Search Results (598)

Background: Chronic stress in childhood and adolescence leads to excessive cortisol secretion, adipokines production and obesity with all the negative mental and physical effects on the health of individuals and adulthood. Objectives: The aim of the present non-randomized controlled trial was to investigate the effect of a stress management protocol with diaphragmatic breathing (DB) and physiotherapy exercise on stress, body composition, cardiorespiratory and metabolic markers of children and adolescents with morbid obesity. Methods: The study included 31 children and adolescents (5–18 years old) with morbid obesity (22 in the intervention arm and 9 controls). All participants completed anxiety questionnaires and a self-perception scale. Forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), blood pressure (BP) and SpO₂ were measured. Fasting glucose, uric acid, triglycerides, HbA1c, (AST/SGOT), (ALT/SGPT), HDL, LDL, insulin, ACTH, cortisol, HOMA-IR, 17-OH, S-DHEA, SHBG were assessed, and anthropometric measurements were also performed. Results: In the intervention group, 4 months after the treatment, an improvement was noted in the BMI, BMI z-score, waist-to-height ratio, FEV1, SpO₂, pulse and systolic BP. HDL increased, ALT/SGPT and insulin resistance improved. Positive changes were observed in temporary and permanent stress and self-esteem of children in the intervention group, including anxiety, self-perception, physical appearance, etc. Conclusions: A combined exercise and DB protocol has a positive effect on stress, by improving body composition, reducing insulin resistance, and ameliorating physical and mental health and quality of life of pediatric patients with morbid obesity. Full article

Hemoglobin plays a critical role in diagnosing various medical conditions, including infections, trauma, hemolytic disorders, and Mediterranean anemia, which is particularly prevalent in Mediterranean populations. Conventional measurement methods require blood sampling and laboratory analysis, which are often time-consuming and impractical during emergency situations with limited medical infrastructure. Although portable oximeters enable non-invasive hemoglobin estimation, they still require physical contact, posing limitations for individuals with circulatory or dermatological conditions. Additionally, reliance on disposable probes increases operational costs. This study presents a non-contact and automated approach for estimating total hemoglobin levels from facial video data using three-dimensional regression models. A dataset was compiled from 279 volunteers, with synchronized acquisition of facial video and hemoglobin values using a commercial pulse oximeter. After preprocessing, the dataset was divided into training, validation, and test subsets. Three 3D convolutional regression models, including 3D CNN, channel attention-enhanced 3D CNN, and residual 3D CNN, were trained, and the most successful model was implemented in a graphical interface. Among these, the residual model achieved the most favorable performance on the test set, yielding an RMSE of 1.06, an MAE of 0.85, and a Pearson correlation coefficient of 0.73. This study offers a novel contribution by enabling contactless hemoglobin estimation from facial video using 3D CNN-based regression techniques. Full article

Monitoring Peripheral Oxygen Saturation (SpO₂) is an important vital sign both in Intensive Care Units (ICUs), during surgery and convalescence, and as part of remote medical consultations after of the COVID-19 pandemic. This has made the development of new SpO₂-measurement tools an area of active research and opportunity. In this paper, we present a new Deep Learning (DL) combined strategy to estimate SpO₂ without contact, using pre-magnified facial videos to reveal subtle color changes related to blood flow and with no calibration per subject required. We applied the Eulerian Video Magnification technique using the Hermite Transform (EVM-HT) as a feature detector to feed a Three-Dimensional Convolutional Neural Network (3D-CNN). Additionally, parameters and hyperparameter Bayesian optimization and an ensemble technique over the dataset magnified were applied. We tested the method on 18 healthy subjects, where facial videos of the subjects, including the automatic detection of the reference from a contact pulse oximeter device, were acquired. As performance metrics for the SpO₂-estimation proposal, we calculated the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and other parameters from the Bland–Altman (BA) analysis with respect to the reference. Therefore, a significant improvement was observed by adding the ensemble technique with respect to the only optimization, obtaining 14.32% in RMSE (reduction from 0.6204 to 0.5315) and 13.23% in MAE (reduction from 0.4323 to 0.3751). On the other hand, regarding Bland–Altman analysis, the upper and lower limits of agreement for the Mean of Differences (MOD) between the estimation and the ground truth were 1.04 and −1.05, with an MOD (bias) of −0.00175; therefore, MOD $\pm 1.96\sigma$ = −0.00175 ± 1.04. Thus, by leveraging Bayesian optimization for hyperparameter tuning and integrating a Bagging Ensemble, we achieved a significant reduction in the training error (bias), achieving a better generalization over the test set, and reducing the variance in comparison with the baseline model for SpO₂ estimation. Full article

