Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.5
Journals
Applied Sciences
Special Issues
Advanced Materials in Implant Dentistry and Regenerative Medicine
applsci-logo
Submit to Applied Sciences Review for Applied Sciences Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advanced Materials in Implant Dentistry and Regenerative Medicine

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (10 September 2021) | Viewed by 4662

Special Issue Editors

Dr. Federico Berton

E-Mail Website
Guest Editor
Department of Medicine, Surgery and Health Sciences, University of Trieste, 34127 Trieste, Italy
Interests: maxillary sinus elevation; bone regeneration; graft materials; oral surgery; periodontal surgery; implant surgery; tooth extraction
Prof. Dr. Roberto Di Lenarda

E-Mail Website
Guest Editor
Department of Medicine, Surgery and Health Sciences, University of Trieste, 34127 Trieste, Italy
Interests: periodontal research; oral implantology; regenerative surgery; maxillary sinus elevation

Special Issue Information

Dear Colleagues,

Given the increasing amount of acquired knowledge regarding the biology beneath the regenerative process into the maxillary sinus cavity, new perspectives in regenerative surgery and implant surgery may be investigated. However, since the findings of the last 5 years, several concepts and principles regarding the choice of a graft material, the surgical technique, and the pattern of graft resorption should be rediscussed and further investigated. The choice of the right graft material according to the anatomical conditions, the timing of implant placement, and the crestal or lateral or even unconventional approaches deserve more investigation. These are necessary to assess the predictability of the therapy and to help patients and clinicians to reach the most reliable approach. Therefore, it is my immense pleasure to invite you who are facing the “maxillary sinus challenge” to submit your work to this Special Issue on “Advanced Materials in Implant Dentistry and Regenerative Medicine” addressing any aspect of sinus biology for bone regeneration, surgical approaches, and grafting materials, including in vitro and in vivo studies.

Dr. Federico Berton
Prof. Dr. Roberto Di Lenarda
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • graft materials
  • maxillary sinus elevation
  • maxillary sinus biology
  • bone regeneration
  • endosseous implants
  • scaffolds
  • sinus width
  • crestal approach
  • lateral approach

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 1379 KiB  
Article
Evaluation of Sambucus nigra L. Biopotential as an Unused Natural Resource
by Marija Radojković, Milena Vujanović, Tatjana Majkić, Gokhan Zengin, Ivana Beara, Michelina Catauro and Domenico Montesano
Appl. Sci. 2021, 11(23), 11207; https://doi.org/10.3390/app112311207 - 25 Nov 2021
Cited by 9 | Viewed by 1992
Abstract
An unbreakable relationship between plants, nutrition, and health has directed researchers to deeply investigate and characterize the biopotential and medicinal properties of traditional foods. The aim of this study is to analyze and compare the phytochemical composition and biological potential of plant extracts [...] Read more.
An unbreakable relationship between plants, nutrition, and health has directed researchers to deeply investigate and characterize the biopotential and medicinal properties of traditional foods. The aim of this study is to analyze and compare the phytochemical composition and biological potential of plant extracts with the idea of defining the most potent extracts as a natural source of bioactive molecules and their application in different industries. We evaluated unused plant species Sambucus nigra L. for investigation of bioactivities as potential natural products. Extracts of fresh elderberry fruits were obtained by modern (microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE)) and traditional (maceration (MAC)) extraction techniques, using 50% ethanol (50% EtOH) and water (H2O) of different polarities. In analyzed extracts, rutin and chlorogenic acid were dominant compounds in both 50% EtOH and H2O extracts, while ursolic acid was identified in 50% EtOH extracts as a terpenic compound with notable concentration. Elderberry extracts were evaluated regarding antioxidant, neuroprotective, antityrosinase, and antidiabetic abilities: MAE extracts had the best overall activity, and in general, 50% EtOH extracts were more potent than water extracts. The correlation of the dominant compound—rutin with all biological activities, indicates the importance of its presence in elderberries. S. nigra fruits showed excellent biopotential and opened possibilities of creating new food products or remedies, which are not present on the market because elderberry extracts are an exceptional source of rutin, chlorogenic acid, and ursolic acid. Full article
(This article belongs to the Special Issue Advanced Materials in Implant Dentistry and Regenerative Medicine)
►▼ Show Figures

Figure 1

18 pages, 22286 KiB  
Article
The Ensembles of Machine Learning Methods for Survival Predicting after Kidney Transplantation
by Yaroslav Tolstyak, Rostyslav Zhuk, Igor Yakovlev, Nataliya Shakhovska, Michal Gregus ml, Valentyna Chopyak and Nataliia Melnykova
Appl. Sci. 2021, 11(21), 10380; https://doi.org/10.3390/app112110380 - 5 Nov 2021
Cited by 8 | Viewed by 2060
Abstract
Machine learning is used to develop predictive models to diagnose different diseases, particularly kidney transplant survival prediction. The paper used the collected dataset of patients’ individual parameters to predict the critical risk factors associated with early graft rejection. Our study shows the high [...] Read more.
Machine learning is used to develop predictive models to diagnose different diseases, particularly kidney transplant survival prediction. The paper used the collected dataset of patients’ individual parameters to predict the critical risk factors associated with early graft rejection. Our study shows the high pairwise correlation between a massive subset of the parameters listed in the dataset. Hence the proper feature selection is needed to increase the quality of a prediction model. Several methods are used for feature selection, and results are summarized using hard voting. Modeling the onset of critical events for the elements of a particular set is made based on the Kapplan-Meier method. Four novel ensembles of machine learning models are built on selected features for the classification task. Proposed stacking allows obtaining an accuracy, sensitivity, and specifity of more than 0.9. Further research will include the development of a two-stage predictor. Full article
(This article belongs to the Special Issue Advanced Materials in Implant Dentistry and Regenerative Medicine)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop