real-world datasets. Our method significantly outperformed other existing methods on the testing data of four viruses with seropositive rates. Also, our strategy showed a better prediction in a larger dataset from the IEDB. Thus, a novel framework providing better linear B cell prediction of newly emerging viruses is established, which will benefit the rational design of vaccines and antibody-based therapeutics in the future.

Low-cost wavefront shaping via the third-order correlation of light fields.

In this Letter, inspired by the ghost imaging technique, we propose a wavefront shaping technique based on the third-order correlation of light fields (TCLF). Theoretically, we prove that if the light field fluctuation can be modeled by a complex Gaussian random process with a non-zero mean, the conjugate complex amplitude of the object and a focusing phase factor can be obtained by TCLF when using a single-point detector, which can support wavefront shaping. Experiments demonstrate that TCLF can achieve high-resolution wavefront shaping for scattered fields and scattering-assisted holography without additional operations such as optimization and phase shifting.

Baveno VII criteria for recompensation predict transplant-free survival in patients with hepatitis B-related decompensated cirrhosis.

Background & Aims: The latest Baveno VII consensus has provided guidance for identifying patients who have truly recompensated from those with hepatic decompensation. This study aimed to evaluate patients' transplant-free survival in three different stages of cirrhosis. Methods: All patients with chronic HBV infection and liver cirrhosis treated with oral nucleos(t)ide analogues from March 2006 to December 2022 were identified from a territory-wide database in Hong Kong. Patients with follow-up duration of <1 year were excluded. Participants were classified into three mutually exclusive groups: (1) no decompensated events (i.e. compensated group); (2) decompensated events occurred (i.e. decompensated group); or (3) decompensated events occurred followed by recompensation according to Baveno VII criteria (i.e. recompensated group). A time-dependent Cox proportional hazard model was adopted for evaluation. The follow-up period was 5 years. Results: A total of 4,701 patients with cirrhosis and HBV who were treated with entecavir, tenofovir disoproxil fumarate (TDF), and tenofovir alafenamide fumarate (TAF) were identified. During a median follow-up of 5 years (interquartile range 3.7, 5 years), 3,327 (70.8%), 1,347 (29.2%), and 265 (5.6%) patients had compensated, decompensated, and recompensated cirrhosis, respectively, at least once before the end of the study. In the time-dependent multivariable model, the recompensated group had similar transplant-free survival compared with the compensated group (adjusted hazard ratio 1.16; 95% CI 0.72-1.86; p = 0.536). The 5-year transplant-free survival rate was 89.3% for the compensated group, whereas it was 76.0% for the recompensated group, reflecting a minimal difference between the two groups. Conclusions: The clinical significance of recompensation of cirrhosis in improving patient outcomes for individuals with CHB infection was highlighted in this study. Early identification and treatment with nucleos(t)ide analogues might promote hepatic recompensation and thus reduce mortality in patients with CHB. Impact and implications: The latest Baveno VII consensus introduces the new concept of hepatic recompensation, which refers to the reversal of the structural and functional changes of cirrhosis after removal, cure, or suppression of the aetiology of cirrhosis. It is essential to investigate the transplant-free survival rates of patients who are able to achieve hepatic recompensation, as this has significant implications for the medical resources required to manage liver failure and transplantation. This study features the clinical significance of hepatic recompensation by comparing patient outcomes of those who achieve it to those who do not. The early identification and use of antiviral treatment with nucleos(t)ide analogues is a pivotal strategy to promote hepatic recompensation, which has the potential to significantly reduce mortality rates in patients with chronic HBV infection and ultimately aid in the elimination of hepatitis.

A Bayesian approach to estimate MHC-peptide binding threshold.

Major histocompatibility complex (MHC)-peptide binding is a critical step in enabling a peptide to serve as an antigen for T-cell recognition. Accurate prediction of this binding can facilitate various applications in immunotherapy. While many existing methods offer good predictive power for the binding affinity of a peptide to a specific MHC, few models attempt to infer the binding threshold that distinguishes binding sequences. These models often rely on experience-based ad hoc criteria, such as 500 or 1000nM. However, different MHCs may have different binding thresholds. As such, there is a need for an automatic, data-driven method to determine an accurate binding threshold. In this study, we proposed a Bayesian model that jointly infers core locations (binding sites), the binding affinity and the binding threshold. Our model provided the posterior distribution of the binding threshold, enabling accurate determination of an appropriate threshold for each MHC. To evaluate the performance of our method under different scenarios, we conducted simulation studies with varying dominant levels of motif distributions and proportions of random sequences. These simulation studies showed desirable estimation accuracy and robustness of our model. Additionally, when applied to real data, our results outperformed commonly used thresholds.

Identification of a Common Variant for Coronary Heart Disease at PDE1A Contributes to Individualized Treatment Goals and Risk Stratification of Cardiovascular Complications in Chinese Patients With Type 2 Diabetes.

OBJECTIVE: In this study we aim to unravel genetic determinants of coronary heart disease (CHD) in type 2 diabetes (T2D) and explore their applications. RESEARCH DESIGN AND METHODS: We performed a two-stage genome-wide association study for CHD in Chinese patients with T2D (3,596 case and 8,898 control subjects), followed by replications in European patients with T2D (764 case and 4,276 control subjects) and general populations (n = 51,442-547,261). Each identified variant was examined for its association with a wide range of phenotypes and its interactions with glycemic, blood pressure (BP), and lipid controls in incident cardiovascular diseases. RESULTS: We identified a novel variant (rs10171703) for CHD (odds ratio 1.21 [95% CI 1.13-1.30]; P = 2.4 × 10-8) and BP (ß ± SE 0.130 ± 0.017; P = 4.1 × 10-14) at PDE1A in Chinese T2D patients but found only a modest association with CHD in general populations. This variant modulated the effects of BP goal attainment (130/80 mmHg) on CHD (Pinteraction = 0.0155) and myocardial infarction (MI) (Pinteraction = 5.1 × 10-4). Patients with CC genotype of rs10171703 had >40% reduction in either cardiovascular events in response to BP control (2.9 × 10-8 < P < 3.6 × 10-5), those with CT genotype had no difference (0.0726 < P < 0.2614), and those with TT genotype had a threefold increase in MI risk (P = 6.7 × 10-3). CONCLUSIONS: We discovered a novel CHD- and BP-related variant at PDE1A that interacted with BP goal attainment with divergent effects on CHD risk in Chinese patients with T2D. Incorporating this information may facilitate individualized treatment strategies for precision care in diabetes, only when our findings are validated.

IRF3-mediated lncRNA FTX promotes cell proliferation, migration, invasion and suppresses cell apoptosis in oral squamous cell carcinoma by up-regulating FCHSD2 via miR-708-5p.

In recent years, researches into the molecular mechanisms of oral squamous cell carcinoma (OSCC) have improved greatly but effective targeted therapies remain elusive. More and more evidence has referred to long non-coding RNAs (lncRNAs) as modulators of carcinomas development. As a novel lncRNA, five prime to Xist (FTX), as reported before, is overexpressed in a variety of cancers. In the present study, we sought to unclose the impacts of FTX and its molecular mechanism in OSCC. Related gene expression levels were disclosed by qRT-PCR and we found that FTX was notably overexpressed in OSCC. The biological functions of FTX in OSCC were measured by functional assays. The results displayed that depletion of FTX hinderedOSCC cell migratory, invasive and proliferative abilities, but promoted cell apoptotic levels. The relationship among interferon regulatory factor 3 (IRF3), FTX, microRNA-708-5p (miR-708-5p) and FCH and double SH3 domains 2 (FCHSD2) was determined by several mechanism assays, from which we discovered that FTX activated by IRF3 regulated FCHSD2 expression by sponging miR-708-5p. Rescue experiments showed that FTX motivated OSCC development by modulating miR-708-5p/FCHSD2 axis. In summary, FTX was an oncogene in OSCC and might provide new insights into OSCC treatment.

Automatic block-wise genotype-phenotype association detection based on hidden Markov model.

BACKGROUND: For detecting genotype-phenotype association from case-control single nucleotide polymorphism (SNP) data, one class of methods relies on testing each genomic variant site individually. However, this approach ignores the tendency for associated variant sites to be spatially clustered instead of uniformly distributed along the genome. Therefore, a more recent class of methods looks for blocks of influential variant sites. Unfortunately, existing such methods either assume prior knowledge of the blocks, or rely on ad hoc moving windows. A principled method is needed to automatically detect genomic variant blocks which are associated with the phenotype. RESULTS: In this paper, we introduce an automatic block-wise Genome-Wide Association Study (GWAS) method based on Hidden Markov model. Using case-control SNP data as input, our method detects the number of blocks associated with the phenotype and the locations of the blocks. Correspondingly, the minor allele of each variate site will be classified as having negative influence, no influence or positive influence on the phenotype. We evaluated our method using both datasets simulated from our model and datasets from a block model different from ours, and compared the performance with other methods. These included both simple methods based on the Fisher's exact test, applied site-by-site, as well as more complex methods built into the recent Zoom-Focus Algorithm. Across all simulations, our method consistently outperformed the comparisons. CONCLUSIONS: With its demonstrated better performance, we expect our algorithm for detecting influential variant sites may help find more accurate signals across a wide range of case-control GWAS.

Influence of natural ventilation design on the dispersion of pathogen-laden droplets in a coach bus.

Natural ventilation is an energy-efficient design approach to reduce infection risk (IR), but its optimized design in a coach bus environment is less studied. Based on a COVID-19 outbreak in a bus in Hunan, China, the indoor-outdoor coupled CFD modeling approach is adopted to comprehensively explore how optimized bus natural ventilation (e.g., opening/closing status of front/middle/rear windows (FW/MW/RW)) and ceiling wind catcher (WCH) affect the dispersion of pathogen-laden droplets (tracer gas, 5 µm, 50 µm) and IR. Other key influential factors including bus speed, infector's location, and ambient temperature (Tref) are also considered. Buses have unique natural ventilation airflow patterns: from bus rear to front, and air change rate per hour (ACH) increases linearly with bus speed. When driving at 60 km/h, ACH is only 6.14 h-1 and intake fractions of tracer gas (IFg) and 5 µm droplets (IFd) are up to 3372 ppm and 1394 ppm with ventilation through leakages on skylights and no windows open. When FW and RW are both open, ACH increases by 43.5 times to 267.50 h-1, and IFg and IFd drop rapidly by 1-2 orders of magnitude compared to when no windows are open. Utilizing a wind catcher and opening front windows significantly increases ACH (up to 8.8 times) and reduces IF (5-30 times) compared to only opening front windows. When the infector locates at the bus front with FW open, IFg and IFd of all passengers are <10 ppm. More droplets suspend and further spread in a higher Tref environment. It is recommended to open two pairs of windows or open front windows and utilize the wind catcher to reduce IR in coach buses.

Revealing Free Energy Landscape From MD Data via Conditional Angle Partition Tree.

Deciphering the free energy landscape of biomolecular structure space is crucial for understanding many complex molecular processes, such as protein-protein interaction, RNA folding, and protein folding. A major source of current dynamic structure data is Molecular Dynamics (MD) simulations. Several methods have been proposed to investigate the free energy landscape from MD data, but all of them rely on the assumption that kinetic similarity is associated with global geometric similarity, which may lead to unsatisfactory results. In this paper, we proposed a new method called Conditional Angle Partition Tree to reveal the hierarchical free energy landscape by correlating local geometric similarity with kinetic similarity. Its application on the benchmark alanine dipeptide MD data showed a much better performance than existing methods in exploring and understanding the free energy landscape. We also applied it to the MD data of Villin HP35. Our results are more reasonable on various aspects than those from other methods and very informative on the hierarchical structure of its energy landscape.

