Search Results (1,118)

The rapid adoption of electric vehicles (BEVs) has increased the need to understand how fast-charging strategies influence long-distance travel times under real-world conditions. While most manufacturers specify maximum charging power and standardized driving ranges, these figures often fail to reflect actual highway operation, particularly in adverse weather. This study addresses this gap by analyzing the fast-charging behaviour, net battery capacity and highway energy consumption of 62 EVs from different market segments. Charging power curves were obtained experimentally at high-power DC stations, with data recorded through both the charging infrastructure and the vehicles’ battery management systems. Tests were conducted, under optimal conditions, between 10% and 90% state of charge (SoC), with additional sessions performed under both cold and preconditioned battery conditions to show thermal effects on the batteries’ fast-charging capabilities. Real-world highway consumption values were applied to simulate 1000 km journeys at 120 km/h under cold (−10 °C, cabin heating) and mild (23 °C, no AC) weather scenarios. An optimization model was developed to minimize total trip time by adjusting the number and duration of charging stops, including a 5 min detour for each charging session. Results show that the optimal charging cutoff point consistently emerges around 59% SoC, with a typical deviation of 10, regardless of ambient temperature. Charging beyond 70% SoC is generally inefficient unless dictated by charging station availability. The optimal strategy involves increasing the number of shorter stops—typically every 2–3 h of driving—thereby reducing total trip. Full article

Objective: The P-POSSUM scale is widely used in predicting perioperative morbidity and mortality. Evidence on the performance of P-POSSUM in predicting outcomes after cytoreductive surgery (CRS) for ovarian cancer (OC) is limited. In this study, we assess how well P-POSSUM predicts morbidity in OC CRS and explore whether incorporating additional clinical variables can enhance its predictive accuracy. We retrospectively collected data on consecutive patients undergoing OC CRS within a tertiary gynaecologic oncology network. The collected information included demographic characteristics, P-POSSUM morbidity and mortality scores, Edmonton Frail Scale (EFS) scores, preoperative serum albumin levels, and observed 30-day postoperative morbidity and mortality, classified using the Clavien–Dindo (CD) scale. The predictive performance of P-POSSUM was evaluated using receiver operating characteristic (ROC) curves to calculate sensitivity and specificity. A stepwise regression analysis was then applied to identify additional variables that could improve model performance, incorporating preoperative covariates. The final model incorporated parameters chosen through bootstrap investigation of the model variability (stepAIC). Predicted versus observed morbidity was calibrated and performance compared between P-POSSUM and the final model. Results: Of 161 sequential OC patients, 95 (59%) underwent primary, 45 (28%) interval, and 21 (13%) delayed CRS. The mean age was 66.4 (95%CI: 60–75) and duration of surgery was 223 mins (95%CI: 142–279). Sixty-five (40.3%) patients had ≥1 postoperative complication. Two deaths were reported. Among the observed complications, 4 patients (6.1%) experienced CD4, 10 patients (15.3%) CD3, 38 patients (58.5%) CD2, and 11 patients (16.9%) CD1 events. The mean P-POSSUM-predicted morbidity and mortality were 59.5% (95%CI: 56.7–62.3%) and 5.86% (95%CI: 5.02–6.70%), respectively. The area under the curve (AUC) for P-POSSUM in predicting morbidity and mortality was 0.539 (p = 0.401) and 0.569 (p = 0.137), respectively. Given the small number of deaths, no robust conclusions regarding mortality are possible. EFS and BMI emerged as significant predictors of observed morbidity using a stepwise-model selection process. The AIC of this final model was 211.44. Our final model of PPOSSUM + EFS + BMI had AUC = 0.6551 (Delong’s Z = 1.8845, p-value = 0.05949). Conclusions: The P-POSSUM scale shows poor performance for predicting morbidity in OC CRS. New validated and accurate model(s) are necessary for predicting surgical morbidity. Our proposed model incorporates additional variables to improve P-POSSUM’s performance. This requires further development and validation. Full article

