Results 181 to 190 of about 45,027 (295)

Identification of a New Interesting BAG3 Modulator Able to Disrupt Cancer‐Related Pathways

ChemMedChem, Accepted Article.
Continuing our research aimed at discovering new BAG3 modulators as attractive anticancer drug candidates, we performed a screening campaign on an in‐house library, including compounds featuring a large variety of scaffolds. The obtained results induced us to focus on the triazole moiety and, following a stepwise structural refinement of the scaffold ...
Dafne Ruggiero, Eleonora Boccia, Emis Ingenito, Vincenzo Vestuto, Gilda D’Urso, Alessandra Capuano, Agostino Casapullo, Stefania Terracciano, Giuseppe Bifulco, Gianluigi Lauro, Ines Bruno   +10 more
wiley   +1 more source

Evaluation of the Impact of Digital Dentistry on the Precision of Implant Placement and Prosthesis Fabrication: An In-Vitro Study. [PDF]

Cureus
Sonkesriya S, Kulkarni R, Satapathy SK, Fathima S, Thomas V, Gangadharappa P.   +5 more
europepmc   +1 more source

Machine Learning–Driven Screening of High‐Activity Antitumor Nanozymes Using an Ensemble Enzymatic Oracle System

Cancer Nexus, EarlyView.
ABSTRACT Nanozymes, by mimicking the catalytic sites of natural enzymes, have emerged as effective substitutes for traditional natural enzymes. However, the relationship between the physicochemical properties and activity of nanozymes is complex and nonlinear.
Guanmeng Zhang, Mutian Yang, Jie Zang, Xiaoli Li, Qinqiu Zhong, Yuxiang Hu, Yumeng Xie, Ludan Zhang, Yuping Qian, Jinna Ren, Yang Peng, Haitao Chen, Jiandong Gao, Ji Wu, Yuguang Wang   +14 more
wiley   +1 more source

Assessment of Digital Dentistry Knowledge and Practices Among Dental Students at King Faisal University, Saudi Arabia. [PDF]

Med Sci Monit
Umer MF, Faheemuddin M, Alshehri YA, Algosaibi AA, Alojail AA, Althani AA, Alnaim MA, Alharbi SA.   +7 more
europepmc   +1 more source

Classifying the Natural Tooth Color Spaces of Different Ethnic Groups

Color Research &Application, EarlyView.
ABSTRACT This study aimed to classify the natural tooth color spaces of various ethnic groups and assess the coverage error (CE) of the Vita 3D‐Master shade guide. A sample of 490 volunteers from five ethnic backgrounds participated, with inclusion criteria set for adults aged 20– to 45 with healthy, correctly aligned natural teeth free of restorations.
Omnia Saleh, Sascha Hein, Stephen Westland, Mayumi Maesako, Akimasa Tsujimoto, Konstantinos Michalakis   +5 more
wiley   +1 more source

The digital era in dentistry

Journal of Contemporary Clinical Practice, 2019
openaire   +2 more sources

Digitalization of Access to Primary Care: Is There an Equity‐Efficiency Trade‐Off?

Health Economics, EarlyView.
ABSTRACT In the English National Health Service, most patients can use an online platform to send a written request to the practice, in addition to calling or visiting the practice in person. However, there are concerns that the availability of an online access route to primary care can adversely impact healthcare provision for older or lower ...
Daniela Rodrigues, Noemi Kreif, Ara Darzi, Mauricio Barahona, Erik Mayer   +4 more
wiley   +1 more source

The Role of Machine Learning to Detect Occult Neck Lymph Node Metastases in Early‐Stage (T1‐T2/N0) Oral Cavity Carcinomas

Head &Neck, EarlyView.
ABSTRACT Objective Oral cavity carcinomas (OCCs) represent roughly 50% of all head and neck cancers. The risk of occult neck metastases for early‐stage OCCs ranges from 15% to 35%, hence the need to develop tools that can support the diagnosis of detecting these neck metastases.
Stefania Troise, Lorenzo Ugga, Maria Esposito, Maria Positano, Andrea Elefante, Serena Capasso, Renato Cuocolo, Raffaele Merola, Umberto Committeri, Vincenzo Abbate, Paola Bonavolontà, Riccardo Nocini, Giovanni Dell’Aversana Orabona   +12 more
wiley   +1 more source

Saliva MicroAge: A salivary microbiome based machine learning model for noninvasive aging assessment and health state prediction

iMetaOmics, EarlyView.
Saliva MicroAge is a machine learning‐based model designed to estimate biological age and assess health status using globally sourced salivary microbiome data. Trained on 4532 healthy samples, the model achieves high accuracy in predicting chronological age and captures health‐related deviations (MicroAgeGap) in various diseases.
Tiansong Xu, Yuting Niu, Chenyu Deng, Yoo Cheung, Yuman Li, Zhewen Hu, Shiyu Sun, Yiming Chen, Fan He, Gai Yang, Feng Chen, Chenggang Duan, Ying Huang, Xuliang Deng   +13 more
wiley   +1 more source

15‐Point versus pass/fail grading in orthodontic education: A randomized controlled trial

Journal of Dental Education, EarlyView.
Abstract Objectives There is a lack of evidence on whether a grading system or a pass/fail system influences manual skills in dental education. This parallel‐group randomized controlled trial aimed to assess the influence of a 15‐point grading system compared with a pass/fail evaluation on the quality of orthodontic appliances in dental education ...
Marina Julia Bialas, Jonas Q. Schmid, Claudius Middelberg, Thomas Stamm, Moritz Blanck‐Lubarsch   +4 more
wiley   +1 more source