p-Cresyl sulfate (PCS), a gut-derived uremic toxin with proinflammatory and cytotoxic effects, has been implicated in cardiovascular injuries among patients with chronic kidney disease (CKD). Aortic stiffness (AS), assessed by carotid–femoral pulse wave velocity (cfPWV), is a recognized predictor of cardiovascular risk. This study investigated the association between serum PCS levels and AS in patients with nondialysis-dependent CKD. In total, 165 patients with nondialysis-dependent CKD were enrolled. Clinical data and fasting blood samples were collected. Arterial stiffness (AS) was assessed bilaterally by measuring carotid–femoral pulse wave velocity (cfPWV) on both the left and right sides. A value above 10 m/s was considered indicative of increased stiffness. Serum PCS levels were quantified using high-performance liquid chromatography–mass spectrometry. Fifty patients (30.3%) had AS. The AS group was significantly older and had higher diabetes prevalence, systolic blood pressure, fasting glucose, urinary protein-creatinine ratio, and PCS levels than the control group. In the multivariate analysis, both PCS (odds ratio [OR]: 1.097; 95% confidence interval [CI]: 1.024–1.175; p = 0.008) and age (OR: 1.057; 95% CI: 1.025–1.090; p < 0.001) were independently associated with AS. In conclusion, elevated serum PCS and older age were independently associated with AS. Thus, PCS is a potential early marker of vascular damage in CKD. Full article

Background: Ambulatory blood pressure monitoring (ABPM) is increasingly recognized as a more reliable indicator of blood pressure status in children than clinic-based measurements, with superior predictive value for cardiovascular morbidity and mortality. However, evidence on the clinical utility of ABPM-derived indices, such as pulse pressure (PP), pulse pressure index (PPI), rate pressure product (RPP), ambulatory arterial stiffness index (AASI), and average real variability (ARV), remains underexplored in the pediatric population, particularly among children with chronic kidney disease (CKD). Objective: To evaluate the correlation between ABPM-derived indices in children, with a subgroup analysis comparing those with and without CKD. Secondary objectives included identifying factors associated with AASI and ARV and assessing their utility in cardiovascular risk stratification. Methods: In this bicentric cross-sectional study, 70 children (41 with CKD and 29 controls) were enrolled. ABPM indices (PP, PPI, RPP, AASI, and ARV) were calculated, and both descriptive and inferential statistical analyses, including linear regression, were performed. Results: Systolic and diastolic hypertension were significant predictors of elevated ARV (p < 0.05), while body mass index (BMI) and glomerular filtration rate (GFR) were positively associated with AASI (p < 0.05). Use of angiotensin-converting enzyme inhibitors (ACEIs) was associated with reduced arterial stiffness (p = 0.02). Significant differences were observed in weight, BMI, PP, and PPI between the CKD and non-CKD groups, with ABPM demonstrating greater sensitivity in detecting vascular health markers. Conclusions: ABPM-derived indices, particularly PP, PPI, and ARV, show promise in improving cardiovascular risk assessment in children. These findings support the broader use of ABPM metrics for refined cardiovascular evaluation, especially in pediatric CKD. Full article

The awareness of the importance of monitoring human vital signs has increased recently due to the outbreak of the COVID-19 pandemic. Non-invasive heart rate monitoring devices, in particular, have become some of the most popular tools for health monitoring. However, heart rate data alone are not enough to reflect the health of one’s cardiovascular function or arterial health. This growing interest has spurred research into developing high-fidelity non-invasive pulse waveform sensors. These sensors can provide valuable information such as data on blood pressure, arterial stiffness, and vascular aging from the pulse waveform. Among these sensors, optical fiber sensors (OFSs) stand out due to their remarkable properties, including resistance to electromagnetic interference, capability in monitoring multiple vital signals simultaneously, and biocompatibility. This paper reviews the latest advancements in using OFSs to measure human vital signs, with a focus on pulse waveform analysis. The various working mechanisms of OFSs and their performances in measuring the pulse waveform are discussed. In addition, we also address the challenges faced by OFSs in pulse waveform monitoring and explore the opportunities for future development. This technology shows great potential for both clinical and personal non-invasive pulse waveform monitoring applications. Full article

Intracranial pressure (ICP) pulse wave morphology, including the ratios of the three characteristic peaks (P1, P2, and P3), offers valuable insights into intracranial dynamics and brain compliance. Traditional invasive methods for ICP pulse wave monitoring pose significant risks, highlighting the need for non-invasive alternatives. This pilot study investigates a novel non-invasive method for monitoring ICP pulse waves through closed eyelids, using a specially designed, liquid-filled, fully passive sensor system named ‘Archimedes 02’. To our knowledge, this is the first technological approach that enables the non-invasive monitoring of ICP pulse waveforms via closed eyelids. This study involved 10 healthy volunteers, aged 26–39 years, who underwent resting-state non-invasive ICP pulse wave monitoring sessions using the ‘Archimedes 02’ device while in the supine position. The recorded signals were processed to extract pulse waves and evaluate their morphological characteristics. The results indicated successful detection of pressure pulse waves, showing the expected three peaks (P1, P2, and P3) in all subjects. The calculated P2/P1 ratios were 0.762 (SD = ±0.229) for the left eye and 0.808 (SD = ±0.310) for the right eye, suggesting normal intracranial compliance across the cohort, despite variations observed in some individuals. Physiological tests—the Valsalva maneuver and the Queckenstedt test, both performed in the supine position—induced statistically significant increases in the P2/P1 and P3/P1 ratios, supporting the notion that non-invasively recorded pressure pulse waves, measured through closed eyelids, reflect intracranial volume and pressure dynamics. Additionally, a transient hypoemic/hyperemic response test performed in the upright position induced signal changes in pressure recordings from the ‘Archimedes 02’ sensor that were consistent with intact cerebral blood flow autoregulation, aligning with established physiological principles. These findings indicate that ICP pulse waves and their dynamic changes can be monitored non-invasively through closed eyelids, offering a potential method for brain monitoring in patients for whom invasive procedures are not feasible. Full article

Background: Systemic arterial stiffness and atherosclerosis have been increasingly recognized as potential contributors to the pathogenesis of glaucoma. Several studies have reported associations between glaucoma and various surrogate markers of vascular stiffness. However, despite the growing interest in the vascular components of glaucoma, no previous studies have specifically explored the relationship between the indices derived from acceleration plethysmography (APG) and glaucoma. This study seeks to address this gap by investigating the potential association between APG parameters and the presence of glaucoma. Methods: The subjects were 701 patients (mean age 68.6 years, 54% male) with open-angle glaucoma (primary open-angle glaucoma [POAG] or exfoliation glaucoma [EXG]), and 94 control subjects (mean age 60.1 years, 57% male) who had no eye diseases other than cataracts. The subjects were all cases in which APG was measured using a sphygmograph (TAS9 Pulse Analyzer Plus View; YKC Corp., Tokyo, Japan). The amplitude of waveform types (a, b, c, d, and e-waves) and derived vascular types (A, B, and C) of the accelerated pulse wave components were statistically compared between the cases and controls. Results: The accelerated pulse wave components (mean ± standard deviation) of the control and glaucoma groups were a-wave 785 ± 99 and 776 ± 93 (p = 0.40), b-wave −522 ± 161 and −491 ± 143 (p = 0.050), c-wave −142 ± 108 and −156 ± 105 (p = 0.24), d-wave −288 ± 144 and −322 ± 122 (p = 0.014), and e-wave 103 ± 79 and 90 ± 58 (p = 0.059), with differences between the groups being observed in the b and d-waves. For derived vascular types, compared with the controls and POAG, patients with EXG had a lower frequency of Type A and a higher frequency of Type C than the other groups (p = 0.044). Multivariate analysis showed that factors significantly associated with vascular type included age (p < 0.0001), sex (p < 0.0001), diastolic blood pressure (p = 0.021), and pulse rate (p < 0.0001), while BMI, systolic blood pressure, history of hypertension, history of diabetes, presence or absence of glaucoma, and presence or absence of pseudoexfoliation material were not significant. Conclusions: This is the first study to investigate the relationship between APG and glaucoma with a large sample size. In elderly glaucoma patients, particularly those with EXG, systemic vascular changes are often present. APG parameters may reflect vascular alterations in glaucoma. Full article

The monitoring of peripheral electrical bioimpedance (EBI) variations is a promising method that has the potential to replace invasive or burdensome techniques for cardiovascular measurements. Segmental or continuous recording of peripheral pulse waves can serve as a basis for calculating prognostic markers like pulse wave velocity (PWV) or include parameters such as pulse transit time (PTT) or pulse arrival time (PAT) for noninvasive blood pressure (BP) estimation, as well as potentially novel cardiovascular risk indicators. However, several technical, analytical, and interpretative aspects need to be resolved before the EBI method can be adopted in clinical practice. Our goal was to investigate and improve the application of EBI, executing its comparison with other cardiovascular assessment methods in patients hospitalized for coronary catheterization procedures. Methods: We analyzed data from 44 non-acute patients aged 45–74 years who were hospitalized for coronary catheterization at East Tallinn Central Hospital between 2020 and 2021. The radial EBI and electrocardiogram (ECG) were measured simultaneously with central and contralateral pressure curves. The Savitzky–Golay filter was used for signal smoothing. The Hankel matrix decomposer was applied for the extraction of cardiac waveforms from multi-component signals. After extracting the cardiac component, a period detection algorithm was applied to EBI and blood pressure curves. Results: Seven points of interest were detected on the pressure and EBI curves, and four with good representativeness were selected for further analysis. The Spearman correlation coefficient was low for all but the central and distal pressure curve systolic upstroke time points. A high positive correlation was found between PWV measured both invasively and with EBI. The median value of complimentary pulse wave velocity (CPWV), a parameter proposed in the paper, was significantly lower in patients with normal coronaries compared to patients with any stage of coronary disease. Conclusions: With regard to wearable devices, the EBI-derived PAT can serve as a substrate for PWV calculations and cardiovascular risk assessment, although these data require further confirmation. Full article

Blood pressure is a vital indicator of cardiovascular health and plays a crucial role in the early detection and management of heart-related diseases. However, current practices for recording blood pressure readings are still largely manual, leading to inefficiencies and data inconsistencies. To address this challenge, we propose a deep learning-based method for automated digit recognition and measurement-type classification (systolic, diastolic, and pulse) from images of blood pressure monitors. A total of 2147 images were collected and expanded to 3649 images using data augmentation techniques. We developed and trained three YOLOv8 variants (small, medium, and large). Post-training quantization (PTQ) was employed to optimize the models for edge deployment in a mobile health (mHealth) application. The quantized INT8 YOLOv8-small (YOLOv8s) model emerged as the optimal model based on the trade-off between accuracy, inference time, and model size. The proposed model outperformed existing approaches, including the RT-DETR (Real-Time DEtection TRansformer) model, achieving 99.28% accuracy, 96.48% F1-score, 641.40 ms inference time, and a compact model size of 11 MB. The model was successfully integrated into the mHealth application, enabling accurate, fast, and automated blood pressure tracking. This end-to-end solution provides a scalable and practical approach for enhancing blood pressure monitoring via an accessible digital platform. Full article

