Platelet-derived TGF-ß1 induces functional reprogramming of myeloid-derived suppressor cells in immune thrombocytopenia.

ABSTRACT: Platelet α-granules are rich in transforming growth factor ß1 (TGF-ß1), which is associated with myeloid-derived suppressor cell (MDSC) biology. Responders to thrombopoietin receptor agonists (TPO-RAs) revealed a parallel increase in the number of both platelets and MDSCs. Here, anti-CD61 immune-sensitized splenocytes were transferred into severe combined immunodeficient mice to establish an active murine model of immune thrombocytopenia (ITP). Subsequently, we demonstrated that TPO-RAs augmented the inhibitory activities of MDSCs by arresting plasma cells differentiation, reducing Fas ligand expression on cytotoxic T cells, and rebalancing T-cell subsets. Mechanistically, transcriptome analysis confirmed the participation of TGF-ß/Smad pathways in TPO-RA-corrected MDSCs, which was offset by Smad2/3 knockdown. In platelet TGF-ß1-deficient mice, TPO-RA-induced amplification and enhanced suppressive capacity of MDSCs was waived. Furthermore, our retrospective data revealed that patients with ITP achieving complete platelet response showed superior long-term outcomes compared with those who only reach partial response. In conclusion, we demonstrate that platelet TGF-ß1 induces the expansion and functional reprogramming of MDSCs via the TGF-ß/Smad pathway. These data indicate that platelet recovery not only serves as an end point of treatment response but also paves the way for immune homeostasis in immune-mediated thrombocytopenia.

Exo-miR-144-3p as a promising diagnostic biomarker for depressive symptoms in heart failure.

AIMS: The prevalence of depression is higher in heart failure (HF) patients. Early screening of depressive symptoms in HF patients and timely intervention can help to improve patients' quality of life and prognosis. This study aims to explore diagnostic biomarkers by examining the expression profile of serum exosomal miRNAs in HF patients with depressive symptoms. METHODS: Serum exosomal RNA was isolated and extracted from 6 HF patients with depressive symptoms (HF-DS) and 6 HF patients without depressive symptoms (HF-NDS). High-throughput sequencing was performed to obtain miRNA expression profiles and target genes were predicted for the screened differentially expressed miRNAs. Biological functions of the target genes were analyzed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, we collected serum exosomal RNAs from HF-DS (n = 20) and HF-NDS (n = 20). The differentially expressed miRNAs selected from the sequencing results were validated using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Finally, the diagnostic efficacy of the differentially expressed exosomal miRNAs for HF-DS was evaluated by using receiver operating characteristic (ROC) curves. RESULTS: A total of 19 significantly differentially expressed exosomal miRNAs were screened by high-throughput sequencing, consisting of 12 up-regulated and 7 down-regulated exosomal miRNAs. RT-qPCR validation demonstrated that the expression level of exo-miR-144-3p was significantly down-regulated in the HF-DS group, and the expression levels of exo-miR-625-3p and exo-miR-7856-5p were significantly up-regulated. In addition, the expression level of exo-miR-144-3p was negatively correlated with the severity of depressive symptoms in HF patients, and that the area under the curve (AUC) of exo-miR-144-3p for diagnosing HF-DS was 0.763. CONCLUSIONS: In this study, we examined the serum exosomal miRNA expression profiles of HF patients with depressive symptoms and found that lower level of exo-miR-144-3p was associated with more severe depressive symptoms. Exo-miR-144-3p is a potential biomarker for the diagnosis of HF-DS.

Landscape of gut microbiota and metabolites and their interaction in comorbid heart failure and depressive symptoms: a random forest analysis study.

IMPORTANCE: There is increasing evidence that alterations in gut microbial composition and function are associated with cardiovascular or psychiatric disease. Therefore, it is meaningful to investigate the taxonomic and functional characterization of the microbiota in HF patients who also have depressive symptoms. In this cross-sectional study, Cloacibacillus and alpha-tocopherol were determined as new diagnostic markers. Furthermore, intestinal microecosystem disorders are closely linked to depressive symptoms in HF patients, providing a new reference viewpoint for understanding the gut-heart/brain axis.

