Tag: pubmed

Heliyon. 2024 Nov 15;10(22):e40442. doi: 10.1016/j.heliyon.2024.e40442. eCollection 2024 Nov 30.

ABSTRACT

PURPOSE: Higher bending forces during chewing and occlusal loading can lead to the deformation of denture bases. Roughness and microbial adhesion can be the result of improper care of the denture. Many attempts have been made to improve the properties of denture bases through the addition of different materials. The present study aimed to evaluate the surface hardness and flexural strength (FS) of newly formulated nanocomposite denture base resin made by adding zinc oxide (ZnO) and titanium dioxide (TiO₂) nanoparticles in heat polymerized polymethyl methacrylate resin in concentrations of 1 % and 2 %.

METHODS: Rectangular metal master dies of dimension 65mm × 10mm × 3.3 mm for flexural strength and 30mm × 10mm × 3 mm for surface hardness were made. These dies were duplicated in 120 acrylic resin samples. These samples were divided into five groups in which group I is control group samples in conventional resin and group II,III, IV &V contained 1 % and 2 % concentrations of ZnO & TiO₂ nanoparticles in heat cure acrylic resin. The processing and finishing of the models were done. Flexural strength was measured using a universal testing machine and surface hardness using a Rockwell hardness testing machine.

RESULTS: The minimum SH reported was 101.7 HRM while FS was 81.1 MPa and maximum was 118.7 HRM and 131.8 MPa respectively. The results showed that group IV containing 1 % TiO₂ nanoparticles showed the highest surface hardness values whereas the flexural strength was highest in group II containing 1 % ZnO nanoparticles. The analysis of variance showed a p value of <0.001 which was statistically highly significant.

CONCLUSION: Nanocomposite denture base resins modified with ZnO & TiO₂ nanoparticles have more flexural strength and surface hardness than conventional denture base resin.

CLINICAL IMPLICATION: The hardness of a denture base material can be increased by adding these nanoparticles for long term use in oral cavity and in cases prone to denture fracture.

PMID:39641016 | PMC:PMC11617853 | DOI:10.1016/j.heliyon.2024.e40442

Clin Park Relat Disord. 2024 Nov 17;11:100284. doi: 10.1016/j.prdoa.2024.100284. eCollection 2024.

ABSTRACT

BACKGROUND: Dual-task (DT) performance is impaired in Parkinson’s disease (PD), contributing to bradykinesia, postural instability, freezing of gait, and falls. Tactile cueing, including vibrotactile stimulation, has been suggested to improve DT performance in PD.

RESEARCH QUESTION: Does tactile cueing affect DT performance in PD, specifically measured by dual-task cost (DTC)?

METHODS: A systematic review was conducted in PubMed and EMBASE up to October 30, 2023, following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Eligible studies were those in English that examined the effects of tactile cueing and/or closed-loop vibrotactile stimulation on DT performance in adults over 18 with idiopathic PD. The primary outcome, DTC, was calculated as the percentage change in performance from DT to single-task using the formula: [(single-task – dual-task)/single-task]* 100. A meta-analysis using a random-effects model pooled standardized mean differences (SMD) of DTC. Statistical significance was set at p < 0.05.

RESULTS: From 130 initially identified studies, eight were included in the review. Four studies with 374 participants were included in meta-analyses focusing on walking speed and step length. Three of the four studies indicated that tactile cueing improved DTC for these parameters. However, the SMD for walking speed (-109.69; 95 % CI -454.89 to 235.51, p = 0.39) and step length (-14.21; 95 %CI -53.25 to 24.83, p = 0.33) showed weak evidence of improvement.

CONCLUSION: The meta-analysis provides weak evidence that tactile cueing may enhance walking speed and step length in DT conditions in PD. Rigorous objective studies are still lacking in this field of research.

PMID:39640985 | PMC:PMC11617393 | DOI:10.1016/j.prdoa.2024.100284

Front Med (Lausanne). 2024 Nov 21;11:1472384. doi: 10.3389/fmed.2024.1472384. eCollection 2024.

ABSTRACT

OBJECTIVE: To construct a hierarchical management system for specialist nurses based on Patricia Benner’s theory, and evaluate its implement effect, so as to provide reference for the hierarchical management of specialist nurses.

