Search Results (6,515)

Background: The implant–abutment joint is important for the long-term marginal tissue integrity in terms of biomimetic design that replicates the natural dentition under mastication forces. This study aimed to evaluate conical implant–abutment joints coupled at different tightening torque values through a mechanical fatigue test. Methods: Eighty conic implants (Ø: 3.8 mm L: 10 mm) with a 6° cone morse joint were embedded in resin blocks with an inclination of 30° ± 2°. The samples were divided into 8 groups (4 Test and 4 Control). The implant–abutment joints were coupled with different tightening torques: 25 Ncm (Group I), 30 Ncm (Group II), 35 Ncm (Group III) and 40 Ncm (Group IV). An in vitro cyclic loading test (1 × 10⁴ loads) was performed for 4 Test groups, while 4 Control groups did not receive any forces. All the samples were assessed with Scanning Electron Microscopy to compare the microfractures and microgaps on flexion and extension points. Results: Microscopy observation results showed significant differences among torque groups. We found that 30 Ncm had the best stability with less microgap. Conclusions: Tightening torque plays an important role in the distortion of the cone morse joint under mechanical forces. However, further studies should be conducted to validate the results using different implant–abutment joints for comparison. Full article

Combined trabeculectomy–phacoemulsification is known to provoke more inflammation and yield a poorer long-term efficacy than trabeculectomy alone. This study evaluates whether a similar trend exists for Ahmed glaucoma valve implantation when performed with or without concurrent phacoemulsification. We retrospectively analyzed 51 eyes from patients who underwent either Ahmed-Alone (n = 25) or PhacoAhmed (n = 26) surgery over a 5-year period. The primary outcomes included intraocular pressure (IOP), the use of IOP-lowering medications, and the need for further surgical intervention. Absolute success was defined as IOP reduction > 20% and IOP < 21 mmHg without medication; relative success allowed for continued pharmacologic therapy. Both groups showed a significant IOP reduction, with similar final mean IOP values (Ahmed-Alone: 14.02 ± 4.76 mmHg; PhacoAhmed: 13.89 ± 4.17 mmHg; p = 0.99) and comparable reductions in medication use (p = 0.52). Reinterventions occurred less frequently and later in the PhacoAhmed group (12% vs. 27.3%; median time: 27.1 vs. 12 months). Absolute success was not achieved in any PhacoAhmed case but occurred in 9.3% of Ahmed-Alone cases; relative success rates were similar (83.3% vs. 81.4%; p = 0.291). These findings suggest that combining phacoemulsification with Ahmed valve implantation does not significantly alter efficacy or safety profiles. Additional prospective studies are warranted to assess long-term outcomes. Full article

Background: Diabetic foot ulcers (DFUs) are a serious complication of diabetes and are often difficult to treat. Hyperbaric oxygen therapy (HBOT) has been proposed as an adjunctive treatment to promote healing, but its long-term clinical and biological effects remain insufficiently characterized. This study aimed to evaluate the impact of HBOT on systemic biomarkers, local microvasculature, and clinical outcomes in patients with DFUs. Methods: In this non-randomized prospective study, 20 patients with ischemic DFUs were followed over a 36-month period. Fourteen received HBOT in addition to standard care, while six received standard care alone. Clinical outcomes—including DFU resolution, recurrence, lower extremity amputation (LEA), and mortality—were assessed alongside systemic inflammatory and angiogenic biomarkers and wound characteristics at baseline and at 3, 6, 12, and 36 months. CD31 immunostaining was performed on available tissue samples. Results: The two groups were comparable at baseline (mean age 62 ± 12 years; diabetes duration 18 ± 9 years). At 3 months, the HBOT group showed significant reductions in erythrocyte sedimentation rate and DFU size (p < 0.05), with downward trends observed in C-reactive protein (CRP), vascular endothelial growth factor (VEGF), and placental growth factor (PlGF), and an increase in stromal-derived factor-1 alpha (SDF1-α). No significant changes were observed in the control group. CD31+ microvessel density appeared to increase in HBOT-treated DFU tissue after one month, although the sample size was limited. Patients receiving HBOT had lower rates of LEA and mortality, improved wound healing, and sustained outcomes over three years. DFU recurrence rates were similar between groups. Conclusions: HBOT was associated with improved wound healing and favorable biomarker profiles in patients with treatment-resistant ischemic DFUs. While these findings are encouraging, the small sample size and non-randomized design limit their generalizability, highlighting the need for larger, controlled studies. Full article