Urine based near-infrared spectroscopy analysis reveals a noninvasive and convenient diagnosis method for cancers: a pilot study.

Background: The challenges in cancer diagnosis underline the need for continued research and development of new diagnostic tools and methods. This study aims to explore an effective, noninvasive, and convenient diagnostic tool using urine based near-infrared spectroscopy (NIRS) analysis combined with machine learning algorithm. Methods: Urine samples were collected from a total of 327 participants, including 181 cancer cases and 146 healthy controls. These participants were randomly spit into train set (n = 218) and test set (n = 109). NIRS analysis (4,000 ∼10,000 cm-1) was performed for each sample in both train and test sets. Five pretreatment methods, including Savitzky-Golay (SG) smoothing, multiplicative scatter correction (MSC), baseline removal (BSL) with fitting polynomials to be used as baselines, the first derivative (DERIV1), and the second derivative (DERIV2), and combination with "scaling" and "center", were investigated. Then partial least-squares (PLS) and linear support-vector machine (SVM) classification models were established, and prediction performance was evaluated in test set. Results: NIRS had greatly overlapping in peaks, and PCA analysis failed in separation between cancers and healthy controls. In modeling with urine based NIRS data, PLS model showed its highest prediction accuracy of 0.780, with DERIV2, "scaling" and "center" pretreatment, while linear SVM displayed its best prediction accuracy of 0.844, with raw NIRS. With optimization in SVM, the prediction accuracy could improve to 0.862, when the top 262 features were involved as variables. Discussion: This pilot study combining urine based NIRS analysis and machine learning is effective and convenient that might facilitate in cancer diagnosis, encouraging further evaluation with a large-size multi-center study.

Preoperative serum bilirubin is an independent prognostic factor for curatively resected esophageal squamous cell carcinoma.

PURPOSE: This study examines prognostic value of preoperative serum bilirubin, including unconjugated bilirubin (UCB), conjugated bilirubin (CB), and total bilirubin (TB), in esophageal squamous cell carcinoma (ESCC) patients who underwent curative resection. METHODS: Between May 2010 and December 2012, a total of 351 ESCC patients were retrospectively reviewed. All the patients underwent curative resection as their primary treatment. Clinicopathological features and overall survival (OS) rate were investigated. Kaplan-Meier curves were used to calculate the OS rate, and the prognostic factors were identified by Cox regression model. Besides, the potential inhibition effect of UCB on ESCC was investigated with both in vitro and in vivo models. RESULTS: The higher-level groups of UCB, CB, and TB demonstrated longer OS than their low counterparts, with hazard ratio (HR) values of 0.567 (95% CI: 0.424-0.759), 0.698 (95% CI: 0.522-0.933), and 0.602 (95% CI: 0.449-0.807), respectively. All three forms of bilirubin were identified as independent prognostic factors for patients with ESCC, and they were found to effectively stratify the survival risk of patients at TNM stage III. In vivo and in vitro models further confirmed the inhibitory effect of unconjugated bilirubin (UCB) on the proliferation of ESCC. CONCLUSION: The findings of our study have shed new light on the prognostic value and biological functions of bilirubin in relation to ESCC. These results may contribute to a better understanding of the underlying mechanisms involved in ESCC tumorigenesis and provide potential therapeutic pathways for treating ESCC.

Mitigation mechanism of zinc oxide nanoparticles on cadmium toxicity in tomato.