Lutein is one of carotenoids in the human brain that is consistently associated with all cognitive performance indicators, and its levels are closely linked to age-related cognitive decline. However, lutein application is limited by its poor stability and low bioaccessibility. In this study, a lutein-loaded delivery system was developed to enhance stability and achieve brain-targeting effects. Using high-speed shear and ethanol hydration methods, PEGylated lutein liposomes with lactoferrin (Lf-LLips) were constructed and characterized. The morphology was observed using TEM and AFM. Particle sizes and lutein retention rates were evaluated under different temperatures (4 °C, 25 ± 2 °C, 50 °C), light (diffusion light, DL; light shielding, LS), and storage durations at 28 d. Compared with free lutein, the in vitro release behavior and permeability across the blood–brain barrier of the systems were investigated. Lf-LLips exhibited a particle size of 186.63 ± 2.04 nm and a potential of −30.53 ± 1.65 mV, and the lutein encapsulation efficiency was 83.11 ± 1.67%. When stored under LS, the particle size of Lf-LLips remained under 190 nm at 4 °C for 28 days, and the retention rate of lutein exceeded 80%. The release curve of Lf-LLips in vitro over 72 h followed the Weibull model. Furthermore, the permeability across the blood–brain barrier model within 12 h was 22.73 ± 1.42%. These results demonstrate that Lf-LLips significantly improve the stability of lutein and exhibit sustained-release properties along with brain-targeting efficiency. The findings demonstrate the promising future of lutein for applications in brain health enhancement. Full article

The competitive adsorption between phosphorus (V) and antimony (V) may influence the release of antimony from Sb-contaminated soils. The objectives of this study were to evaluate the effect of P(V) on the adsorption–desorption behavior and transport of Sb(V) in two typical soil types. Specifically, the simultaneous adsorption, competitive interactions, and miscible displacement dynamics of P(V) and Sb(V) in these soils were investigated. Results clearly indicated that the competitive effect of P(V) on Sb(V) adsorption is more pronounced in acidic red soil than in alkaline calcareous soil. The adsorption capacity of Sb(V) decreased with increasing solution pH, leading to greater mobility of Sb(V) in both soils. P(V) was preferentially adsorbed over Sb(V) in both soil types. Sb(V) adsorption isotherms fitting by Freundlich model yielded higher coefficients of determination (R²) compared to the Langmuir model, while the Langmuir model provided a good fit to the P(V) adsorption isotherms. The total released amounts of P(V) and Sb(V) accounted for 0% and 0.4%, respectively, in red soil and 2.7% and 48.6%, respectively, in calcareous soil, relative to their adsorption capacities. The red soil exhibited remarkably strong binding affinity, with only minimal amounts of P(V) and Sb(V) released after five consecutive desorption steps. Breakthrough curves (BTCs) revealed that the presence of P(V) can promote significant Sb(V) release from the soils, which persists over an extended duration. This study on the adsorption–desorption behavior of P(V) and Sb(V) in two typical soils enhances our understanding of their mobility, fate, and associated environmental risks. In conclusion, the assessment of environmental risks from antimony-contaminated soils should take into account the competitive adsorption–desorption interactions between Sb(V) and P(V). Full article

Banana fibres (BFs), derived from the pseudo-stems of Musa acuminata, represent a widely available agricultural residue with strong potential as an eco-friendly reinforcement in composite materials—particularly in bio-based epoxy or thermoplastic systems used in automotive interiors, packaging, and lightweight construction. However, their inherent variability presents challenges for consistent and reliable mechanical characterisation. This study investigates the effect of wood ash treatment, an eco-friendly alternative to conventional alkaline processing, on the tensile strength of single BFs. Fibres were treated in aqueous wood ash solutions at two pH levels (12.4 and 13.5) and soaking durations of 3 h and 24 h, and then tested according to ASTM C1557. At least 50 valid tensile tests per series were performed, and the results were analysed using a two-parameter Weibull distribution to quantify characteristic strength and variability, complemented by reliability analysis to assess survival probability. Untreated fibres exhibited low characteristic strength (396.6 MPa) and a Weibull modulus of 1.79, confirming significant scatter. Treated fibres showed marked improvements: the highest characteristic strength was achieved at pH 13.5 for 3 h (552.8 MPa, m = 3.17), while the greatest uniformity was observed at pH 13.5 for 24 h (m = 4.62). Reliability curves confirmed superior performance of treated fibres, with 75% survival strengths up to 373 MPa compared to 198 MPa for untreated. These findings demonstrate that wood ash treatment enhances both the strength and reliability of BFs for sustainable composite applications. Full article