Background: Cardiac surgery patients with pre- or post-operative atrial fibrillation are at an increased risk for thromboembolic stroke, often due left atrial appendage (LAA) thrombus. Surgical LAA exclusion (LAAE) can be performed and must be complete to avoid increased thrombus formation. Methods: This prospective, multi-center, post-market study (NCT05101993) evaluated the long-term safety and performance of the epicardial V-shape AtriClip device. Patients ≥18 years who had received V-shape AtriClip devices during non-emergent cardiac surgery consented to a prospective 12-month follow-up visit and LAA imaging. The primary performance was LAAE without residual left atrium-LAA communication, assessed by imaging at the last follow-up visit. The primary safety was device- or implant procedure-related serious adverse events (SAEs) (death, major bleeding, surgical site infection, pericardial effusion requiring intervention, myocardial infarction) within 30 days. Results: Of 155 patients from 11 U.S. centers, 151 patients had evaluable imaging. Complete LAAE was obtained in all patients. Primary performance in the intent-to-treat population was met, with 97% (95% CI 93.52%, 99.29%; p = 0.0001) complete LAAE. Primary safety was met, with 100% (95% CI 97.75%, 100%; p < 0.0001) of patients free from pre-defined SAEs within 30 days. One device-related SAE was reported, which resolved intraprocedurally. Conclusions: AtriClip V-Clip showed safe and successful LAAE through 12 months of follow-up. Full article

Liquid calcium aluminate cement (LCAC) is an innovative material technology with significant potential for varied applications in civil engineering. However, despite its promising results, a significant gap remains in the direct application of LCAC as a concrete binder. The primary catalysts for LCAC are sodium hydroxide (NaOH) and potassium hydroxide (KOH). Therefore, it is crucial to investigate the effects of sodium and potassium ions on alkali–aggregate reactions in concrete structures. This study evaluated the durability of liquid calcium aluminate cement concrete catalyzed using four different concentrations of NaOH (0.5%, 1.0%, 1.5%, and 2.0%) as experimental variables, incorporating a control group of traditional concrete with a water–cement ratio of 0.64. The findings indicate that NaOH catalysis in the concrete significantly trigger alkali–aggregate reactions, leading to volume expansion. Furthermore, it increased chloride ion penetration and porosity in the concrete. These effects were more notable with the increase in NaOH concentration. The results suggested that NaOH catalysis can enhance certain chemical reactions within the concrete matrix; however, its concentration must be carefully controlled to mitigate adverse effects. The NaOH dosage should be limited to 0.5% to ensure optimal durability of the concrete. This study emphasizes the crucial importance of precisely balancing catalyst concentration to maintain the long-term durability and performance of liquid calcium aluminate cement concrete in structural applications. Full article

The COVID-19 pandemic triggered unprecedented economic disruptions, raising critical questions about the resilience and adaptability of macroeconomic productivity across countries. This study examines the impact of COVID-19 on macroeconomic efficiency and productivity dynamics in 37 OECD countries using quarterly data from 2018Q1 to 2024Q4. By employing a Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and the Malmquist Productivity Index (MPI), we decompose total factor productivity (TFP) into efficiency change (EC) and technological change (TC) across three periods: pre-pandemic, during-pandemic, and post-pandemic. Our framework incorporates both desirable (GDP) and undesirable outputs (inflation, unemployment, housing price inflation, and interest rate distortions), offering a multidimensional view of macroeconomic efficiency. Results show broad but uneven productivity gains, with technological progress proving more resilient than efficiency during the pandemic. Post-COVID recovery trajectories diverged, reflecting differences in structural adaptability and innovation capacity. Regression analysis reveals that stringent lockdowns in 2020 were associated with lower productivity in 2023–2024, while more adaptive policies in 2021 supported long-term technological gains. These findings highlight the importance of aligning crisis response with forward-looking economic strategies and demonstrate the value of DEA-based methods for evaluating macroeconomic performance beyond GDP. Full article