Cadmium (Cd) pollution seriously reduces the yield and quality of vegetables. Reducing Cd accumulation in vegetables is of great significance for improving food safety and sustainable agricultural development. Here, using tomato as the material, we analyzed the effect of foliar spraying with zinc oxide nanoparticles (ZnO NPs) on Cd accumulation and tolerance in tomato seedlings. Foliar spraying with ZnO NPs improved Cd tolerance by increasing photosynthesis efficiency and antioxidative capacity, while it reduced Cd accumulation by 40.2% in roots and 34.5% in leaves but increased Zn content by 33.9% in roots and 78.6% in leaves. Foliar spraying with ZnO NPs also increased the contents of copper (Cu) and manganese (Mn) in the leaves of Cd-treated tomato seedlings. Subsequent metabonomic analysis showed that ZnO NPs exposure alleviated the fluctuation of metabolic profiling in response to Cd toxicity, and it had a more prominent effect in leaves than in roots. Correlation analysis revealed that several differentially accumulated metabolites were positively or negatively correlated with the growth parameters and physiol-biochemical indexes. We also found that flavonoids and alkaloid metabolites may play an important role in ZnO NP-alleviated Cd toxicity in tomato seedlings. Taken together, the results of this study indicated that foliar spraying with ZnO NPs effectively reduced Cd accumulation in tomato seedlings; moreover, it also reduced oxidative damage, improved the absorption of trace elements, and reduced the metabolic fluctuation caused by Cd toxicity, thus alleviating Cd-induced growth inhibition in tomato seedlings. This study will enable us to better understand how ZnO NPs regulate plant growth and development and provide new insights into the use of ZnO NPs for improving growth and reducing Cd accumulation in vegetables.

Advances in research on the effectiveness and mechanism of Traditional Chinese Medicine formulas for colitis-associated colorectal cancer.

Inflammatory bowel disease (IBD) can progress into colitis-associated colorectal cancer (CAC) through the inflammation-cancer sequence. Although the mechanism of carcinogenesis in IBD has not been fully elucidated, the existing research indicates that CAC may represent a fundamentally different pathogenesis pattern of colorectal cancer. At present, there is no proven safe and effective medication to prevent IBD cancer. In recent years, Chinese medicine extracts and Chinese medicine monomers have been the subject of numerous articles about the prevention and treatment of CAC, but their clinical application is still relatively limited. Traditional Chinese Medicine (TCM) formulas are widely applied in clinical practice. TCM formulas have demonstrated great potential in the prevention and treatment of CAC in recent years, although there is still a lack of review. Our work aimed to summarize the effects and potential mechanisms of TCM formulas for the prevention and treatment of CAC, point out the issues and limitations of the current research, and provide recommendations for the advancement of CAC research in the future. We discovered that TCM formulas regulated many malignant biological processes, such as inflammation-mediated oxidative stress, apoptosis, tumor microenvironment, and intestinal microecology imbalance in CAC, through a review of the articles published in databases such as PubMed, SCOPUS, Web of Science, Embase, and CNKI. Several major signal transduction pathways, including NF-κB, STAT3, Wnt/ß-catenin, HIF-1α, and Nrf2, were engaged. TCM formula may be a promising treatment candidate to control the colitis-cancer transformation, however further high-quality research is required.

Identification and validation of ferroptosis-related genes and immune infiltration in ischemic cardiomyopathy.

Background: Cardiomyocyte death is an important pathophysiological basis for ischemic cardiomyopathy (ICM). Many studies have suggested that ferroptosis is a key link in the development of ICM. We performed bioinformatics analysis and experiment validation to explore the potential ferroptosis-related genes and immune infiltration of ICM. Methods: We downloaded the datasets of ICM from the Gene Expression Omnibus database and analyzed the ferroptosis-related differentially expressed genes (DEGs). Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and protein-protein interaction network were performed to analyze ferroptosis-related DEGs. Gene Set Enrichment Analysis was used to evaluate the gene enrichment signaling pathway of ferroptosis-related genes in ICM. Then, we explored the immune landscape of patients with ICM. Finally, the RNA expression of the top five ferroptosis-related DEGs was validated in blood samples from patients with ICM and healthy controls using qRT-PCR. Results: Overall, 42 ferroptosis-related DEGs (17 upregulated and 25 downregulated genes) were identified. Functional enrichment analysis indicated several enriched terms related to ferroptosis and the immune pathway. Immunological analysis suggested that the immune microenvironment in patients with ICM is altered. The immune checkpoint-related genes (PDCD1LG2, LAG3, and TIGIT) were overexpressed in ICM. The qRT-PCR results showed that the expression levels of IL6, JUN, STAT3, and ATM in patients with ICM and healthy controls were consistent with the bioinformatics analysis results from the mRNA microarray. Conclusion: Our study showed significant differences in ferroptosis-related genes and functional pathway between ICM patients and healthy controls. We also provided insight into the landscape of immune cells and the expression of immune checkpoints in patients with ICM. This study provides a new road for future investigation of the pathogenesis and treatment of ICM.

Classification of multiple cancer types by combination of plasma-based near-infrared spectroscopy analysis and machine learning modeling.

BACKGROUND AND AIM: Near-infrared spectroscopy (NIRS) is a non-invasive and convenient tool, which gains features related to chemical components in biological samples. Machine learning (ML) has been popularized in medical diagnosis. This study aimed at investigating a novel cancer diagnosis strategy using NIRS data based ML modeling. METHODS: Plasma samples were collected from a total of 247 participants, including lung cancer, cervical cancer, nasopharyngeal cancer, and healthy control, and were randomly split into train set and test set. After performing NIRS analysis, the train dataset was utilized to train ML models, including partial least-squares (PLS), random forest (RF), gradient boosting machine (GBM), and support-vector machine (SVM). Subsequently, these models were tested for their prediction performance by the test set. RESULTS: All ML models demonstrated high prediction performance in differentiating cancers from controls, and SVM had high prediction accuracy for different types of cancers. SVM was considered as the most suitable model for its minimal computational cost and high accuracies for both binary and quaternary classification. CONCLUSIONS: This strategy coupling NIRS with ML is insightful that may aid in clinic cancer diagnosis, while further studies should test our results in a larger cohort with better representativeness.

A bibliometric analysis of research on heart failure comorbid with depression from 2002 to 2021.

Heart failure (HF) with depression is a common comorbidity associated with worse clinical status and quality of life. Although there have been numerous high-quality studies and relevant reviews on HF comorbid with depression, few bibliometric analyses of this field have been reported. In order to understand the development process, research hotspots and future directions, this review analyzes the papers on HF comorbid with depression from January 2002 to December 2021 through CiteSpace and VOSviewer. Visual cooperative networks between countries, authors and institutions were conducted to understand the basic development status of HF comorbid with depression. Furthermore, we performed co-occurrence analysis, burst detection, and timeline analysis for keywords to understand this field's research directions and hotspots. Finally, a detailed review and analysis of the classical literature in this field were conducted based on co-citation analysis. This bibliometric analysis provides an overview of studies on HF comorbid with depression and emphasizes the research on comorbidity mechanisms and more effective interventions as a priority for future research.

Perfluorooctanoic acid and perfluorooctane sulfonic acid inhibit plant growth through the modulation of phytohormone signalling pathways: Evidence from molecular and genetic analysis in Arabidopsis.

Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) are the most representative perfluoroalkyl substances that accumulate in the food chain and are harmful to the environment. The uptake, translocation and physiological effects of PFOA and PFOS in plants have been reported in recent years; however, the regulatory mechanisms underlying PFOA- and PFOS-mediated plant growth and development remain largely unclear. Here, using Arabidopsis thaliana as the study material, we showed that both PFOA and PFOS inhibited plant growth; PFOS showed a stronger inhibitory effect on primary root (PR) growth, whereas PFOA exerted a stronger inhibitory effect on photosynthesis. Transcriptome analysis revealed that PFOA- and PFOS-modulated plant growth and development were correlated with the phytohormones auxin and abscisic acid (ABA). Further genetic analyses using mutants related to auxin biosynthesis, receptors and transport and mutants related to ABA biosynthesis and signalling transduction revealed that both PFOA and PFOS inhibited PR growth by modulating auxin biosynthesis and signalling pathways, and the ABA signalling pathway was also involved in PFOS-mediated PR growth inhibition. Collectively, these results shed new light on the molecular mechanisms of PFOA- and PFOS-mediated root system growth and their effects on phytohormone signalling pathways in plants.

