Search Results (2,504)

Background: The rising demand for aesthetic dental treatments has spurred interest in peroxide-free color correctors as alternatives to traditional hydrogen peroxide formulations, which are associated with tooth sensitivity and potential enamel demineralization. This systematic review evaluates the whitening efficacy and safety profile of hydrogen peroxide-free color corrector (HPFCC) products, focusing on color change metrics, enamel and dentin integrity, and adverse effects. Methods: Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science throughout January 2025 for randomized controlled trials, observational studies, and in vitro experiments comparing HPFCC to placebo or peroxide-based agents. The data extraction covered study design, sample characteristics, intervention details, shade improvement (ΔE00 or CIE Lab), enamel/dentin mechanical properties (microhardness, roughness, elastic modulus), and incidence of sensitivity or tissue irritation. Risk of bias was assessed using the Cochrane tool for clinical studies and the QUIN tool for in vitro research. Results: Six studies (n = 20–80 samples or subjects) met the inclusion criteria. In vitro, HPFCC achieved mean ΔE00 values of 3.5 (bovine incisors; n = 80) and 2.8 (human molars; n = 20), versus up to 8.9 for carbamide peroxide (p < 0.01). Across studies, HPFCC achieved a mean ΔE00 of 2.8–3.5 surpassing the perceptibility threshold of 2.7 and approaching the clinical acceptability benchmark of 3.3. Surface microhardness increased by 12.9 ± 11.7 VHN with HPFCC (p < 0.001), and ultramicrohardness rose by 110 VHN over 56 days in prolonged use studies. No significant enamel erosion or dentin roughness changes were observed, and the sensitivity incidence remained below 3%. Conclusions: These findings derive from one clinical trial (n = 60) and five in vitro studies (n = 20–80), encompassing violet-pigment serums and gels with differing concentrations. Due to heterogeneity in designs, formulations, and outcome measures, we conducted a narrative synthesis rather than a meta-analysis. Although HPFCC ΔE00 values were lower than those of carbamide peroxide, they consistently exceeded perceptibility thresholds while maintaining enamel integrity and causing sensitivity in fewer than 3% of subjects, supporting HPFCCs as moderate but safe alternatives for young patients. Full article

Renewable fuels produced from animal- and plant-based edible oils have emerged as an alternative to oil and natural gas. Burgeoning interest in renewables can be attributed to the rapid depletion of fossil fuels caused by the global energy demand and the environmental advantages of renewables, specifically reduced emissions of greenhouse gases. An important property of the feedstock that is crucial for the conversion of edible oils to renewable fuels is the total acid number (TAN), as even a small increase in TAN for the feedstock can lead to corrosion of the catalyst in the refining process. Currently, the TAN is determined by potentiometric titration, which is time-consuming, expensive, and requires the preparation of reagents. As part of an effort to promote the use of renewable fuels, a partial least squares regression method with orthogonal signal correction to remove spectral information related to the sample background was developed to determine the TAN from the mid-infrared (IR) spectra of the feedstock. Digitally blended mid-IR spectral data were generated to fill in regions of the PLS calibration where there were very few samples. By combining experimental and digitally blended mid-IR spectral data to ensure adequate sample representation in all regions of the spectra–property calibration and better understand the spectra–property relationship through the identification of sample outliers in the original data that can be difficult to detect because of swamping, a PLS regression model for TAN (R² = 0.992, cross-validated root mean square error = 0.468, and bias = 0.0036) has been developed from 118 experimental and digitally blended mid-IR spectra of commercial feedstock. Thus, feedstock whose TAN value is too high for refining can be flagged using the proposed mid-IR method, which is faster and easier to use than the current titrimetric method. Full article