Screening of xylene degrading bacteria and optimization of their degradation characteristics in heavily polluted areas.

Aiming at the problems of high xylene concentration and difficult removal in heavily polluted areas, high-efficient degrading bacteria of volatile organic compounds (VOCs) xylene in heavily polluted areas were selected and screened from sewage sludge, and their degradation characteristics were studied. The response surface methodology (RSM) optimized the optimal degradation conditions. The results showed that the screened degrading strain was identified as Klebsiella by the 16SrDNA technology and named H-16. During the start-up phase of the reactor, the removal rate of xylene by strain H-16 fluctuated, and it was stable above 71.3% for 150 min. At 40°C, the degradation rate is the highest, reaching 63.25%. With an increasing inoculum amount of strain H-16, the degradation rate of xylene gradually increased, and the degradation rate could reach 86.1% when the inoculation amount was 25%. A neutral environment was more conducive to the degradation and removal of xylene. Through the analysis of the model and RSM, the optimal conditions for the degradation of xylene by H-16 were obtained: 38.89°C, pH 6.94 and 18.07%. GC-MS results showed that the possible degradation pathway of xylene began with demethylation, formation of pentene diacid by benzene ring cleavage, and finally oxidation to generate CO2 and H2O.

Exhaustive Cross-Linking Search with Protein Feedback.

Improving the sensitivity of protein-protein interaction detection and protein structure probing is a principal challenge in cross-linking mass spectrometry (XL-MS) data analysis. In this paper, we propose an exhaustive cross-linking search method with protein feedback (ECL-PF) for cleavable XL-MS data analysis. ECL-PF adopts an optimized α/ß mass detection scheme and establishes protein-peptide association during the identification of cross-linked peptides. Existing major scoring functions can all benefit from the ECL-PF workflow to a great extent. In comparisons using synthetic data sets and hybrid simulated data sets, ECL-PF achieved 3-fold higher sensitivity over standard techniques. In experiments using real data sets, it also identified 65.6% more cross-link spectrum matches and 48.7% more unique cross-links.

A Bayesian model for identifying cancer subtypes from paired methylation profiles.

Aberrant DNA methylation is the most common molecular lesion that is crucial for the occurrence and development of cancer, but has thus far been underappreciated as a clinical tool for cancer classification, diagnosis or as a guide for therapeutic decisions. Partly, this has been due to a lack of proven algorithms that can use methylation data to stratify patients into clinically relevant risk groups and subtypes that are of prognostic importance. Here, we proposed a novel Bayesian model to capture the methylation signatures of different subtypes from paired normal and tumor methylation array data. Application of our model to synthetic and empirical data showed high clustering accuracy, and was able to identify the possible epigenetic cause of a cancer subtype.

Uptake of core outcome sets by clinical trialists in China: a protocol.

Background: The concept of core outcome sets (COS) has been introduced in China for about 10 years. In recent years, some Chinese researchers also committed to developing COS, though the majority of COS are ongoing. However, there were more than 500 published COS for research in the COMET database by 2020. The extent of availability of COS for the top 25 diseases with the highest burden in China is unknown. In addition, the uptake of COS in clinical trials for these diseases is unknown, along with the knowledge, perceptions, and views of the clinical trialist community in China on the use of COS in relation to choosing outcomes for their research. Methods: The main burden of disease in China will be identified. Then we will search the COMET database to identify if there are ongoing or completed relevant COS research A COS published since 2012 would be preferred to one published before 2012 for the analysis of COS uptake if one meets the eligibility criteria. We will extract scopes of published eligible COS, including condition, population, interventions, and core outcomes. Then we will search the Chinese Clinical Trial Registry using disease names for each disease that has a published COS. We will assess the overlap in scope between clinical trials and COS. Then we will conduct an online survey and semi-structured interviews to identify the knowledge and perceptions of COS among primary investigators of included clinical trials. Discussion: This research will fill in gaps between COS and the burden of disease in China. Understanding clinical trialists'knowledge and perceptions of COS may help dissemination and application of COS in the future. Trial registration: This research is registered in Core Outcome Measures in Effectiveness: https://www.comet-initiative.org/Studies/Details/2563.