Background: Microsurgical skill acquisition and development are complex processes, due to the often complex learning curve, limited training possibilities, and growing restrictions on working hours. Simulation-based training programmes, employing various models, have been proposed. Nevertheless, the extent to which these training programmes are supported by scientific evidence is unclear. The aim of this systematic review is to evaluate the extent and quality of the scientific evidence backing validated microsurgical training programmes. Methods: A systematic literature review was conducted, following a study protocol established a priori and in accordance with the PRISMA guidelines. The databases searched were the Web of Science Core Collection (Web of Knowledge), Medline (Ovid), Embase (Embase.com), and ERIC (Ovid). Studies were included if they described microsurgical training programmes and presented a form of validation of training effectiveness. Data extraction included the number of participants, training duration and frequency, validation type, assessment methods, outcomes, study limitations, and a detailed training regimen. The risk of bias and quality were assessed using the Medical Education Research Study Quality Instrument (MERSQI). Validity was assessed using an established validity framework (content, face, construct, and criterion encompassing both concurrent and predictive validity). The Level of Evidence (LoE) and Recommendation (LoR) were evaluated using the Oxford Centre for Evidence-Based Medicine (OCEBM). Results: A total of 25 studies met the inclusion criteria. Training programmes were classified into one-time intensive courses or longitudinal curricula. Face, content, and construct validity were the most commonly assessed aspects, while predictive validity was the least frequently assessed and not properly evaluated. Training models ranged from low-fidelity (silicone tubes, synthetic vessels) to high-fidelity (live animal models). The Global Rating Scale (GRS), the Structured Assessment of Microsurgery Skills (SAMS), and the Objective Structured Assessment of Technical Skills (OSATS) were the most frequently used objective assessment tools for evaluation methods within the programmes. The risk of bias MERSQI score was 12.96, ranging from 10.5 to 15.5, and LoE and LoR scores were moderated. Across the studies, 96% reported significant improvement in microsurgical skills among participants. However, most studies were limited by small sample sizes, heterogeneity in baseline skills, and a lack of long-term follow-up. Conclusions: While validated microsurgical training programmes improve skill acquisition, challenges remain in terms of standardisation and best cost-effective methods. Future research should prioritise evaluating predictive validity, creating standardised objective assessment tools, and focus on skill maintenance. Full article

Missing values in hourly outdoor air temperature series are common and can bias building energy assessments that rely on uninterrupted temperature profiles. This paper examines how the polynomial degree can be used to reconstruct incomplete temperature data from the duration curve, which affect the energy indicators of an air-source heat pump (ASHP). Using an operational dataset from Opole, Poland (1 September 2019–31 August 2020; 5.1% gaps), global polynomials of degree n = 3…11 were fitted to the sorted hourly temperatures, and the reconstructions were mapped back to time. The reconstructions drive a building–ASHP model evaluated for two supply-water regimes (L_WT, leaving water temperature = 35 °C and 45 °C). Accuracy is assessed with mean absolute error (MAE), root-mean-square error (RMSE), and R² on observed, filled, and full subsets—including cold/hot tails—and propagated to energy metrics: seasonal space-heating demand (Q_season); electricity use (E_el); seasonal coefficient of performance (SCOP); peak electrical power (P_el,max); seasonal minimum coefficient of performance (COP_min); and the share of error due to filled hours (WFE_fill). All degrees satisfy $\left|{RE}_{Q_{season}}\right|\le 2\%$. For L_WT = 35 °C, relative changes span ${RE}_{E_{el}}$ ≈ −2.22…−1.63% and ${RE}_{N_{el,max}}$ ≈ −21.6…−7.7%, with ${ER}_{SCOP}$ ≈ +0.53…+0.80%. For L_WT = 45 °C, ${RE}_{E_{el}}$ remains ≈ −0.43% across degrees. A multi-criterion selection (seasonal bias, stability of energy indicators, tail errors, and WFE_fill) identifies n = 7 as the lowest sufficient degree: increasing n beyond seven yields negligible improvements while raising the overfitting risk. The proposed, data-driven procedure makes degree selection transparent and reproducible for gap-filled temperature inputs in ASHP studies. Full article