Despite targeting mainly the respiratory tract, SARS-CoV-2 disrupts T cell homeostasis in ways that may explain both acute lethality and long-term immunological consequences. In this study, we aimed to evaluate the T-cell-mediated chain of immunity and formation of TCR via TREC assessment in COVID-19 and long COVID (LC). For this study, we collected 231 blood samples taken from patients with acute COVID-19 (n = 71), convalescents (n = 51), people diagnosed with LC (n = 63), and healthy volunteers (n = 46). With flow cytometry, we assessed levels of CD4+ and CD8+ minor T cell subpopulations (i.e., naïve, central and effector memory cells (CM and EM), Th1, Th2, Th17, Tfh, Tc1, Tc2, Tc17, Tc17.1, and subpopulations of effector cells (pE1, pE2, effector cells)). Additionally, we measured TREC levels. We found distinct changes in immune cell distribution—whilst distribution of major subpopulations of T cells was similar between cohorts, we noted that COVID-19 was associated with a decrease in naïve Th and CTLs, an increase in Th2/Tc2 lymphocyte polarization, an increase in CM cells, and a decrease in effector memory cells 1,3, and TEMRA cells. LC was associated with naïve CTL increase, polarization towards Th2 population, and a decrease in Tc1, Tc2, Em2, 3, 4 cells. We also noted TREC correlating with naïve cells subpopulations. Our findings suggest ongoing immune dysregulation, possibly driven by persistent antigen exposure or tissue migration of effector cells. The positive correlation between TREC levels and naïve T cells in LC patients points to residual thymic activity. The observed Th2/Th17 bias supports the hypothesis that LC involves autoimmune mechanisms, potentially driven by molecular mimicry or loss of immune tolerance. Full article

In recent years, cross-domain few-shot learning (CDFSL) has demonstrated remarkable performance in hyperspectral image classification (HSIC), partially alleviating the distribution shift problem. However, most domain adaptation methods rely on similarity metrics to establish cross-domain class matching, making it difficult to simultaneously account for intra-class sample size variations and inherent inter-class differences. To address this problem, existing studies have introduced a class weighting mechanism within the prototype network framework, determining class weights by calculating inter-sample similarity through distance metrics. However, this method suffers from a dual limitation: susceptibility to noise interference and insufficient capacity to capture global class variations, which may lead to distorted weight allocation and consequently result in alignment bias. To solve these issues, we propose a novel class-discrepancy dynamic weighting-based cross-domain FSL (CDDW-CFSL) framework. It integrates three key components: (1) the class-weighted domain adaptation (CWDA) method dynamically measures cross-domain distribution shifts using global class mean discrepancies. It employs discrepancy-sensitive weighting to strengthen the alignment of critical categories, enabling accurate domain adaptation while maintaining feature topology; (2) the class mean refinement (CMR) method incorporates class covariance distance to compute distribution discrepancies between support set samples and class prototypes, enabling the precise capture of cross-domain feature internal structures; (3) a novel multi-dimensional feature extractor that captures both local spatial details and continuous spectral characteristics simultaneously, facilitating deep cross-dimensional feature fusion. The results in three publicly available HSIC datasets show the effectiveness of the CDDW-CFSL. Full article

Background/Objectives: Speech intelligibility (SI) is a key indicator of spoken language development, especially for children with hearing loss, as it directly impacts communication and social engagement. However, due to logistical and methodological challenges, SI assessment is often underutilised in clinical practice. This study aimed to evaluate the accuracy and consistency of an artificial intelligence (AI)-based transcription model in assessing SI in young children with cochlear implants (CI), hearing aids (HA), or normal hearing (NH), in comparison to naïve human listeners. Methods: A total of 580 speech samples from 58 five-year-old children were transcribed by three naïve listeners and the AI model. Word-level transcription accuracy was evaluated using Bland–Altman plots, intraclass correlation coefficients (ICCs), and word error rate (WER) metrics. Performance was compared across the CI, HA, and NH groups. Results: The AI model demonstrated high consistency with naïve listeners across all groups. Bland–Altman analyses revealed minimal bias, with fewer than 6% of sentences falling outside the 95% limits of agreement. ICC values exceeded 0.9 in all groups, with particularly strong agreement in the NH and CI groups (ICCs > 0.95). WER results further confirmed this alignment and indicated that children with CIs showed better SI performance than those using HAs. Conclusions: The AI-based method offers a reliable and objective solution for SI assessment in young children. Its agreement with human performance supports its integration into clinical and home environments for early intervention and ongoing monitoring of speech development in children with hearing loss. Full article

