The c4 atriplex halimus vs. The c3 atriplex hortensis: Similarities and differences in the salinity stress response

open7noSoil properties and the ability to sustain agricultural production are seriously impaired by salinity. The cultivation of halophytes is seen as a solution to cope with the problem. In this framework, a greenhouse pot experiment was set up to assess salinity response in the perennial C4 species Atriplex halimus, and in the following three cultivars of the annual C3 Atriplex hortensis: green, red, and scarlet. The four genotypes were grown for 35 days with water salinity (WS) ranging from 0 to 360 mM NaCl. Plant height and fresh weight (FW) increased at 360 vs. 0 WS. The stomatal conductance (GS) and transpiration rate (E) were more severely affected by salinity in the C4 A. halimus than in the C3 species A. hortensis. This was reflected in a lower leaf water potential indicating stronger osmotic adjustment, and a higher relative water content associated with more turgid leaves, in A. halimus than A. hortensis. In a PCA including all the studied traits, the GS and E negatively correlated to the FW, which, in turn, positively correlated with Na concentration and intrinsic water use efficiency (iWUE), indicating that reduced gas exchange associated with Na accumulation contributed to sustain iWUE under salinity. Finally, FTIR spectroscopy showed a reduced amount of pectin, lignin, and cellulose under salinity, indicating a weakened cell wall structure. Overall, both species were remarkably adapted to salinity: From an agronomic perspective, the opposite strategies of longer vs. faster soil coverage, involved by the perennial A. halimus vs. the annual A. hortensis cv. scarlet, are viable natural remedies for revegetating marginal saline soils and increasing soil organic carbon.openCalone R.; Cellini A.; Manfrini L.; Lambertini C.; Gioacchini P.; Simoni A.; Barbanti L.Calone R.; Cellini A.; Manfrini L.; Lambertini C.; Gioacchini P.; Simoni A.; Barbanti L

Prognostication for oral carcinomas based on two histological scoring systems (BD and iBD models)

Peer reviewe

Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer

Background: The proper estimate of the risk of recurrences in early-stage oral tongue squamous cell carcinoma (OTSCC) is mandatory for individual treatment-decision making. However, this remains a challenge even for experienced multidisciplinary centers. Objectives: We compared the performance of four machine learning (ML) algorithms for predicting the risk of locoregional recurrences in patients with OTSCC. These algorithms were Support Vector Machine (SVM), Naive Bayes (NB), Boosted Decision Tree (BDT), and Decision Forest (DF). Materials and methods: The study cohort comprised 311 cases from the five University Hospitals in Finland and A.C. Camargo Cancer Center, Sao Paulo, Brazil. For comparison of the algorithms, we used the harmonic mean of precision and recall called F1 score, specificity, and accuracy values. These algorithms and their corresponding permutation feature importance (PFI) with the input parameters were externally tested on 59 new cases. Furthermore, we compared the performance of the algorithm that showed the highest prediction accuracy with the prognostic significance of depth of invasion (DOI). Results: The results showed that the average specificity of all the algorithms was 71% The SVM showed an accuracy of 68% and F1 score of 0.63, NB an accuracy of 70% and F1 score of 0.64, BDT an accuracy of 81% and F1 score of 0.78, and DF an accuracy of 78% and F1 score of 0.70. Additionally, these algorithms outperformed the DOI-based approach, which gave an accuracy of 63%. With PFI-analysis, there was no significant difference in the overall accuracies of three of the algorithms; PFI-BDT accuracy increased to 83.1%, PFI-DF increased to 80%, PFI-SVM decreased to 64.4%, while PFI-NB accuracy increased significantly to 81.4%. Conclusions: Our findings show that the best classification accuracy was achieved with the boosted decision tree algorithm. Additionally, these algorithms outperformed the DOI-based approach. Furthermore, with few parameters identified in the PFI analysis, ML technique still showed the ability to predict locoregional recurrence. The application of boosted decision tree machine learning algorithm can stratify OTSCC patients and thus aid in their individual treatment planning.Peer reviewe

Improved salinity tolerance in early growth stage of maize through salicylic acid foliar application