Population mobility links cities, propelling the spatiotemporal spread of urban pandemics and adding complexity to disease dynamics. It also closely shapes, and is shaped by, the selection and intensity of intervention measures. Revealing the multistage spatial-temporal dynamics of cross-regional epidemic continuity under this interaction is often overlooked but critically important. This study innovatively applies a self-organizing map (SOM) neural network to classify cities into six distinct types based on population mobility characteristics: high-inflow core (HIC), low-inflow core (LIC), low-inflow sub-core (LISC), high-outflow semi-peripheral (HOSP), equilibrious semi-peripheral (ESP), and low-outflow peripheral (LOP). Building on this, we propose a novel SEIR-AHQ theoretical framework and construct an epidemiological model using network-coupled ordinary differential equations (ODEs). This model captures the dynamic interplay between inter-city population mobility and intervention measures, and quantifies how heterogeneous city types shape the evolution of epidemic transmission across the coupled mobility network. The results show that: (1) Cities with stronger population mobility face significantly higher infection risks and longer epidemic durations, characterized by “higher peaks and longer tails” in infection curves. HIC cities experience the greatest challenges, and LOP cities experience the least. (2) Both higher transmission rates and delayed intervention timings lead to exponential growth in infections, with nonlinear effects amplifying small changes disproportionately. (3) Intervention efficacy follows a “diminishing marginal returns” pattern, where the incremental benefits of increasing intervention intensity gradually decrease. This study offers a novel perspective on managing interregional epidemics, providing actionable insights for crafting tailored and effective epidemic response strategies. Full article

Background/Objectives: Adolescent idiopathic scoliosis (AIS) is a three-dimensional deformity of the spine that can negatively impact on quality of life, pulmonary function, and body image. Its conservative management includes various interventions, among which the Schroth method stands out. This approach is based on three-dimensional corrective exercises and rotational breathing. This review aimed to analyze the effectiveness of the Schroth method, applied either alone or in combination with other conservative therapies, on variables such as Cobb angle, angle of trunk rotation (ATR), pulmonary function, and health-related quality of life in patients with AIS. Methods: A scientific literature search was conducted using the PubMed database. We searched for randomized controlling trials (RCTs), systematic reviews, and meta-analyses reported in English from 2020 to 2025. Different combinations of the terms and MeSH terms “adolescent”, “idiopathic”, “scoliosis”, and “Schroth” connected with various Boolean operators. Results: Overall, 82 articles were reviewed from the selected database. After removing duplicated papers and title/abstract screening, 13 studies were included in our review. The results showed that the Schroth method proved effective in reducing the Cobb angle and ATR, particularly in patients with mild curves and in early stages of skeletal growth. Improvements were also observed in health-related quality of life and aesthetic perception, and to a lesser extent, in pulmonary function. Moreover, therapeutic adherence and treatment continuity were important to maintaining long-term benefits. Conclusions: The Schroth method could be an effective treatment associated with orthopedic treatment, yielding satisfactory results. Its implementation requires structured programs, professional supervision, and strategies to enhance therapeutic adherence. Nevertheless, to validate its long-term effectiveness, we need more homogeneous studies with longer follow-up durations. Full article

Background/Objectives: Sodium (Na) concentration and the sodium-to-potassium (Na/K) ratio in human milk reflect epithelial tight junction integrity and have been proposed as non-invasive biomarkers of lactational dysfunction, including subclinical mastitis and ductal obstruction. However, their discriminative performance across varied mammary duct conditions, as well as their relevance to milk quality and nutritional integrity, remain underexplored. This study aimed to evaluate the ability of Na, K and the Na/K ratio to discriminate ductal obstruction from non-obstructed lactation—including normal, mixed, and donor milk—and to assess their applicability as nutritional and clinical screening biomarkers. Methods: The study analyzed 635 human milk samples from four groups: obstructed ducts (n = 94), mixed ducts (n = 39), normal ducts (n = 102), and donor milk (n = 400). Na and K concentrations were measured using validated handheld ion-selective electrode analyzers. Statistical analyses included Quade’s ANCOVA and receiver operating characteristic curve analysis, adjusting for infant age, gestational age, birth body weight, maternal age and storage duration. Results: Na concentrations were highest in obstructed ducts (Group A: median 810 ppm, IQR 368–1725) compared with normal ducts (Group C: 220 ppm, IQR 140–283) and donor milk (Group D: 98 ppm, IQR 80–130) (p < 0.001). A similar pattern was observed for the Na/K ratio (Group A: 1.5, IQR 0.6–3.1 vs. Group C: 0.3, IQR 0.2–0.5; Group D: 0.3, IQR 0.2–0.3). After adjusting, both Na and the Na/K ratio remained significantly elevated in milk from obstructed ducts compared to non-obstructed samples (p < 0.001). Donor milk exhibited the lowest and most stable electrolyte levels. Na demonstrated excellent discriminative performance (area under the curve = 0.96), slightly outperforming the Na/K ratio (area under the curve = 0.92). Conclusions: Na concentration and the Na/K ratio in human milk are sensitive and practical biomarkers of mammary gland integrity. Given that Na alone can be measured without additional calculations, its simplicity and strong performance support its application as a potential biomarker for ductal obstruction, with implications for both lactation support and nutritional science. Full article

