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Background. Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of morbidity and mortality worldwide, and its prevalence is rising. In Italy, respiratory diseases are the third most common cause of death. The aim of the study is to produce a patient information leaflet (PIL) designed to educate patients about COPD in accordance with the best recommendations based on evidence and guidelines for the production of good quality written information, and to evaluate the impact of this intervention on the patients’ knowledge of COPD. Methods. The study was conducted in the Department of Chest Diseases of the Cardarelli Hospital, Naples, Italy. A total of 166 patients admitted with a diagnosis of COPD participated in the study. Patients were asked to answer 10 multiple-choice questions compiled to assess their knowledge of the disease and then to read the leaflet. Two days later they were asked to complete the questionnaire again to assess their post-intervention knowledge. Analysis of the data was performed using SPSS version 15.0. Results. After reading the leaflet, a statistically significant increase in the proportion of correct responses was noted (p

Background:. ChatGPT, launched in 2022 and updated to Generative Pre-trained Transformer 4 (GPT-4) in 2023, is a large language model trained on extensive data, including medical information. This study compares ChatGPT’s performance on Plastic Surgery In-Service Examinations with medical residents nationally as well as its earlier version, ChatGPT-3.5. Methods:. This study reviewed 1500 questions from the Plastic Surgery In-service Examinations from 2018 to 2023. After excluding image-based, unscored, and inconclusive questions, 1292 were analyzed. The question stem and each multiple-choice answer was inputted verbatim into ChatGPT-4. Results:. ChatGPT-4 correctly answered 961 (74.4%) of the included questions. Best performance by section was in core surgical principles (79.1% correct) and lowest in craniomaxillofacial (69.1%). ChatGPT-4 ranked between the 61st and 97th percentiles compared with all residents. Comparatively, ChatGPT-4 significantly outperformed ChatGPT-3.5 in 2018–2022 examinations (P < 0.001). Although ChatGPT-3.5 averaged 55.5% correctness, ChatGPT-4 averaged 74%, a mean difference of 18.54%. In 2021, ChatGPT-3.5 ranked in the 23rd percentile of all residents, whereas ChatGPT-4 ranked in the 97th percentile. ChatGPT-4 outperformed 80.7% of residents on average and scored above the 97th percentile among first-year residents. Its performance was comparable with sixth-year integrated residents, ranking in the 55.7th percentile, on average. These results show significant improvements in ChatGPT-4’s application of medical knowledge within six months of ChatGPT-3.5’s release. Conclusion:. This study reveals ChatGPT-4’s rapid developments, advancing from a first-year medical resident’s level to surpassing independent residents and matching a sixth-year resident’s proficiency.

This work reports the preparation and testing of porous beds made from packed vinylated silica microparticles (SiMPs) grafted with thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) and exhibiting on demand thermally triggered permeability. PNIPAM-grafted hybrid SiMPs with diameters of 1.40–1.55 μm were synthesized and characterized with Attenuated Total Reflection Fourier Transform Infrared Spetroscopy (ATR-FTIR), Thermogravimetric Analysis (TGA), Flow Particle Image Analysis (FPIA) and Scannning Electron Miscroscopy (SEM) to elucidate their composition and morphology. The PNIPAM-grafted SiMPs were used to prepare thermoresponsive beds of dimensions 1×0.5×0.5 cm inside filtration tubes. The thermo-regulated permeability of solutions of selected model compounds, namely caffeine, ketoprofen, orange II, bromocresol green and cresol red across the hybrid beds was tested by calculating the retention percentage of the model compounds at temperatures below and above the lower critical solution temperature (LCST) of PNIPAM. The results showed a clear control over the permeability of the packed hybrid beds mediated by external temperature changes. This control was achieved by virtue of the switchable nanovalves created by the thermoresponsive PNIPAM present in the inter-particle voids of the packed beds.

A series of poly(N-isopropylacrylamide-co-acrylamide) thermoresponsive random copolymers with different molecular weights and composition were synthesized and characterized by attenuated total reflectance Fourier-transform infrared (ATR-FTIR), differential scanning calorimetry (DSC), size exclusion chromatography (SEC) and proton nuclear magnetic resonance (NMR) spectroscopy. The lower critical solution temperatures (LCST) of the copolymers were tuned by changing the mole ratios of monomers. Copolymer with highest molecular weight and LCST (41.2 °C) was grafted on SBA-15 type mesoporous silica particles by a two-step polymer grafting procedure. Bare SBA-15 and the thermoresponsive copolymergrafted (hybrid) SBA-15 particles were fully characterized by scanning electron microscope (SEM), ATR-FTIR, thermogravimetric analysis (TGA) and Brunauer-Emmett-Teller (BET) analyses. The hybrid particles were tested for their efficiency as temperature-sensitive systems for dermal delivery of the antioxidant rutin (quercetin-3-O-rutinoside). Improved control over rutin release by hybrid particles was obtained which makes them attractive hybrid materials for drug delivery.