Background: Long-term right ventricular pacing (RVP) can cause electrical and mechanical dyssynchrony, resulting in adverse outcomes. Recently, left bundle branch area pacing (LBBAP) has emerged as a physiological pacing modality and is considered a promising alternative. To date, the long-term outcomes of LBBAP compared with RVP, particularly with respect to sex differences, remain unclear. Methods: Between January 2017 and July 2024, 1211 patients who underwent de novo pacemaker implantation were enrolled and categorized into RVP (n = 789) and LBBAP (n = 422). The primary outcome was a composite of all-cause mortality, heart failure hospitalization (HFH), and pacing-induced cardiomyopathy (PICM). Propensity score matching (PSM) was employed to minimize the selection bias and achieve comparability among the study population. A post hoc power analysis based on the observed effect size and sample size showed a power of 80%, confirming sufficient sensitivity to detect group differences. Results: After PSM, 764 patients were analyzed. The mean age of the patients was 74.6 ± 10.5 years in RVP and 74.5 ± 9.8 years in LBBAP, respectively, and 52.3% patients were male. Patients with LBBAP had a lower incidence of the primary outcome (8.6% vs. 24.6%, p < 0.001), HFH (2.6% vs. 13.6%, p < 0.001), and all-cause mortality (6.5% vs. 13.9%, p < 0.001) compared with RVP. There were no significant differences in the clinical outcomes, including the primary outcome, HFH and all-cause mortality, between the sexes in the group with either RVP or LBBAP. However, during a 2-year follow-up period for survival analysis, male patients with LBBAP had a significant lower incidence of all the endpoints, whereas female patients with LBBAP had a lower incidence of HFH [HR 0.14 (95% CI 0.06–0.32), p = 0.001] compared with those with RVP. Conclusions: Regardless of sex, patients with LBBAP had a lower risk of poor clinical outcomes, including HFH and all-cause mortality, compared to those with RVP. Moreover, compared with RVP, LBBAP decreased the risks of all the major endpoints in male patients and the risk of HFH particularly in female patients. Further research is needed to establish the sex-specific responses to LBBAP. Full article

Background: Continuous monitoring of hemoglobin (HB) and hematocrit (HCT) during hemodialysis could improve fluid management and patient safety. The Fresenius 5008 dialysis machine includes an ultrasound-based sensor that estimates HB and HCT values, though its accuracy compared to standard laboratory measurements remains unclear. Methods: This exploratory observational study assessed the agreement between sensor-derived and laboratory-derived HB and HCT values in 20 patients at the start of hemodiafiltration. A total of 177 paired blood samples were collected. Results: Sensor values significantly underestimated laboratory HB (9.61 vs. 11.31 g/dL) and HCT (27% vs. 34%) (p < 8 × 10⁻²⁵). Correlations were strong for both parameters (HB: r = 0.788; HCT: r = 0.876). Regression analyses revealed consistent proportional bias. Applying a fixed correction of +1.69 g/dL for HB and +7.55% for HCT eliminated the statistical differences and reduced intercepts in regression models. Bland–Altman plots confirmed improved agreement post-correction. Albumin levels correlated modestly with error magnitude. Conclusions: HB and HCT values from the Fresenius 5008 sensor are strongly correlated with laboratory data but are systematically underestimated at treatment start, likely due to hemodilution. Applying fixed correction factors improves accuracy and supports the sensor’s use for real-time monitoring. Full article