METHODS: Literature retrieval, semi-structured interview and Delphi method were conducted for initially formulation of the draft of hierarchical management system for specialist nurses. Forty-three specialist nurses and 14 nursing managers were selected for the study, using a non-randomized controlled experimental study design, and at the end of the study, the job satisfaction, job engagement, job exuberance, advice behaviors and nursing managers’ overall job satisfaction of specialist nurses were compared before and after the hierarchical management.

RESULTS: This study constructed a hierarchical management system for specialist nurses. The differences in specialist nurses’ job satisfaction, job engagement, job exuberance and constructive behaviors before and after hierarchical management were statistically significant (p < 0.05), and the differences in the nursing managers’ assessment of specialist nurses’ overall job satisfaction were statistically significant (p < 0.05).

CONCLUSION: The hierarchical management system of specialist nurses based on Patricia Benner’s theory improves the quality of hierarchical management of specialist nurses, which could improve the job satisfaction of specialist nurses. The system could provide guidance and reference for hierarchical management system of specialist nurses.

PMID:39640983 | PMC:PMC11619138 | DOI:10.3389/fmed.2024.1472384

Front Med (Lausanne). 2024 Nov 21;11:1447716. doi: 10.3389/fmed.2024.1447716. eCollection 2024.

ABSTRACT

OBJECTIVE: The aim of this study was to conduct a systematic review and meta-analysis of the incidence of inflammatory bowel disease-associated bronchiectasis (IBD-BE) and to explore the possible risk factors for IBD-BE, which could help to understand the pulmonary involvement in patients with IBD and to determine the global incidence of the disease.

METHODS: We searched PubMed and EMBASE databases to identify information on the prevalence of IBD-BE among IBD patients in the published literature. Information was extracted on study design, country, year, IBD-BE testing method, IBD characteristics, number of IBD-BE cases and total number of IBD patients, and factors associated with IBD-BE. We conducted meta-analyses using random-effects or fixed-effects models to estimate the prevalence of IBD-BE among IBD patients.

RESULTS: Out of a total of 682 studies, we identified 16 studies that reported prevalence. These studies used a heterogeneous approach to identify IBD-BE. In these 16 studies, there were 92,191 patients with IBD, of whom 372 cases of IBD-BE were identified. The results of the meta-analysis showed that the overall prevalence of IBD-BE in IBD derived from the use of a random effects model was 5.0% (95% CI 2.0-12.0%). In contrast, the prevalence of IBD-BE in studies using high-resolution chest computed tomography (HRCT) imaging was 12% (95% CI 4-39%) using a random-effects model. When only retrospective studies with sample sizes greater than 100 (n = 6) were considered, the prevalence was 1% (95% CI 0-1%). However, when only retrospective studies with sample sizes less than 100 were included (n = 4), the prevalence was 29% (95% CI 6-100%); in prospective studies (n = 6), the combined prevalence was 11% (95% CI 4-29%). we performed a subgroup analysis of the differences in the incidence of IBD-BE between the different studies, each of which we subgrouped by type of study, type of disease, duration of disease, and diagnostic modality, and the results showed no significance. Future studies should standardize methods to identify IBD-BE cases and investigate the natural history and clinical course given the relatively high prevalence among IBD.

CONCLUSION: In this systematic review and meta-analysis, the prevalence of IBD-BE was 12% among studies with HRCT imaging, suggesting that bronchiectasis may be an underestimated common extraintestinal manifestation of IBD. Asymptomatic patients with IBD-BE may present with abnormalities on HRCT or pulmonary function tests. Future studies should standardize methods to identify IBD-BE cases and investigate the natural history and clinical course given the relatively high prevalence among IBD.

PMID:39640979 | PMC:PMC11617167 | DOI:10.3389/fmed.2024.1447716

Front Med (Lausanne). 2024 Nov 21;11:1422163. doi: 10.3389/fmed.2024.1422163. eCollection 2024.

ABSTRACT

BACKGROUND: Genetic and genomic literacy of health professionals is of utmost importance to realize the full potential of personalized medicine. As part of a European Union project, we piloted an e-learning course on oncogenomics, primarily targeted to physicians, and we assessed both its effectiveness and users’ satisfaction.