During the coronavirus 2019 pandemic, sports activities were restricted, raising concerns about their impact on the physical condition of adolescent athletes, which remained largely unquantified. This study was designed with two primary objectives: first, to precisely quantify and elucidate the differences in the physical condition of adolescent athletes before and after activity restrictions due to the pandemic; and second, to innovatively develop and validate a non-contact medical checkup application. Medical checks were conducted on 563 athletes designated for sports enhancement. Participants were junior high school students aged 13 to 15, and the sample consisted of 315 boys and 248 girls. Furthermore, we developed a smartphone application and compared self-checks using the application with in-person checks by orthopedic surgeons to determine the challenges associated with self-checks. Statistical tests were conducted to determine whether there were statistically significant differences in range of motion and flexibility parameters before and after the pandemic. Additionally, items with discrepancies between values self-entered by athletes using the smartphone application and values measured by specialists were detected, and application updates were performed. Student’s t-test was used for continuous variables, whereas the chi-square test was used for other variables. Following the coronavirus 2019 pandemic, athletes were stiffer than during the pre-pandemic period in terms of hip and shoulder joint rotation range of motion and heel–buttock distance. The dominant hip external rotation decreased from 53.8° to 46.8° (p = 0.0062); the non-dominant hip external rotation decreased from 53.5° to 48.0° (p = 0.0252); the dominant shoulder internal rotation decreased from 62.5° to 54.7° (p = 0.0042); external rotation decreased from 97.6° to 93.5° (p = 0.0282), and the heel–buttock distance increased from 4.0 cm to 10.4 cm (p < 0.0001). The heel–buttock distance and straight leg raising angle measurements differed between the self-check and face-to-face check. Although there are items that cannot be accurately evaluated by self-check, physical condition can be improved with less contact by first conducting a face-to-face evaluation under appropriate guidance and then conducting a self-check. These findings successfully address our primary objectives. Specifically, we demonstrated a significant decline in the physical condition of adolescent athletes following pandemic-related activity restrictions, thereby quantifying their impact. Furthermore, our developed non-contact medical checkup application proved to be a viable tool for monitoring physical condition with reduced contact, although careful consideration of measurable parameters is crucial. This study provides critical insights into the long-term effects of activity restrictions on young athletes and offers a practical solution for health monitoring during infectious disease outbreaks, highlighting the potential for hybrid checkup approaches. Full article

Background/Objectives: Polycystic ovary syndrome (PCOS) is a multifactorial endocrine disorder frequently associated with metabolic and inflammatory disturbances. Due to its antioxidant and anti-inflammatory properties, pomegranate juice has been proposed as a potential adjunctive therapy in managing PCOS. To evaluate the effects of pomegranate juice on hormonal, inflammatory, and lipid parameters and body mass index (BMI) in women with PCOS. Methods: A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted following PRISMA guidelines. Comprehensive searches were performed in electronic databases including Medline, Scopus, Web of Science, Cochrane CENTRAL, and Embase from inception to July 2025, using keywords and MeSH terms related to “polycystic ovary syndrome” and “pomegranate juice” without language restrictions. The primary outcomes were changes in serum testosterone, luteinizing hormone (LH), high-sensitivity C-reactive protein (hs-CRP), lipid profile parameters (HDL, LDL, triglycerides, and total cholesterol), and body mass index (BMI). Results: Four RCTs published between 2020 and 2023, encompassing 128 women with PCOS, were included. The meta-analysis revealed significant reductions in testosterone (MD: −0.05; 95% CI: −0.07 to −0.03; p < 0.0001; I² = 0%, two studies, 85 participants) and hs-CRP (SMD: −0.85; 95% CI: −1.35 to −0.35; p = 0.0009; I² = 20%, two studies, 85 participants), along with increases in HDL (MD: 6.21; 95% CI: 2.43 to 10.00; p = 0.001; I² = 0%, two studies, 85 participants) and reductions in triglycerides (MD: −23.30; 95% CI: −45.19 to −1.42; p = 0.04; I² = 0%, two studies, 85 participants). No significant changes were observed in LH, LDL, total cholesterol, or BMI. Conclusions: Pomegranate juice demonstrates promising effects as an adjunctive intervention in women with PCOS, improving androgen levels, inflammatory markers, and certain lipid parameters. Further long-term studies are needed to confirm these findings. Full article

Machine learning modeling is a valuable tool for gap-filling or prediction, and its performance is typically evaluated using standard metrics. To enable more precise assessments for time-series data, this study emphasizes the importance of considering time-series consistency, which can be evaluated through amplitude—specifically, the interquartile range and the lower bound of the band in gap-filled time series. To test this hypothesis, a gap-filling technique was applied using long-term (~6 years) high-frequency flux and meteorological data collected at four different levels (1.5, 60, 140, and 300 m above sea level) on a ~300 m tall flux tower. This study focused on turbulent kinetic energy among several variables, which is important for estimating sensible and latent heat fluxes and net ecosystem exchange. Five ensemble machine learning algorithms were selected and trained on three different datasets. Among several modeling scenarios, the stacking model with a dataset combined with derivative data produced the best metrics for predicting turbulent kinetic energy. Although the metrics before and after gap-filling reported fewer differences among the scenarios, large distortions were found in the consistency of the time series in terms of amplitude. These findings underscore the importance of evaluating time-series consistency alongside traditional metrics, not only to accurately assess modeling performance but also to ensure reliability in downstream applications such as forecasting, climate modeling, and energy estimation. Full article

