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Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to investigate trimethoprim (TMP) resistance in the key pathogen Streptococcus pneumoniae . We explored a collection of 662 S . pneumoniae genomes by conducting a genome-wide association study (GWAS), followed by functional validation using resistance reconstruction experiments, combined with machine learning (ML) approaches to predict TMP minimum inhibitory concentration (MIC). Our study showed that multiple additive mutations in the folA and sulA loci are responsible for TMP non-susceptibility in S. pneumoniae and can be used as key features to build ML models for digital MIC prediction, reaching an average accuracy within ±1 twofold dilution factor of 86.3%. Our roadmap of in silico analysis-wet-lab validation-diagnostic tool building could be adapted to explore AMR in other combinations of bacteria-antibiotic., Importance: In the age of next-generation sequencing (NGS), while data-driven methods such as genome-wide association study (GWAS) and machine learning (ML) excel at finding patterns, functional validation can be challenging due to the high numbers of candidate variants. We designed an integrative approach combining a GWAS on S. pneumoniae clinical isolates, followed by whole-genome transformation coupled with NGS to functionally characterize a large set of GWAS candidates. Our study validated several phenotypic folA mutations beyond the standard Ile100Leu mutation, and showed that the overexpression of the sulA locus produces trimethoprim (TMP) resistance in Streptococcus pneumoniae . These validated loci, when used to build ML models, were found to be the best inputs for predicting TMP minimal inhibitory concentrations. Integrative approaches can bridge the genotype-phenotype gap by biological insights that can be incorporated in ML models for accurate prediction of drug susceptibility., Competing Interests: The authors declare no conflict of interest.

Light-emitting sources are currently used to activate the setting reaction of restorative composite resins. It is well known that the polymerization extent of the resins will highly influence their clinical behavior. The monomer-polymer transformation will mostly depend on the chemical nature of the photo-initiators used and on the luminous energy given by the curing device. The aims of this study were to characterize three light curing devices and to compare their efficiency to polymerize a composite resin (SureFil). For that purpose, the emission spectra and the irradiance of a plasma arc (Flipo), a QTH visible light (Elipar Trilight), and a LEDs curing device (Elipar Freelight) were measured. Then, the depth of cure and the Vickers hardness of composite samples were evaluated, for each curing device, as a function of the exposure time. The emission spectra obtained showed the irradiance of the visible light emitted as a function of the wavelength, which was different for each light-curing device. The maximum cured depth (approximately 4 mm) give only a qualitative indication of the extent of the polymerization, as the hardness of the composite samples diminished as a function of the depth. Moreover, it strongly depended on the exposure time. Hence, to obtain a hardness of approximately 100 HV 0.5 at 2 mm depth, the illumination time must be at least of 3 s with the plasma arc Flipo, 10 s with the LEDs Elipar Freelight and 20 s with the QTH Elipar Trilight. In order to efficiently polymerize a composite resin, the emission spectra of the luminous source shall correspond with the absorption spectra of the photo-initiators. The present study showed that the LEDs Elipar Freelight is the most efficient curing device when the camphorquinone is used, as 92% of the emitted energy will be absorbed by the initiator. However, the power of this source is relatively low, hence higher exposure time shall be used.

The objectives of this study were (1) to investigate the effect of operator variability on the shear bond strength of adhesives to dentin and (2) to determine the effectiveness of education on bonding performance for different types of adhesives. Thirty general practitioners were recruited for a CE course by a regional mailing. They used bovine dentin as a substrate for bonding the adhesive system they routinely used in practice and two other materials (no previous experience). Each adhesive OptiBond FL, ScotchBond Multipurpose Plus, ScotchBond 1 and Clearfil SE was applied according to manufacturer's instructions and immediately tested using a shear bond strength test. Shear bond strengths between adhesives and dentin were compared before and after a 90 min lecture on bonding principles and materials. For dentists with and without previous experience with a material, there were no statistically significant differences seen before and after the lecture (paired t-tests, p < or = 0.05). However, in every case, the bond strengths after the lecture were higher than those before (range of improvement from 15 to 150%). For dentists with routine experience with a particular material, all materials were statistically equivalent after the lecture, although the OptiBond FL was the highest. For dentists who had no previous experience with a material, the ScotchBond 1 had lower bond strengths than the other materials after the lecture. There was a large range in the ability of dentists to manipulate adhesive systems correctly. However, if a dentist has sufficient experience and receives sufficient education, any of these materials can give reasonable results.