METHODS: The course materials were developed in English according to the Problem-Based Learning method. Learning objectives, covering the basic principles of genetics and the OMICS technologies applied to oncology, were defined based on previously identified core competencies. We used a pre-test vs. post-test study design to assess knowledge improvements. Performance results by demographic and professional characteristics of participants were analyzed using univariate or multivariate statistical methods.

RESULTS: Overall, 346 Italian professionals (61% physicians, 39% biologists) successfully completed the course. Their average post-test score was almost 19% higher than the pre-test (71.6% vs. 52.9%), with no significant differences by sex. Older age (>50 years) and southern area of residence were both correlated with higher gains. The average proportion of correct answers in the final certification test after three attempts was 85% (69% at first attempt), with some differences across professional categories. Methodology, quality of content and usability of the e-learning platform were all highly rated via satisfaction questionnaire (average scores between 4 and 5, scale 1 to 5).

CONCLUSION: The pilot phase confirmed the suitability of the e-learning as a cost-effective method to improve oncogenomic literacy of health professionals. Translation into natural languages and accreditation by European or country-specific Continuing Medical Education systems will be the main incentives for wider dissemination.

PMID:39640978 | PMC:PMC11617149 | DOI:10.3389/fmed.2024.1422163

J Plast Reconstr Aesthet Surg. 2024 Nov 28;100:205-207. doi: 10.1016/j.bjps.2024.11.049. Online ahead of print.

ABSTRACT

This study aimed to evaluate the potential use of artificial dermal grafts in the lower eyelid following surgical resection of basal cell carcinoma (BCC), focusing on the degree of scar contracture. Postoperative changes were assessed using four quantitative and two qualitative parameters. Anthropometric analysis revealed no statistically significant differences across the four quantitative measures. Furthermore, no new cases of ectropion or scleral show were observed after grafting. These findings suggest that artificial dermal grafting may be a viable option following surgical excision of BCCs on the lower eyelids, without inducing significant eyelid retraction.

PMID:39637516 | DOI:10.1016/j.bjps.2024.11.049

Forensic Sci Int. 2024 Nov 28;367:112309. doi: 10.1016/j.forsciint.2024.112309. Online ahead of print.

ABSTRACT

Environmental and individualistic variables affect the rate of human decomposition in complex ways. These effects complicate the estimation of the postmortem interval (PMI) based on observed decomposition characteristics. In this work, we develop a generative probabilistic model for decomposing human remains based on PMI and a wide range of environmental and individualistic variables. This model explicitly represents the effect of each variable, including PMI, on the appearance of each decomposition characteristic, allowing for direct interpretation of model effects and enabling the use of the model for PMI inference and optimal experimental design. In addition, the probabilistic nature of the model allows for the integration of expert knowledge in the form of prior distributions. We fit this model to a diverse set of 2529 cases from the GeoFOR dataset. We demonstrate that the model accurately predicts 24 decomposition characteristics with an ROC AUC score of 0.85. Using Bayesian inference techniques, we invert the decomposition model to predict PMI as a function of the observed decomposition characteristics and environmental and individualistic variables, producing an R-squared measure of 71 %. Finally, we demonstrate how to use the fitted model to design future experiments that maximize the expected amount of new information about the mechanisms of decomposition using the Expected Information Gain formalism.

PMID:39637513 | DOI:10.1016/j.forsciint.2024.112309

Sci Total Environ. 2024 Dec 4;958:177832. doi: 10.1016/j.scitotenv.2024.177832. Online ahead of print.

ABSTRACT

In spatiotemporal trend analysis, selective inference occurs when researchers are only interested in significant trends based on a fixed threshold (α, often 0.05), without considering the total number of statistical tests performed. Using simultaneous inference in gridded data involves thousands of trend tests, one for each pixel, leading to multiple testing or multiplicity problems. Multiplicity increases the chance of false discoveries in an unknown way unless the p-values of all tests performed are appropriately considered and adjusted. This discussion paper provides a selective and non-exhaustive review of the problems of multiplicity and selective inference. We discuss some appropriate methods to cope with the inflation of spurious results and comment on some examples based on gridded data in the context of research on spatiotemporal trend analysis. In addition, we suggest some good practices in transparency to facilitate the replicability of studies. The effects of uncorrected multiplicity and selective interference can be likened to a ghostly layer over the data, projecting illusions of significance that vanish with rigorous correction methods, revealing the true statistical skeleton of the results. The basis for addressing these problems is to assume that, although it may sometimes seem counterintuitive, the reality of what we perceive as statistically significant (i.e., p-values <0.05) also depends on the number (and value) of what we perceive as non-significant (i.e., p-values ≥0.05). Indeed, in a multiplicity context, one cannot correctly decide what is statistically significant until the whole story is known. Uncorrected selective inference precisely involves ignoring part of the story.