Soil salinity threatens agricultural production worldwide by constraining plant growth and final crop yield. The early stages are most sensitive to salinity, in response to which salicylic acid (SA) has demonstrated beneficial effects in various plant species. Based on this, a maize (Zea mays L.) pot experiment was set up combining three levels of soil salinity (0, 6 and 12 dS m–1), obtained through NaCl addition, with three levels of SA (0, 300 and 600 mM), applied by leaf spraying 20 days after seedling emergence. Fifteen days later, the following traits were assessed: morphology (plant height, leaf number), growth (root and shoot dry weight), leaf water status [relative water content (RWC), elec-trolyte leakage (EL)], pigments (chlorophyll a and b, carotenoids, anthocyanin), antioxidant enzymes (peroxidase, catalase, ascor-bate peroxidase, vitamin C), oxidative stress markers (H2O2, mal-ondialdehyde), osmo-regulating compounds (free amino acids, soluble proteins and sugars, proline), hormones [indole-3-acetic acid, gibberellic acid (GA), abscisic acid (ABA), ethylene], ele-ment (Na, K, Ca, Mg and Cl) concentration and content in roots, stem and leaves. Salinity severely affected maize growth (–26% total dry weight), impaired leaf water status (–31% RWC), reduced photosynthetic pigments, enhanced all antioxidant enzymes and oxidative stress markers, two osmo-regulating compounds (soluble sugars and proline) out of four, and all hormones except GA. SA was shown effective in containing most of the stress effects, while supporting plant defences by upgrading anti-oxidant activities (reduced oxidative stress markers), increasing cell membrane stability (–24% EL) and leaf water status (+20% RWC), and reducing plant stress signalling (–10% ABA and –20% ethylene). Above all, SA contrasted the massive entry of noxious ions (Na+ and Cl–), in favour of K+, Ca2+ and Mg2+ accumulation. Lastly, salicylic acid was shown beneficial for maize growth and physiology also under non-saline condition, suggesting a potential use in normal field conditions

Secretome profiling of oral squamous cell carcinoma-associated fibroblasts reveals organization and disassembly of extracellular matrix and collagen metabolic process signatures

An important role has been attributed to cancer-associated fibroblasts (CAFs) in the tumorigenesis of oral squamous cell carcinoma (OSCC), the most common tumor of the oral cavity. Previous studies demonstrated that CAF-secreted molecules promote the proliferation and invasion of OSCC cells, inducing a more aggressive phenotype. In this study, we searched for differences in the secretome of CAFs and normal oral fibroblasts (NOF) using mass spectrometry-based proteomics and biological network analysis. Comparison of the secretome profiles revealed that upregulated proteins involved mainly in extracellular matrix organization and disassembly and collagen metabolism. Among the upregulated proteins were fibronectin type III domain-containing 1 (FNDC1), serpin peptidase inhibitor type 1 (SERPINE1), and stanniocalcin 2 (STC2), the upregulation of which was validated by quantitative PCR and ELISA in an independent set of CAF cell lines. The transition of transforming growth factor beta 1 (TGF-beta 1)-mediating NOFs into CAFs was accompanied by significant upregulation of FNDC1, SERPINE1, and STC2, confirming the participation of these proteins in the CAF-derived secretome. Type I collagen, the main constituent of the connective tissue, was also associated with several upregulated biological processes. The immunoexpression of type I collagen N-terminal propeptide (PINP) was significantly correlated in vivo with CAFs in the tumor front and was associated with significantly shortened survival of OSCC patients. Presence of CAFs in the tumor stroma was also an independent prognostic factor for OSCC disease-free survival. These results demonstrate the value of secretome profiling for evaluating the role of CAFs in the tumor microenvironment and identify potential novel therapeutic targets such as FNDC1, SERPINE1, and STC2. Furthermore, type I collagen expression by CAFs, represented by PINP levels, may be a prognostic marker of OSCC outcome.Peer reviewe

Machine learning application for prediction of locoregional recurrences in early oral tongue cancer: a Web-based prognostic tool

Estimation of risk of recurrence in early-stage oral tongue squamous cell carcinoma (OTSCC) remains a challenge in the field of head and neck oncology. We examined the use of artificial neural networks (ANNs) to predict recurrences in early-stage OTSCC. A Web-based tool available for public use was also developed. A feedforward neural network was trained for prediction of locoregional recurrences in early OTSCC. The trained network was used to evaluate several prognostic parameters (age, gender, T stage, WHO histologic grade, depth of invasion, tumor budding, worst pattern of invasion, perineural invasion, and lymphocytic host response). Our neural network model identified tumor budding and depth of invasion as the most important prognosticators to predict locoregional recurrence. The accuracy of the neural network was 92.7%, which was higher than that of the logistic regression model (86.5%). Our online tool provided 88.2% accuracy, 71.2% sensitivity, and 98.9% specificity. In conclusion, ANN seems to offer a unique decision-making support predicting recurrences and thus adding value for the management of early OTSCC. To the best of our knowledge, this is the first study that applied ANN for prediction of recurrence in early OTSCC and provided a Web-based tool.</p

Fascin promotes migration and invasion and is a prognostic marker for oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) prognosis is related to clinical stage and histological grade. However, this stratification needs to be refined. We conducted a comparative proteome study in microdissected samples from normal oral mucosa and OSCC to identify biomarkers for malignancy. Fascin and plectin were identified as differently expressed and both are implicated in several malignancies, but the clinical impacts of aberrant fascin and plectin expression in OSCCs remains largely unknown. Immunohistochemistry and real-time quantitative PCR were carried out in ex vivo OSCC samples and cell lines. A loss-of-function strategy using shRNA targeting fascin was employed to investigate in vitro and in vivo the fascin role on oral tumorigenesis. Transfections of microRNA mimics were performed to determine whether the fascin overexpression is regulated by miR-138 and miR-145. We found that fascin and plectin are frequently upregulated in OSCC samples and cell lines, but only fascin overexpression is an independent unfavorable prognostic indicator of disease-specific survival. In combination with advanced T stage, high fascin level is also an independent factor of disease-free survival. Knockdown of fascin in OSCC cells promoted cell adhesion and inhibited migration, invasion and EMT, and forced expression of miR-138 in OSCC cells significantly decreased the expression of fascin. In addition, fascin downregulation leads to reduced filopodia formation and decrease on paxillin expression. The subcutaneous xenograft model showed that tumors formed in the presence of low levels of fascin were significantly smaller compared to those formed with high fascin levels. Collectively, our findings suggest that fascin expression correlates with disease progression and may serve as a prognostic marker and therapeutic target for patients with OSCC.Peer reviewe

Stanniocalcin 2 contributes to aggressiveness and is a prognostic marker for oral squamous cell carcinoma

Stanniocalcin 2 (STC2), a glycoprotein that regulates calcium and phosphate homeostasis during mineral metabolism, appears to display multiple roles in tumorigenesis and cancer progression. This study aimed to access the prognostic value of STC2 in oral squamous cell carcinoma (OSCC) and its implications in oral tumorigenesis. STC2 expression was examined in 2 independent cohorts of OSCC tissues by immunohistochemistry. A loss-of-function strategy using shRNA targeting STC2 was employed to investigate STC2 in vitro effects on proliferation, apoptosis, migration, invasion, epithelial-mesenchymal transition (EMT) and possible activation of signaling pathways. Moreover, STC2 effects were assessed in vivo in a xenograft mouse cancer model. High expression of STC2 was significantly associated with poor disease-specific survival (HR: 2.67, 95% CI: 1.37-5.21, p = 0.001) and high rate of recurrence with a hazard ratio of 2.80 (95% CI: 1.07-5.71, p = 0.03). In vitro downregulation of STC2 expression in OSCC cells attenuated proliferation, migration and invasiveness while increased apoptotic rates. In addition, the STC2 downregulation controlled EMT phenotype of OSCC cells, with regulation on E-cadherin, vimentin, Snaill, Twist and Zeb2. The reactivation of STC2 was observed in the STC2 knockdown cells in the in vivo xenograft model, and no influence on tumor growth was observed. Modulation of STC2 expression levels did not alter consistently the phosphorylation status of CREB, ERK, JNK, p38, p70 S6K, STAT3, STAT5A/B and AKT. Our findings suggest that STC2 overexpression is an independent marker of OSCC outcome and may contribute to tumor progression via regulation of proliferation, survival and invasiveness of OSCC cells.Peer reviewe

Machine learning application for prediction of locoregional recurrences in early oral tongue cancer: a Web-based prognostic tool

Estimation of risk of recurrence in early-stage oral tongue squamous cell carcinoma (OTSCC) remains a challenge in the field of head and neck oncology. We examined the use of artificial neural networks (ANNs) to predict recurrences in early-stage OTSCC. A Web-based tool available for public use was also developed. A feedforward neural network was trained for prediction of locoregional recurrences in early OTSCC. The trained network was used to evaluate several prognostic parameters (age, gender, T stage, WHO histologic grade, depth of invasion, tumor budding, worst pattern of invasion, perineural invasion, and lymphocytic host response). Our neural network model identified tumor budding and depth of invasion as the most important prognosticators to predict locoregional recurrence. The accuracy of the neural network was 92.7%, which was higher than that of the logistic regression model (86.5%). Our online tool provided 88.2% accuracy, 71.2% sensitivity, and 98.9% specificity. In conclusion, ANN seems to offer a unique decision-making support predicting recurrences and thus adding value for the management of early OTSCC. To the best of our knowledge, this is the first study that applied ANN for prediction of recurrence in early OTSCC and provided a Web-based tool.Peer reviewe

Tumour budding in oral squamous cell carcinoma : a meta-analysis

Background: Tumour budding has been reported as a promising prognostic marker in many cancers. This meta-analysis assessed the prognostic value of tumour budding in oral squamous cell carcinoma (OSCC). Methods: We searched OvidMedline, PubMed, Scopus and Web of Science for articles that studied tumour budding in OSCC. We used reporting recommendations for tumour marker (REMARK) criteria to evaluate the quality of studies eligible for meta-analysis. Results: A total of 16 studies evaluated the prognostic value of tumour budding in OSCC. The meta-analysis showed that tumour budding was significantly associated with lymph node metastasis (odds ratio = 7.08, 95% CI = 1.75-28.73), disease-free survival (hazard ratio = 1.83, 95% CI = 1.34-2.50) and overall survival (hazard ratio = 1.88, 95% CI = 1.25-2.82). Conclusions: Tumour budding is a simple and reliable prognostic marker for OSCC. Evaluation of tumour budding could facilitate personalised management of OSCC.Peer reviewe