Developing accurate activity data on tree biomass using remote sensing tools such as LiDAR and drone-mounted sensors is essential for improving carbon accounting in the agricultural sector. However, direct biomass measurements of perennial fruit trees remain limited, especially for validating remote sensing estimates. This study evaluates the potential of terrestrial laser scanning (TLS) and drone-mounted RGB sensors (Drone_RGB) for estimating biomass in two major perennial crops in South Korea: apple (‘Fuji’/M.9) and citrus (‘Miyagawa-wase’). Trees of different ages were destructively sampled for biomass measurement, while volume, height, and crown area data were collected via TLS and Drone_RGB. Regression analyses were performed, and the model accuracy was assessed using R², RMSE, and bias. The TLS-derived volume showed strong predictive power for biomass (R² = 0.704 for apple, 0.865 for citrus), while the crown area obtained using both sensors showed poor fit (R² ≤ 0.7). Aboveground biomass was reasonably estimated (R² = 0.725–0.865), but belowground biomass showed very low predictability (R² < 0.02). Although limited in scale, this study provides empirical evidence to support the development of remote sensing-based biomass estimation methods and may contribute to improving national greenhouse gas inventories by refining emission/removal factors for perennial fruit crops. Full article

In observational causal inference studies, unmeasured confounding remains a critical threat to the validity of effect estimates. While proximal causal inference (PCI) has emerged as a powerful framework for mitigating such bias through proxy variables, existing PCI methods cannot directly handle censored data. This article develops a unified proximal causal inference framework that simultaneously addresses unmeasured confounding and right-censoring challenges, extending the proximal causal inference literature. Our key contributions are twofold: (i) We propose novel identification strategies and develop two distinct estimators for the censored-outcome bridge function and treatment confounding bridge function, resolving the fundamental challenge of unobserved outcomes; (ii) To improve robustness against model misspecification, we construct a robust proximal estimator and establish uniform consistency for all proposed estimators under mild regularity conditions. Through comprehensive simulations, we demonstrate the finite-sample performance of our methods, followed by an empirical application evaluating right heart catheterization effectiveness in critically ill ICU patients. Full article

A new approach in amperometric enzyme electrodes production based on all-electrochemically assisted procedures will be described. Enzyme (glucose oxidase) immobilization was performed by in situ co-crosslinking of enzyme molecules through electrophoretic protein deposition, assuring enzyme immobilization exclusively onto the transducer surface (Pt electrode). Analogously, the poor selectivity of the transducer was dramatically improved by the electrosynthesis of non-conducting polymers with built-in permselectivity, permitting the formation of a thin permselective film onto the transducer surface, able to reject common interferents usually found in real samples. Since both approaches required a proper and distinct electrochemical perturbation (a pulsed current sequence for electrophoretic protein deposition and cyclic voltammetry for the electrosynthesis of non-conducting polymers), an appropriate coupling of the two all-electrochemical approaches was assured by a thorough study of the likely combinations of the electrosynthesis of permselective polymers with enzyme immobilization by electrophoretic protein deposition and by the use of several electrosynthesized polymers. For each investigated combination and for each polymer, the analytical performances and the rejection capabilities of the resulting biosensor were acquired so to gain information about their sensing abilities eventually in real sample analysis. This study shows that the proper coupling of the two all-electrochemical approaches and the appropriate choice of the electrosynthesized, permselective polymer permits the easy fabrication of novel glucose oxidase biosensors with good analytical performance and low bias in glucose measurement from typical interferent in serum. This novel approach, resembling classical electroplating procedures, is expected to allow all the advantages expected from such procedures like an easy preparation biosensor, a bi-dimensional control of enzyme immobilization and thickness, interferent- and fouling-free transduction of the electrodic sensor and, last but not the least, possibility of miniaturization of the biosensing device. Full article