Accurate forecasting of tropical cyclone (TC) tracks is critical for disaster preparedness and risk mitigation. While traditional numerical weather prediction (NWP) systems have long served as the backbone of operational forecasting, they face limitations in computational cost and sensitivity to initial conditions. In recent years, deep learning (DL) has emerged as a promising alternative, offering data-driven modeling capabilities for capturing nonlinear spatiotemporal patterns. This paper presents a comprehensive review of DL-based approaches for TC track forecasting. We categorize all DL-based TC tracking models according to the architecture, including recurrent neural networks (RNNs), convolutional neural networks (CNNs), Transformers, graph neural networks (GNNs), generative models, and Fourier-based operators. To enable rigorous performance comparison, we introduce a Unified Geodesic Distance Error (UGDE) metric that standardizes evaluation across diverse studies and lead times. Based on this metric, we conduct a critical comparison of state-of-the-art models and identify key insights into their relative strengths, limitations, and suitable application scenarios. Building on this framework, we conduct a critical cross-model analysis that reveals key trends, performance disparities, and architectural tradeoffs. Our analysis also highlights several persistent challenges, such as long-term forecast degradation, limited physical integration, and generalization to extreme events, pointing toward future directions for developing more robust and operationally viable DL models for TC track forecasting. To support reproducibility and facilitate standardized evaluation, we release an open-source UGDE conversion tool on GitHub. Full article

In this study, we propose a bidirectional chemical sensor platform based on a reconfigurable ion-sensitive field-effect transistor (R-ISFET) architecture. The device incorporates Ni-silicide Schottky barrier source/drain (S/D) contacts, enabling ambipolar conduction and bidirectional turn-on behavior for both p-type and n-type configurations. Channel polarity is dynamically controlled via the program gate (PG), while the control gate (CG) suppresses leakage current, enhancing operational stability and energy efficiency. A dual-control-gate (DCG) structure enhances capacitive coupling, enabling sensitivity beyond the Nernst limit without external amplification. The extended-gate (EG) architecture physically separates the transistor and sensing regions, improving durability and long-term reliability. Electrical characteristics were evaluated through transfer and output curves, and carrier transport mechanisms were analyzed using band diagrams. Sensor performance—including sensitivity, hysteresis, and drift—was assessed under various pH conditions and external noise up to 5 V_pp (i.e., peak-to-peak voltage). The n-type configuration exhibited high mobility and fast response, while the p-type configuration demonstrated excellent noise immunity and low drift. Both modes showed consistent sensitivity trends, confirming the feasibility of complementary sensing. These results indicate that the proposed R-ISFET sensor enables selective mode switching for high sensitivity and robust operation, offering strong potential for next-generation biosensing and chemical detection. Full article

This study investigates the use of waste glass powder derived from fluorescent lamps as a partial replacement for cement in mortar production, aiming to valorize this Waste from Electrical and Electronic Equipment (WEEE) and enhance sustainability in the construction sector. Mortars were formulated by substituting 25% of cement by volume with glass powders from fluorescent lamp glass and green bottle glass. The experimental program evaluated mechanical strength, durability parameters and ecotoxicological performance. Results revealed that clean fluorescent lamp mortars showed the most promising mechanical behavior, exceeding the reference in long-term compressive (54.8 MPa) and flexural strength (10.0 MPa). All glass mortars exhibited significantly reduced chloride diffusion coefficients (85–89%) and increased electrical resistivity (almost 4 times higher), indicating improved durability. Leaching tests confirmed that the incorporation of fluorescent lamp waste did not lead to hazardous levels of heavy metals in the cured mortars, suggesting effective encapsulation. By addressing both technical (mechanical and durability) and ecotoxic performance, this research contributes in an original and relevant way to the development of more sustainable building materials. Full article