Deleterious effects of nervous system in the offspring following maternal SARS-CoV-2 infection during the COVID-19 pandemic.

During the Coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is universally susceptible to all types of populations. In addition to the elderly and children becoming the groups of great concern, pregnant women carrying new lives need to be even more alert to SARS-CoV-2 infection. Studies have shown that pregnant women infected with SARS-CoV-2 can lead to brain damage and post-birth psychiatric disorders in offspring. It has been widely recognized that SARS-CoV-2 can affect the development of the fetal nervous system directly or indirectly. Pregnant women are recommended to mitigate the effects of COVID-19 on the fetus through vaccination, nutritional supplements, and psychological support. This review summarizes the possible mechanisms of the nervous system effects of SARS-CoV-2 infection on their offspring during the pregnancy and analyzes the available prophylactic and treatment strategies to improve the prognosis of fetal-related neuropsychiatric diseases after birth.

Comparative physiological and metabolomic analyses reveal that Fe3O4 and ZnO nanoparticles alleviate Cd toxicity in tobacco.

BACKGROUND: Heavy metals repress tobacco growth and quality, and engineered nanomaterials have been used for sustainable agriculture. However, the underlying mechanism of nanoparticle-mediated cadmium (Cd) toxicity in tobacco remains elusive. RESULTS: Herein, we investigated the effects of Fe3O4 and ZnO nanoparticles (NPs) on Cd stress in tobacco cultivar 'Yunyan 87' (Nicotiana tabacum). Cd severely repressed tobacco growth, whereas foliar spraying with Fe3O4 and ZnO NPs promoted plant growth, as indicated by enhancing plant height, root length, shoot and root fresh weight under Cd toxicity. Moreover, Fe3O4 and ZnO NPs increased, including Zn, K and Mn contents, in the roots and/or leaves and facilitated seedling growth under Cd stress. Metabolomics analysis showed that 150 and 76 metabolites were differentially accumulated in roots and leaves under Cd stress, respectively. These metabolites were significantly enriched in the biosynthesis of amino acids, nicotinate and nicotinamide metabolism, arginine and proline metabolism, and flavone and flavonol biosynthesis. Interestingly, Fe3O4 and ZnO NPs restored 50% and 47% in the roots, while they restored 70% and 63% in the leaves to normal levels, thereby facilitating plant growth. Correlation analysis further indicated that these metabolites, including proline, 6-hydroxynicotinic acid, farrerol and quercetin-3-O-sophoroside, were significantly correlated with plant growth. CONCLUSIONS: These results collectively indicate that metal nanoparticles can serve as plant growth regulators and provide insights into using them for improving crops in heavy metal-contaminated areas.

Role of depressive symptoms in the prognosis of heart failure and its potential clinical predictors.