As yet, no study has investigated the use of a research magnetic resonance imaging (MRI) scanner to support undergraduate medical radiation science (MRS) students in developing their MRI knowledge and practical skills (competences). The purpose of this study was to test an innovative program for a total of 10 s- and third-year students of a MRS course to enhance their MRI competences. The study involved an experimental, two-week MRI learning program which focused on practical MRI scanning of phantoms and healthy volunteers. Pre- and post-program questionnaires and tests were used to evaluate the competence development of these participants as well as the program’s educational quality. Descriptive statistics, along with Wilcoxon signed-rank and paired t-tests, were used for statistical analysis. The program improved the participants’ self-perceived and actual MRI competences significantly (from an average of 2.80 to 3.20 out of 5.00, p = 0.046; and from an average of 34.87% to 62.72%, Cohen’s d effect size: 2.53, p < 0.001, respectively). Furthermore, they rated all aspects of the program’s educational quality highly (mean: 3.90–4.80 out of 5.00) and indicated that the program was extremely valuable, very effective, and practical. Nonetheless, further evaluation should be conducted in a broader setting with a larger sample size to validate the findings of this feasibility study, given the study’s small sample size and participant selection bias. Full article

Background: Depression is a mental disorder characterized by a combination of somatic and cognitive disturbances, in which a predominantly sad or irritable mood significantly interferes with the patient’s functioning. This condition can affect individuals of all ages and socioeconomic backgrounds. Currently, various studies are exploring a possible association between oral dysbiosis and depression—an increasingly relevant topic, as confirmation of such a relationship could position the oral microbiota as a potential etiological or diagnostic factor for depression, given its accessibility and ease of analysis. Aim: To present a qualitative synthesis of studies addressing how oral dysbiosis influences the onset of depression, as well as the importance of controlling this alteration of the oral microbiota to aid in the prevention of the disease. Materials and Methods: The PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) outline the procedures to be followed for conducting this systematic review. The article search was carried out on 22 May 2025, across the PubMed, Scopus, Scielo, and The Cochrane Library databases, using terms related to “depression” and “oral dysbiosis”. Studies published within the last 10 years that addressed the potential association between oral dysbiosis, and depression were included. Furthermore, the quality of the studies was assessed using various tools depending on their design: the Newcastle–Ottawa Scale (NOS) was applied to case-control and cohort studies; the Joanna Briggs Institute (JBI) critical appraisal checklist was used for cross-sectional studies; and experimental studies were evaluated using SYRCLE’s Risk of Bias Tool. Results: A total of eleven studies were included in this systematic review. The findings suggest the presence of alterations in the oral microbiota of patients with depression, particularly in terms of composition, structure, and diversity. A reduction in alpha diversity—an indicator of local microbial balance—was observed, along with an increase in beta diversity, indicating greater inter-individual variability, which may be associated with inflammatory processes or immunological dysfunctions. Some studies reported differing results, which may be attributable to methodological variability regarding study design, or the populations sampled. Conclusions: This systematic review suggests that the oral microbiome could be considered a diagnostic biomarker and therapeutic target for depression, as the analyzed studies demonstrate a significant association between oral microbiome dysbiosis and this mental disorder. However, the methodological heterogeneity among the studies highlights the need for further research to confirm this potential relationship. Full article

Background/Objective: Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) has affected more than 1700 women with textured breast implants. About 80% of patients present with fluid (seroma) around their implant. BIA-ALCL can be cured by surgery alone when confined to the seroma and lining of the peri-implant capsule. To address the need for early detection, we developed a rapid point of care (POC) lateral flow assay (LFA) to identify lymphoma in seromas. Methods: We compared 28 malignant seromas to 23 benign seromas using both ELISA and LFA. LFA test lines (TL) and control lines (CL) were visualized and measured with imaging software and the TL/CL ratio for each sample was calculated. Results: By visual exam, the sensitivity for detection of CA9 was 93% and specificity 78%, while the positive predictive value was 84% and negative predictive value 90%. Quantitative image analysis increased the positive predictive value to 96% while the negative predictive value reduced to 79%. Conclusions: We conclude that CA9 is a sensitive biomarker for detection and screening of patients for BIA-ALCL in patients who present with seromas of unknown etiology. The CA9 LFA can potentially replace ELISA, flow cytometry and other tests requiring specialized equipment, highly trained personnel, larger amounts of fluid and delay in diagnosis of BIA-ALCL. Full article