Introduction: Cystic fibrosis (CF) is a genetic condition affecting several organs and systems, including the pancreas, colon, respiratory system, and reproductive system. The detection of a growing number of CFTR variants and genotypes has contributed to an increase in the CF population which, in turn, has had an impact on the overall statistics regarding the prognosis and outcome of the condition. Given the increase in life expectancy, it is critical to better predict outcomes and prognosticate in CF. Thus, each person’s choice to aggressively treat specific disease components can be more appropriate and tailored, further increasing survival. The objective of our narrative review is to summarize the most recent information concerning the value and significance of clinical parameters in predicting outcomes, such as gender, diabetes, liver and pancreatic status, lung function, radiography, bacteriology, and blood and sputum biomarkers of inflammation and disease, and how variations in these parameters affect prognosis from the prenatal stage to maturity. Materials and methods: A methodological search of the available data was performed with regard to prognostic factors in the evolution of CF in children and young adults. We evaluated articles from the PubMed academic search engine using the following search terms: prognostic factors AND children AND cystic fibrosis OR mucoviscidosis. Results: We found that it is crucial to customize CF patients’ care based on their unique clinical and biological parameters, genetics, and related comorbidities. Conclusions: The predictive significance of more dynamic clinical condition markers provides more realistic future objectives to center treatment and targets for each patient. Over the past ten years, improvements in care, diagnostics, and treatment have impacted the prognosis for CF. Although genotyping offers a way to categorize CF to direct research and treatment, it is crucial to understand that a variety of other factors, such as epigenetics, genetic modifiers, environmental factors, and socioeconomic status, can affect CF outcomes. The long-term management of this complicated multisystem condition has been made easier for patients, their families, and physicians by earlier and more accurate identification techniques, evidence-based research, and centralized expert multidisciplinary care. Full article

Background/Objectives: Identifying and classifying abnormal lung sounds is essential for diagnosing patients with respiratory disorders. In particular, the simultaneous recording of auscultation signals from multiple clinically relevant positions offers greater diagnostic potential compared to traditional single-channel measurements. This study aims to improve the accuracy of respiratory sound classification by leveraging multichannel signals and capturing positional characteristics from multiple sites in the same patient. Methods: We evaluated the performance of respiratory sound classification using multichannel lung sound data with a deep learning model that combines a convolutional neural network (CNN) and long short-term memory (LSTM), based on mel-frequency cepstral coefficients (MFCCs). We analyzed the impact of the number and placement of channels on classification performance. Results: The results demonstrated that using four-channel recordings improved accuracy, sensitivity, specificity, precision, and F1-score by approximately 1.11, 1.15, 1.05, 1.08, and 1.13 times, respectively, compared to using three, two, or single-channel recordings. Conclusions: This study confirms that multichannel data capture a richer set of features corresponding to various respiratory sound characteristics, leading to significantly improved classification performance. The proposed method holds promise for enhancing sound classification accuracy not only in clinical applications but also in broader domains such as speech and audio processing. Full article

Background: Transcatheter aortic valve implantation (TAVI) has revolutionized the treatment of severe aortic valve stenosis (AS). Balloon post-dilatation (PD) remains an important procedural step to optimize valve function by resolving incomplete valve expansion, which may lead to paravalvular regurgitation and other potentially adverse effects. There are only limited data on the predictors, incidence, and clinical impact of PD during TAVI. Methods: This retrospective, single-center study analyzed 585 patients who underwent TAVI (2016–2022). Pre-procedural evaluations included transthoracic echocardiography and CT angiography to assess key parameters, including the aortic valve calcium score (AVCS); aortic valve calcium density (AVCd); aortic valve maximal systolic transvalvular flow velocity (AV Vmax); and aortic valve mean systolic pressure gradient (AV MPG). We identified imaging predictors of PD and evaluated associated clinical outcomes by analyzing procedural endpoints (according to VARC-3 criteria) and long-term survival. Results: PD was performed on 67 out of 585 patients, with elevated AV Vmax (OR: 1.424, 95% CI: 1.039–1.950; p = 0.028) and AVCd (OR: 1.618, 95% CI: 1.227–2.132; p = 0.001) emerging as a significant independent predictor for PD in TAVI. Kaplan–Meier survival analysis revealed no significant differences in short- and mid-term survival between patients who underwent PD and those who did not. Interestingly, patients requiring PD exhibited a lower incidence of adverse events regarding major vascular complications, permanent pacemaker implantations and stroke. Conclusions: The study highlights AV Vmax and AVCd as key predictors of PD. Importantly, PD was not associated with increased procedural adverse events and did not predict adverse events in this contemporary cohort. Full article