AIMS: This study aims to analyse the factors associated with prognosis in hospitalized patients with heart failure, particularly the role of depressive symptoms, and to develop a prediction model for depressive symptoms based on clinical characteristics in hospitalized patients with heart failure. METHODS AND RESULTS: Baseline information was collected at admission, and patients were followed up after discharge. The endpoint events were being hospitalized for heart failure or all-cause death. Depressive symptoms were evaluated and defined via the Patient Health Questionnaire (PHQ)-2 and PHQ-9. The bidirectional elimination was used to screen independent predictors of heart failure with depression symptoms. The least absolute shrinkage and selection operator (LASSO) optimized the predictor variables, and the prediction model was constructed. The model was internally validated by the bootstrap sampling method (Bootstrap), and its performance was assessed by discrimination and calibration. The mean age of patients with heart failure was 69.43 ± 12.15 years, and the proportion of males was 66.67%. The prevalence of depressive symptoms in hospitalized patients with heart failure was 46.83%, and the prevalence of moderate/severe depressive symptoms was 11.62%. Eighty cases (30.30%) were readmitted for heart failure, and 13 cases (4.92%) were all-cause deaths. Depressive symptoms (HR = 2.43, 95% CI: 1.55-3.80) and the PHQ-9 score (HR = 1.11, 95% CI: 1.06-1.16) were both independent risk factors for endpoint events (P < 0.001). For heart failure patients combined with depressive symptoms, obesity (OR = 0.27, 95% CI: 0.09-0.77, P = 0.015), N-terminal brain natriuretic peptide precursor (NT-proBNP) level (lnNT-proBNP: OR = 1.55, 95% CI: 1.20-2.01, P < 0.001) and red blood cell distribution width (RDW) (OR = 1.26, 95% CI: 1.08-1.47, P = 0.004) were the independent factors. Six variables, including cardiovascular disease hospitalization history, obesity, renal insufficiency, NT-proBNP level, neutrophil ratio and RDW, were included to construct the prediction model. The area under the curve (AUC) was 0.730 in the original data, and the calibration curve was approximately distributed along the reference line in Bootstrap (500 resamplings), indicating the high level of discrimination and calibration of this model. CONCLUSIONS: Depressive symptoms and the PHQ-9 score are both independent risk factors for the prognosis of hospitalized patients with heart failure. In hospitalized patients with heart failure, the risk prediction model developed in this study has good predictive power for depressive symptoms.

STAT4 and COL1A2 are potential diagnostic biomarkers and therapeutic targets for heart failure comorbided with depression.

BACKGROUND: Heart failure (HF) and depression are common disorders that markedly compromise quality of life and impose a great financial burden on the society. Although increasing evidence has supported the closely linkage between the two disorders, the comorbidity mechanisms remain to be fully illuminated. We performed a bioinformatics network analysis to understand potential diagnostic biomarkers and therapeutic targets for HF comorbided with depression. METHODS: We downloaded the datasets of HF and depression from the Gene Expression Omnibus (GEO) database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis (WGCNA) to identify key modules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the common genes existing in the HF and depression related modules. Then, we employed the STRING database to construct the protein-protein interaction (PPI) network and detected the hub genes in the network. Finally, we validated the expression difference of hub genes from additional datasets of HF and depression. RESULTS: Functional enrichment analysis indicated that platelet activation, chemokine signaling and focal adhesion were probably involved in HF comorbided with depression. PPI network construction indicated that HF comorbided with depression is likely related to 5 hub genes, including STAT4, CD83, CX3CR1, COL1A2, and SH2D1B. In validated datasets, STAT4 and COL1A2 were especially involved in the comorbidity of HF and depression. CONCLUSION: Our work indicated a total of 5 hub genes including STAT4, CD83, CX3CR1, COL1A2, and SH2D1B, in which STAT4 and COL1A2 especially underlie the comorbidity mechanisms of HF and depression. These shared pathways might provide new targets for further mechanistic studies of the pathogenesis and treatment of HF and depression.

Significance of anti-HBc serological status in primary immune thrombocytopenia.