Objective: This cross-sectional content analysis aimed to investigate how oil pulling is portrayed on YouTube Shorts, focusing on the types of speakers, claims made, and alignment with scientific evidence. The study further explored how the content may influence viewer perception, health behaviors, and the potential spread of misinformation. Methods: On 28 January 2025, a systematic search of YouTube Shorts was performed using the term “oil pulling” in incognito mode to reduce algorithmic bias. English language videos with at least 1000 views were included through purposive sampling. A total of 47 Shorts met the inclusion criteria. Data were extracted using a structured coding framework that recorded speaker type (e.g., dentist, hygienist, influencer), engagement metrics, stated benefits, oil type and regimen, the use of disclaimers or citations, and stance toward oil pulling rated on a 5-point Likert scale. Speaker background and nationality were determined through publicly available channel descriptions or linked websites, with user identities anonymized and ethical approval deemed unnecessary due to the use of publicly available content. In total, 47 videos met the inclusion criteria. Results: Of the 47 YouTube Shorts that met the inclusion criteria, most were posted by influencers rather than dental professionals. These videos predominantly encouraged oil pulling, often recommending coconut oil for 10–15 min daily and citing benefits such as reduced halitosis and improved gum health. However, a smaller subset advanced more extreme claims, including reversing cavities and remineralizing enamel. Notably, US-licensed dentists and dental hygienists tended to discourage or express skepticism toward oil pulling, assigning lower Likert scores (1 or 2) to influencers and alternative health practitioners (often 4 or 5). Conclusions: YouTube Shorts largely promote oil pulling through anecdotal and testimonial-driven content, often diverging from evidence-based dental recommendations. The findings reveal a disconnect between professional dental guidance and popular social media narratives. While some benefits like halitosis reduction may have limited support, exaggerated or misleading claims may result in improper oral hygiene practices. Greater engagement from dental professionals and improved health communication strategies are needed to counteract misinformation and reinforce oil pulling’s role, if any, as an adjunct—not a replacement—for standard oral care. Future studies should explore viewer interpretation, behavioral influence, and cross-platform content patterns to better understand the impact of short-form health videos. Full article

Rat hepatitis E virus (rat HEV) is an emerging zoonotic virus detected in rodents worldwide, with increasing evidence of presence in environmental sources such as surface water, wastewater and bivalves. This systematic review compiles and analyzes all the published research on rat HEV contamination in these matrices, as well as its implications for human health. A comprehensive literature search was conducted using databases such as PubMed, Scopus, Web of Science, and Mendeley, including studies published up until 27 May 2025. Studies were included if they evaluated rat HEV in water- or food-related matrices using molecular detection. The risk of bias was not assessed. The certainty of evidence was not formally evaluated. Limitations include reliance on PCR methods without infectivity confirmation. Following PRISMA inclusion and exclusion criteria, eight eligible studies were analyzed. The results show high detection rates of rat HEV RNA in influent wastewater samples from several high-income European countries, namely Sweden, France, Italy, Spain and Portugal. Lower detection rates were found in effluent wastewater and surface waters in Sweden. In bivalve mollusks sampled in Brazil, rat HEV RNA was detected in 2.2% of samples. These findings show the widespread environmental presence of rat HEV, particularly in urban wastewater systems. While human infections by rat HEV have been documented, the true extent of rat HEV zoonotic potential remains unclear. Given the risks associated with this environmental rat HEV contamination, enhanced surveillance, standardized detection methods, and targeted monitoring programs in food production and water management systems are essential to mitigate potential public health threats. Establishing such programs will be crucial for understanding the impact of rat HEV on human health. Full article