Potential anticancer activities of securinine and its molecular targets.

BACKGROUND: Securinine is an alkaloid identified from the roots and leaves of the shrub Flueggea suffruticosa (Pall.) Baill. The molecular structure of securinine consists of four rings, including three chiral centers. It has been suggested that securinine can be chemically synthesized from tyrosine and lysine. Securinine has long been used to treat central nervous system diseases. In recent years, more and more evidence shows that securinine also has anticancer activity, which has not been systematically discussed and analyzed. PURPOSE: This study aims to propose an overall framework to describe the molecular targets of securinine in different signal pathways, and discuss the current status and prospects of each pathway, so as to provide a theoretical basis for the development securinine as an effective anticancer drug. METHODS: The research databases on the anticancer activity of securinine from PubMed, Scopus, Web of Science and ScienceDirect to 2021 were systematically searched. This paper follows the Preferred Reporting Items and Meta-Analysis guidelines. RESULTS: Securinine has the ability to kill a variety of human cancer cells, including, leukemia as well as prostate, cervical, breast, lung, and colon cancer cells. It can regulate the signal pathways of phosphatidylinositol-3-kinase/protein kinase B/mammalian target of rapamycin, Wnt and Janus kinase-signal transducer and activator of transcription, promote cancer cell apoptosis and autophagy, and inhibit cancer cell metastasis. Securinine also has the activity of inducing leukemia cell differentiation. CONCLUSION: Although there has been some experimental evidence indicating the anticancer effect of securinine and its possible pharmacology, in order to design more effective anticancer drugs, it is necessary to study the synergy of intracellular signaling pathways. More in vivo experiments and even clinical studies are needed, and the synergy between securinine and other drugs is also worth studying.

Bioremediation of a saline-alkali soil polluted with Zn using ryegrass associated with Fusariumincarnatum.

Biotechnological strategies have become effective in the remediation of polluted soils as they are cost-effective and do not present a risk of secondary pollution. However, using a single bioremediation technique (microorganism or plant) is not suitable for achieving a high remediation rate of polluted saline-alkali soils with heavy metals. Therefore, the present study aims to assess the effects and mechanisms of combined ryegrass and Fusarium incarnatum on the zinc (Zn)-polluted saline-alkali soil over 45 days. According to the obtained results, the combined Fusarium incarnatum-ryegrass showed the highest remediation rate of 49.35% after 45 days, resulting in a significantly lower soil Zn concentration than that observed in the control group. In addition, the inoculation of Fusarium incarnatum showed a positive effect on the soil EPS secretion. The soil protein contents ranged from 0.035 to 0.055 mg/kg, while the soil polysaccharide contents increased from 0.25 to 0.61 mg/g. The soil microbial flora and ryegrass showed resistance to saline and alkaline stresses through the secretion of extracellular polysaccharides. The three-dimensional fluorescence spectrum (3D-EEM) confirmed that EPS in the soil was mainly a fulvic acid-like substance. The fluorescein diacetate (FDA) hydrolase activity in the saline-alkali soil was first increased due to the effect of Fusarium incarnatum and then decreased to a minimum value of 96 µg/(g·h). In addition, the Fusarium incarnatum inoculation improved the diversity and richness of soil fungi. Although the Fusarium incarnatum inoculation had a slight effect on the germination of ryegrass, it increased the biomass and enrichment coefficient. The results revealed a translocation factor (TF) value of 0.316 at 45 days after ryegrass sowing, showing significant enrichment of the soil Zn heavy metal zinc in the ryegrass roots.