The association of previous hepatitis B virus (HBV) exposure [hepatitis B surface antigen (HBsAg) negative, hepatitis B core antibody (anti-HBc/HBcAb) positive] with disease severity and decision on treatment option in primary immune thrombocytopenia (ITP) patients remains unclear. Data from 725 patients diagnosed with ITP were analyzed to elucidate the association between anti-HBc serological status and disease severity. Data from a published prospective study [high-dose dexamethasone (HD-DXM), HD-DXM plus recombinant human thrombopoietin, NCT01734044] and two retrospective studies (standard-dose and low-dose rituximab) were rearranged to evaluate the impact of anti-HBc serological status on the response and outcome to ITP-specific treatments and the risk of HBV reactivation related to these treatments. The prevalence of HBsAg- HBcAb+ and HBsAg- HBcAb- in ITP patients was 51·03% and 48·97% respectively. Compared to the HBsAg- HBcAb- group, patients in the HBsAg- HBcAb+ group had lower platelet count, higher bleeding score, and longer hospitalization (P = 0·002, 0·033, and 0·008 respectively). Moreover, the initial complete response rate of HBsAg- HBcAb+ patients was lower than that of HBsAg- HBcAb- patients (45·2% vs 59·8%, P = 0·027). In conclusion, previous HBV exposure was correlated with disease severity and hospitalization in ITP patients. Anti-HBc positivity may be considered as a predictor for poor response to ITP-specific treatments.

Physiological, Metabolic, and Transcriptomic Analyses Reveal the Responses of Arabidopsis Seedlings to Carbon Nanohorns.

Carbon-based nanomaterials have potential applications in nanoenabled agriculture. However, the physiological and molecular mechanisms underlying single-walled carbon nanohorn (SWCNH)-mediated plant growth remain unclear. Here, we investigated the effects of SWCNHs on Arabidopsis grown in 1/4-strength Murashige and Skoog medium via physiological, genetic, and molecular analyses. Treatment with 0.1 mg/L SWCNHs promoted primary root (PR) growth and lateral root (LR) formation; 50 and 100 mg/L SWCNHs inhibited PR growth. Treatment with 0.1 mg/L SWCNHs increased the lengths of the meristematic and elongation zones, and transcriptomic and genetic analyses confirmed the positive effects of SWCNHs on root tip stem cell niche activity and meristematic cell division potential. Increased expression of YUC3 and YUC5 and increased PIN2 abundance improved PR growth and LR development in 0.1 mg/L SWCNH-treated seedlings. Metabolomic analyses revealed that SWCNHs altered the levels of sugars, amino acids, and organic acids, suggesting that SWCNHs reprogrammed carbon/nitrogen metabolism in plants. SWCNHs also regulate plant growth and development by increasing the levels of several secondary metabolites; transcriptomic analyses further supported these results. The present results are valuable for continued use of SWCNHs in agri-nanotechnology, and these molecular approaches could serve as examples for studies on the effects of nanomaterials in plants.

Comparative Physiological and Transcriptomic Analyses Reveal the Toxic Effects of ZnO Nanoparticles on Plant Growth.

Zinc oxide (ZnO) nanoparticles (nZnO) are among the most commonly used nanoparticles (NPs), and they have been shown to have harmful effects on plants. However, the molecular mechanisms underlying nZnO tolerance and root sensing of NP stresses have not been elucidated. Here, we compared the differential toxic effects of nZnO and Zn2+ toxicity on plants during exposure and recovery using a combination of transcriptomic and physiological analyses. Although both nZnO and Zn2+ inhibited primary root (PR) growth, nZnO had a stronger inhibitory effect on the growth of elongation zones, whereas Zn2+ toxicity had a stronger toxic effect on meristem cells. Timely recovery from stresses is critical for plant survival. Despite the stronger inhibitory effect of nZnO on PR growth, nZnO-exposed plants recovered from stress more rapidly than Zn2+-exposed plants upon transfer to normal conditions, and transcriptome data supported these results. In contrast to Zn2+ toxicity, nZnO induced endocytosis and caused microfilament rearrangement in the epidermal cells of elongation zones, thereby repressing PR growth. nZnO also repressed PR growth by disrupting cell wall organization and structure through both physical interactions and transcriptional regulation. The present study provides new insight into the comprehensive understanding and re-evaluation of NP toxicity in plants.