In patients with respiratory failure, mechanical ventilation aims to balance respiratory muscle loading and gas exchange. The interplay between the ventilator and the respiratory muscles is an increasingly recognized factor in tailoring ventilatory support. Surface electromyography (sEMG) offers a non-invasive modality to monitor the respiratory muscles. The sEMG signal, however, requires elaborate processing, which is limitedly standardized and documented. This paper presents the Respiratory Surface Electromyography (ReSurfEMG) package, an open-source Python package for respiratory sEMG analysis developed to address these challenges. ReSurfEMG integrates denoising, feature extraction, and quality assessment in one dedicated library. The effects of over- and under-filtering were compared to ReSurfEMG default settings regarding waveform duration, time-to-peak, amplitude, electrical time product (ETP), pseudo-slope, pseudo-signal-to-noise ratio (SNR), area under the baseline (AUB), and bell-curve error. Under-filtering increased amplitudes (+21%) and ETPs (+10%). Over-filtering smoothed sEMG waveforms, reducing amplitude (−58%), ETP (−39%), and pseudo-slope (−49%), while waveform duration and time-to-peak increased. Default ReSurfEMG settings provided the highest SNRs with similar or lower AUBs and bell-curve errors. The ReSurfEMG library integrates advanced methods dedicated to respiratory sEMG analysis. Systematic assessment using ReSurfEMG showed that signal processing settings affect sEMG features. ReSurfEMG enables reproducible signal processing, facilitating the standardization of respiratory sEMG analysis. Full article

Background: Retinal microvascular changes may serve as biomarkers for disease activity in multiple sclerosis (MS). This study evaluated macular and peripapillary vascular plexus densities using optical coherence tomography angiography (OCTA) in patients with relapsing MS (RMS) and healthy controls (HCs), exploring their association with disease activity based on the NEDA-3 concept. Methods: In a cross-sectional study, 117 RMS patients and 37 HCs underwent OCTA imaging. Parameters analyzed included superficial vascular plexus (SVP), deep vascular plexus (DVP), foveal avascular zone (FAZ), and radial peripapillary capillary (RPC) density. Images with artifacts were excluded. Associations between OCTA metrics and demographic, clinical, and MRI volumetrics, as well as NEDA-3 status, were evaluated using multivariate generalized estimating equations. Receiver operating characteristic (ROC) curves assessed predictive capacity. Results: Compared to HCs, MS eyes with prior optic neuritis showed significantly lower SVP density (p < 0.05). DVP and FAZ parameters did not differ between groups. SVP and DVP densities correlated with age, disease duration, relapse history, and MRI volumetrics, including gray matter and whole brain volume. SVP density predicted NEDA-3 status (AUC = 0.82), while DVP also showed predictive value (AUC = 0.64). FAZ FD (Foveal density) was associated with gray matter and whole brain atrophy (AUC = 0.62–0.61). Conclusions: Retinal vascular alterations correlate with clinical and MRI measures in MS. Reduced SVP and DVP densities may serve as markers of recent disease activity, and FAZ metrics reflect neurodegeneration. OCTA may be a valuable non-invasive tool for monitoring MS progression. Full article