PMID:39637466 | DOI:10.1016/j.scitotenv.2024.177832

Comput Biol Med. 2024 Dec 4;185:109479. doi: 10.1016/j.compbiomed.2024.109479. Online ahead of print.

ABSTRACT

In this study, we investigate the application of self-supervised learning via pre-trained Long Short-Term Memory (LSTM) networks for training surface electromyography pattern recognition models (sEMG-PR) using dynamic data with transitions. While labeling such data poses challenges due to the absence of ground-truth labels during transitions between classes, self-supervised pre-training offers a way to circumvent this issue. We compare the performance of LSTMs trained with either fully-supervised or self-supervised loss to a conventional non-temporal model (LDA) on two data types: segmented ramp data (lacking transition information) and continuous dynamic data inclusive of class transitions. Statistical analysis reveals that the temporal models outperform non-temporal models when trained with continuous dynamic data. Additionally, the proposed VICReg pre-trained temporal model with continuous dynamic data significantly outperformed all other models. Interestingly, when using only ramp data, the LSTM performed worse than the LDA, suggesting potential overfitting due to the absence of sufficient dynamics. This highlights the interplay between data type and model choice. Overall, this work highlights the importance of representative dynamics in training data and the potential for leveraging self-supervised approaches to enhance sEMG-PR models.

PMID:39637459 | DOI:10.1016/j.compbiomed.2024.109479

Accid Anal Prev. 2024 Dec 4;211:107850. doi: 10.1016/j.aap.2024.107850. Online ahead of print.

ABSTRACT

Conflicts between cyclists and motorized vehicles at crosswalks often lead to severe collisions. The varied behaviour of cyclists at these crossings introduces unobserved heterogeneity. Despite this, there is a notable research gap in studying the cyclist behaviour at roundabout crosswalks. To address this gap, we propose a discrete choice latent class method to capture the multi-level latent heterogeneity in cyclists’ crossing behaviour at roundabout crosswalks. Latent heterogeneity can be captured at multiple levels: site-level, interaction-level, choice-attribute level, and individual-level. This method, rooted in behavioural theory, aims to provide a deeper understanding of cyclists’ crossing decisions, enhancing safety measures at these intersections. We present an application of the proposed method to two publicly available drone datasets of naturalistic road user trajectories at roundabouts, including 8 roundabout sites that exhibit some level of similarity to minimize site heterogeneity. We capture the latent heterogeneity in the cyclists’ membership to a distinct behavioural class at two levels using these datasets: the individual level, represented by the speed of the cyclist as they enter the crosswalk, and the interaction level, defined by the presence of vehicles approaching the cyclist. Our findings align with previous studies that emphasize the significance of the initial speed variable in influencing cyclists’ subsequent behaviour and decisions. We identified two distinct classes of cyclists. We hypothesize that Class 1 cyclists, whom we refer to as passers, tend to bypass or overtake other road users at the crosswalk, especially in the absence of vehicles, prioritizing speed and efficiency. We also hypothesize that Class 2 cyclists, referred to as followers, exhibit more cautious behaviour, preferring to maintain a steady pace and avoid overtaking, particularly when vehicles are present. The proposed latent class model effectively captures this behavioural distinction, offering a more granular view of cyclists’ decision-making processes at roundabout crosswalks. A key finding is that the discrete choice model with a latent class structure outperforms the basic model without it, despite having more degrees of freedom, as it achieves a lower BIC and AIC but improved model fit statistic. This demonstrates that latent heterogeneity can be effectively captured, leading to improved predictions and outperforming the basic non-latent class model. Classifying cyclists into distinct behavioural classes not only enhances cyclist safety at crosswalks but also provides valuable insights for the development of autonomous vehicle-cyclist interactions.

PMID:39637453 | DOI:10.1016/j.aap.2024.107850