Necmettin Erbakan University

Objectives: To evaluate the fabrication trueness and adaptation of additively manufactured denture bases made from different resins and postprocessed with different cleaning solutions. Methods: An edentulous maxillary model was scanned to design a reference denture base file. This reference file was used to fabricate 96 denture bases from three resins (DB, DentaBASE; DT, Denturetec; FD, FREEPRINT Denture) that were cleaned with four solutions (MES, Weiton-3D Resin Cleaner; WBS, Print Cleaning Concentrate; BDS, Cleaning Fluid Bio; isopropyl alcohol [IPA]) (n = 8). All bases were scanned for digital deviation (external, intaglio, and overall root mean square) and adaptation (triple scan, average gap) analyses. Data were analyzed with two-way analysis of variance and Bonferroni-corrected post hoc tests (alpha = 0.05). Results: FD bases had the lowest and DT bases had the highest intaglio and overall deviations across tested solutions (P <= 0.017). DT bases also had the highest external deviations within WBS, BDS, and IPA (P < 0.001). IPA led to higher external and overall deviations than MES for DT bases (P = 0.001). DT bases exhibited the highest gaps, whereas BDS cleaning increased their gaps compared with MES and IPA cleaning (P <= 0.044). Conclusions: FD bases mostly had the highest and DT bases mostly had the lowest trueness. Tested cleaning solutions' effect on fabrication trueness was minimal and potentially clinically negligible. DT bases showed the poorest adaptation, irrespective of the solution.

Social responsibility-based practices have become crucial for the long-term growth of organizations. Empirical studies show that socially responsible human resource management (HRM) positively influences individual behavior; however, limited research investigates its role in mitigating negative employee attitudes and behaviors. Drawing on social exchange theory and self-determination theory, we investigate how and when socially responsible HRM affects knowledge sabotage among employees in the hospitality and tourism industry. We obtained 150 valid surveys from five-star hotel employees in Kyrgyzstan and 240 from hotel employees in T & uuml;rkiye and tested the hypotheses using PLS-SEM. The results show that socially responsible HRM reduces knowledge sabotage and increases workplace belongingness. Workplace belongingness is found to negatively affect knowledge sabotage. Our findings reveal that work belongingness mediates the influences of socially responsible human resource management on knowledge sabotage. More importantly, corporate ethical values strengthen the negative effect of socially responsible HRM on knowledge sabotage via work belongingness, thereby amplifying this impact further in the hospitality and tourism industry. This paper provides theoretical and practical implications for hospitality and tourism researchers and practitioners by demonstrating how socially responsible HRM reduces employee knowledge sabotage through psychological mechanisms and corporate values.

Poly(2-ethyl-2-oxazoline) (PEtOx) represents a versatile platform for developing supramolecular polymer systems. In this study, propargyl-terminated PEtOx was synthesized via cationic ring-opening polymerization and subsequently functionalized at the gamma-chain end with either adamantane or phenyl groups using thiol-yne click chemistry. Monoazide-functionalized beta-cyclodextrin (beta-CD-N-3) was then covalently conjugated to these polymers through Cu(I)-catalyzed azide-alkyne cycloaddition. Comprehensive characterization by 1H NMR, NOESY NMR, FTIR, GPC, and MALDI-TOF MS confirmed successful synthesis and precise end-group modifications. Notably, 2D NOESY NMR spectroscopy provided direct evidence of supramolecular host-guest interactions between the adamantane moiety and the beta-CD cavity in the P1/CD conjugate, while no significant inclusion complexation was observed for the phenyl-terminated counterpart (P2/CD), highlighting the critical influence of end-group identity on supramolecular complexation behavior in PEtOx-based systems. Overall, this work introduces a versatile strategy for designing supramolecular polymer architectures through end-group engineering and cyclodextrin conjugation, offering new perspectives for advanced functional materials with tunable self-assembly properties.

To systematically evaluate the diagnostic accuracy of artificial intelligence (AI) models in periapical radiography for detection, classification, and segmentation tasks compared to human experts, while critically appraising methodological quality and risk of bias. The systematic review was conducted in accordance with PRISMA guidelines and registered in PROSPERO (CRD420251132033). Strict exclusion criteria were applied to studies with insufficient dataset sizes (< 200 images) lacking augmentation, ambiguous reference standards, or reporting only accuracy without complementary metrics. A comprehensive literature search was conducted on June 23, 2025, across five electronic databases: PubMed/MEDLINE, Scopus, ScienceDirect, Web of Science, and IEEE Xplore. The search strategy combined keywords related to “periapical radiography” (e.g., periapical X-ray), “artificial intelligence” (e.g., deep learning, neural networks), and specific diagnostic tasks, with no restrictions on publication date or language. Studies utilizing artificial intelligence models for diagnostic tasks on periapical radiographs and validating performance against a human reference standard (expert consensus) were eligible for inclusion. Out of 544 identified records, 47 studies met the full eligibility criteria and were included in the qualitative synthesis. AI models possess a high diagnostic potential in periapical radiography, performing at a level comparable to human experts in tasks such as pathology detection, anatomical segmentation, and implant classification. However, their clinical applicability is currently limited by a high risk of bias, lack of external validation, reliance on cropped datasets, and the use of human consensus as a surrogate reference standard. Future research must prioritize full-arch evaluations, anatomical region-specific performance reporting, and adherence to AI-specific standardized metrics.

Amyloid fibrils derived from whey, pea, rice, and gluten proteins were evaluated as copigmentation agents to enhance the stability of anthocyanin-rich Hibiscus sabdariffa extracts. Fibrils were prepared via heat-induced self-assembly for 24, 36, or 48 h, and their effects on color enhancement and thermal stability were assessed using UV-Vis spectroscopy, FTIR, fluorescence, and kinetic modeling. The most effective samples combined high bathochromic and hyperchromic shifts with improved thermal stability. Among these, 36-h whey nanofibrils copigmented with hibiscus extract (36WH) exhibited the greatest bathochromic shift (6 nm) and the highest hyperchromic effect (33.84%), while 24-h whey nanofibrils copigmented with hibiscus extract (24WH) showed similarly high color enhancement (33.00%) along with high activation energy (E a: 103.54 kJ mol-1) and low degradation rates. The 24-h pea nanofibrils copigmented with hibiscus extract (24PH) achieved the highest E a (141.08 kJ mol-1), indicating exceptional thermal resistance. In addition, 36-h rice nanofibrils copigmented with hibiscus extract (36RH) displayed strong performance with an E a of 89.69 kJ mol-1 and a bathochromic shift of 4 nm, whereas 24-h gluten nanofibrils copigmented with hibiscus extract (24GH) had the highest z value (75.72 K), reflecting strong resistance to temperature changes. FTIR spectra confirmed hydrogen bonding and aromatic interactions, while fluorescence quenching from 100 to 1000 au to 3-5 au indicated strong pigment-protein binding. Overall, 24WH, 36WH, 24PH, 36RH, and 24GH emerged as the most promising fibril-pigment systems, offering significant color enhancement and/or thermal stability.