Synthetic food colourings are widely used because they are stable, inexpensive, reliable, and effective in shaping consumer perception and behaviour, even though some are under scrutiny for adverse health effects. In this work, we present a new sensitive voltammetric method for the determination of brilliant blue FCF (BB) using a cyclic renewable silver-based mercury film electrode (Hg(Ag)FE). The experimental parameters, including pulse height, step potential, preconcentration potential and duration, and the composition of the supporting electrolyte, were systematically optimised. Under these conditions, the calibration curve exhibited linearity within the range of 0.7 up to 250 µg L⁻¹. For an Hg(Ag)FE with a surface area of 10.9 mm², with a short preconcentration step of 15 s, the limits of detection (LOD) and quantification (LOQ) of BB were 0.24 µg L⁻¹ and 0.72 µg L⁻¹, respectively. The repeatability of the method at a concentration level of the analyte as low as 2.0 µg L⁻¹, expressed as RSD, was 2.39% (n = 6). The proposed method was successfully applied in the analysis of brilliant blue FCF in popular beverages and artificial juices. The obtained results not only verify that BB levels are within acceptable limits, but also enrich the limited data on the quantitative compositions of ‘popular’ beverages. Full article

Background/Objectives: Baricitinib, a selective Janus kinase (JAK) 1 and 2 inhibitor, has recently emerged as a therapeutic option for patients with severe alopecia areata (AA). The aim of this study was to identify clinical and biological predictors of early therapeutic response to baricitinib in patients with AA in real-world clinical practice. Methods: A retrospective cohort study was conducted including patients with AA initiating baricitinib between January 2022 and January 2025. Patients were stratified into early responders and non-early responders. Univariate and multivariate logistic regression analyses were performed to assess factors independently associated with early therapeutic response. Results: A total of 44 patients with AA treated with baricitinib were included, the majority being female (65.9%, 29/44), with a mean age of 37.3 years (SD 16.1). Early responders accounted for 34.1% (15/44) of the cohort. In multivariate analysis, early response to baricitinib was independently associated with a lower baseline Severity of Alopecia Tool (SALT) score, shorter disease duration, and elevated erythrocyte sedimentation rate (ESR) at baseline (p < 0.05). Receiver Operating Characteristic (ROC) curve analyses were performed to determine optimal thresholds for predicting early therapeutic response: ESR ≥ 9 mm/h, baseline SALT score ≤ 60%, and disease duration ≤ 7 years. Conclusions: Baseline stratification using easily obtainable clinical and laboratory parameters may help identify patients most likely to benefit from initiating treatment with baricitinib. Our findings support the existence of a therapeutic window of opportunity in AA, particularly in patients with lower disease burden, shorter disease duration, and elevated ESR values. Full article

This work investigates and compare the corrosion behavior in artificial saliva of oxide thin films grown on commercially pure titanium (cp-Ti), via electrochemical oxidation (EO) in sulphate bath at 1 V and thermal treatment (TT) at 450 °C, for durations between 20 min and 4 h. The ultimate goal is to determine which method and duration provide the optimal protection for titanium against degradation in dental environment particularly in varying fluoride concentration and acidity. Surface characterizations were performed through morphological and microstructural analysis using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD). Electrochemical behavior was conducted in Fusayama-Meyer solution (pH = 6.50 and T = 37 °C) using potentiodynamic polarization curve (PPC) and electrochemical impedance spectroscopy (EIS), under varying pH and fluoride ion concentrations. The results demonstrated that a 3-h duration treatment provided the optimal corrosion resistance for both EO and TT processes. The pH of the environment influenced corrosion performance markedly: both acidic (pH 2.5) and basic (pH 9.0) conditions increased I_corr and decreased R_p, indicating degradation of the passive oxide layer outside neutral conditions. Similarly, increasing fluoride concentrations (1000; 5000; and 12,300 ppm) significantly impaired corrosion resistance. At 12,300 ppm F⁻, untreated Ti showed severe degradation, with EIS revealing the formation of a porous outer layer and a weakened inner barrier layer (R_f = 33 W·cm² for the outer layer and R_ct = 21 kW·cm² for the barrier layer). In contrast, the TT-treated surface remained highly protective even under these aggressive conditions, with minimal surface damage and the highest resistances for both the outer and the inner layers (R_f = 1610 kW·cm²; R_ct = 1583 kW·cm²), significantly outperforming the EO film. These findings highlight the superior performance of thermal oxidation at 450 °C for 3 h as a promising surface treatment for enhancing the corrosion resistance of titanium in fluoride-rich oral environments. Understanding these strategies helps improve the longevity and security of titanium dental implants. Full article