Antifouling and toxic properties of the bioactive metabolites from the seagrasses Syringodium isoetifolium and Cymodocea serrulata

International audienceThe present study documents the antifouling and toxic properties of seagrasses Syringodium isoetifolium and Cymodocea serrulata. For that, the seagrasses S. isoetifolium and C. serrulata were extracted individually using organic solvents viz. dichloromethane, acetone and methanol. Amongst the extracts, the maximum antimicrofouling and antimacrofouling activities were exhibited by methanol extracts of both the seagrasses. The Minimal Inhibitory Concentration (MIC) of methanolic extracts of seagrasses was ranged from 1.0 to 10 mu g/ml against test biofilm bacteria and microalgal strains. Similarly, 100% fouling inhibition of limpet Patella vulgata was found at 6.0 mg/ml of methanolic extracts of seagrasses. The mussel Perna indica showed 50% of byssal production and attachment inhibition at 21.51 +/- 2.03, 17.82 +/- 1.07 mu g/ml and the anticrustaecean activity for 50% mortality of Anemia sauna was recorded at 732.14 +/- 921 and 394.16 +/- 5.16 mu g/ml respectively for methanolic extracts of S. isoetifolium and C serrulata. The minimal inhibitory and higher lethal concentrations of active methanol extracts shows it's less toxic nature. Based on the prolific results, methanol extracts of S. isoetifolium and C serrulata were subjected to purification using silica gel column and thin layer chromatography. Then the active compounds of the bioassay guided fractions were partially characterized using gas chromatography coupled with mass spectroscopy (GC-MS) and keyed out that fatty acids (C-16 to C-24) were the major components which responsible for the antifouling properties of the candidate seagrasse

Assessing dentists’ awareness of the orthodontic–restorative interface

Objectives: Awareness of the interface between restorative and orthodontic treatments is essential for dentists to facilitate a meaningful interdisciplinary approach by integrating the knowledge and skills of different dental disciplines into patients' treatment to enhance outcomes. The aim of this study was to investigate General Dental Practitioners' (GDPs) awareness of the orthodontic-restorative interface. Methods: This was a mixed-method study involving the collection of a) quantitative data via a bespoke online questionnaire and b) qualitative data through open questions. A weblink was created to the questionnaire using Opinio®. The questionnaire was distributed to GDPs practising in the UK. Clinical vignette-based questions assessed GDPs awareness and the results were categorised into two groups: aware and unaware. Two months after the primary survey, respondents were sent an email with follow-up (reliability) survey. Reliability responses were compared against the primary responses to assess the repeatability using intraclass correlation coefficient. Data were analysed using independent t-test and X2 test. Results: 118 complete responses were received. 63 GDPs (53.4 % [95 % CI 44 %-63 %]) demonstrated a good understanding of the orthodontic-restorative interface. These GDPs were characterised by greater age (t = 2.75, p = 0.007) and experience (t = 3.54, p Conclusions: Orthodontic-restorative treatment aids in minimal invasive dentistry. GDPs lack adequate awareness of the orthodontic-restorative interface in relation to patient care and communication with patients. More quality and structured undergraduate and postgraduate training are imperative to facilitate GDPs to understand and utilise aspects of orthodontic-restorative treatments to raise the standard of patient care. Additionally, to support these patients, the educational pathway between GDPs and specialist orthodontists is crucial. Clinical significance: GDPs ability to assess and carry out orthodontic-restorative treatments would conserve natural teeth. Dependable access to orthodontic services would encourage GDPs to refer challenging cases to specialists or dentists with enhanced skills. When the circumstances call for it, patients should be given orthodontic-restorative alternatives, regardless of the potential consequences of their acceptance of the procedures</p

Early diagnosis and meta-agnostic model visualization of tuberculosis based on radiography images

Abstract Despite being treatable and preventable, tuberculosis (TB) affected one-fourth of the world population in 2019, and it took the lives of 1.4 million people in 2019. It affected 1.2 million children around the world in the same year. As it is an infectious bacterial disease, the early diagnosis of TB prevents further transmission and increases the survival rate of the affected person. One of the standard diagnosis methods is the sputum culture test. Diagnosing and rapid sputum test results usually take one to eight weeks in 24 h. Using posterior-anterior chest radiographs (CXR) facilitates a rapid and more cost-effective early diagnosis of tuberculosis. Due to intraclass variations and interclass similarities in the images, TB prognosis from CXR is difficult. We proposed an early TB diagnosis system (tbXpert) based on deep learning methods. Deep Fused Linear Triangulation (FLT) is considered for CXR images to reconcile intraclass variation and interclass similarities. To improve the robustness of the prognosis approach, deep information must be obtained from the minimal radiation and uneven quality CXR images. The advanced FLT method accurately visualizes the infected region in the CXR without segmentation. Deep fused images are trained by the Deep learning network (DLN) with residual connections. The largest standard database, comprised of 3500 TB CXR images and 3500 normal CXR images, is utilized for training and validating the recommended model. Specificity, sensitivity, Accuracy, and AUC are estimated to determine the performance of the proposed systems. The proposed system demonstrates a maximum testing accuracy of 99.2%, a sensitivity of 98.9%, a specificity of 99.6%, a precision of 99.6%, and an AUC of 99.4%, all of which are pretty high when compared to current state-of-the-art deep learning approaches for the prognosis of tuberculosis. To lessen the radiologist’s time, effort, and reliance on the level of competence of the specialist, the suggested system named tbXpert can be deployed as a computer-aided diagnosis technique for tuberculosis

Effect of plant compounds on induced activities of defense-related enzymes and pathogenesis related protein in bacterial blight disease susceptible rice plant

Induction of resistance to control bacterial blight in rice was studied after treatment with various plant extracts by measuring activities of polyphenol oxidase (PPO), peroxidase (PO), β-1,3-glucanase and a pathogen related (PR) protein. Extracts of four plants (Azardirachta indica, Ages mermelos, Cassia auriculata and . Vitex negundo) against bacterial blight were analyzed. Bacterial blight was more effectively controlled by the water and methanol extracts of V. negundo than the other plant extracts. The extracts induced the defense related enzymes such as PPO, PO and β-1,3-glucanase in both pre and post inoculation of Xanthomonas oryzae. The pathogenesis related (PR) protein bands were clearly visible at 33 kDa and 14 kDa in methanol and water extract treated leaves of V. negundo. Elevated enzyme activities and PR protein levels indicate that defense enzymes are responsible for the control the bacterial blight disease rather than antagonism by extracts. The methanol and water extracts of V. negundo suppressed the bacterial blight disease about 73% and 76% over control respectively, under field condition. The plants grown in extract-treated plots were healthy and their leaf surface area was found to be higher than the control and standard V. negundo effectively controlled the bacterial blight disease under . in vitro and in vivo conditions through induced systemic resistance which can be used as an effective biocontrol agent in rice field. © 2012 Elsevier Ltd