Background/Objectives: Hypertension is strongly linked to changes in vascular function and lipid metabolism. This study aimed to examine the relationship between lipid profiles, various metabolic biomarkers, and pulse wave analysis in patients with hypertension. Methods: A group of 66 hypertensive patients, aged 64 ± 10 years, participated in pulse wave analysis utilizing an oscillometric device. Multiple lipid serum biomarkers were assessed, such as total cholesterol (TC), triglycerides (TG), and non-HDL cholesterol (non-HDL). Lipid balance index (LBI) was determined by considering TG, LDL, HDL levels, and lipid-lowering medications. Results: Notable correlations were observed for SBP, DBP, and early vascular aging (EVA) with lipid biomarkers. In addition to serum lipids, metabolic syndrome, insulin resistance, and non-alcoholic fatty liver disease (NAFLD) were significantly linked to pulse wave analysis variables. Multiple regression analysis showed that only TC continued to have a significant association with DBP. Conclusions: Total cholesterol, triglycerides, non-HDL cholesterol, and lipid balance index provide information about systolic and diastolic blood pressure, as well as early vascular aging in hypertensive patients. LBI offers valuable vascular insights in hypertensive individuals with cardiovascular risk factors, early vascular aging, insulin resistance, and NAFLD. The connection between metabolic biomarkers and pulse wave measurements in individuals with hypertension offers a comprehensive method for the early identification of vascular injury and could enhance the prediction of major cardiovascular events. Full article

Background: Exercise and nutritional interventions are often recommended to help manage risk related to metabolic syndrome (MetSyn). The co-ingestion of Phyllanthus emblica (PE) with trivalent chromium (Cr) has been purported to improve the bioavailability of chromium and enhance endothelial function, reduce platelet aggregation, and help manage blood glucose as well as lipid levels. Shilajit (SJ) has been reported to have anti-inflammatory, adaptogenic, immunomodulatory, and lipid-lowering properties. This study evaluated whether dietary supplementation with Cr, PE, and SJ, or PE alone, during an exercise and diet intervention may help individuals with risk factors to MetSyn experience greater benefits. Methods: In total, 166 sedentary men and women with at least two markers of metabolic syndrome participated in a randomized, placebo-controlled, parallel-arm, and repeated-measure intervention study, of which 109 completed the study (48.6 ± 10 yrs., 34.2 ± 6 kg/m², 41.3 ± 7% fat). All volunteers participated in a 12-week exercise program (supervised resistance and endurance exercise 3 days/week with walking 10,000 steps/day on non-training days) and were instructed to reduce energy intake by −5 kcals/kg/d. Participants were matched by age, sex, BMI, and body mass for the double-blind and randomized supplementation of a placebo (PLA), 500 mg of PE (PE-500), 1000 mg/d of PE (PE-1000), 400 µg of trivalent chromium (Cr) with 6 mg of PE and 6 mg of SJ (Cr-400), or 800 µg of trivalent chromium with 12 mg of PE and 12 mg of SJ (Cr-800) once a day for 12 weeks. Data were obtained at 0, 6, and 12 weeks of supplementation, and analyzed using general linear model multivariate and univariate analyses with repeated measures, pairwise comparisons, and mean changes from the baseline with 95% confidence intervals (CIs). Results: Compared to PLA responses, there was some evidence (p < 0.05 or approaching significance, p > 0.05 to p < 0.10) that PE and/or Cr with PE and SJ supplementation improved pulse wave velocity, flow-mediated dilation, platelet aggregation, insulin sensitivity, and blood lipid profiles while promoting more optimal changes in body composition, strength, and aerobic capacity. Differences among groups were more consistently seen at 6 weeks rather than 12 weeks. While some benefits were seen at both dosages, greater benefits were more consistently observed with PE-1000 and Cr-800 ingestion. Conclusions: The results suggest that PE and Cr with PE and SJ supplementation may enhance some exercise- and diet-induced changes in markers of health in overweight individuals with at least two risk factors to MetSyn. Registered clinical trial #NCT06641596. Full article

Background/Objectives: This research presents a novel analytical method for breast tumor characterization and tissue classification by leveraging intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) combined with hyperspectral imaging techniques and deep learning. Traditionally, dynamic contrast-enhanced MRI (DCE-MRI) is employed for breast tumor diagnosis, but it involves gadolinium-based contrast agents, which carry potential health risks. IVIM imaging extends conventional diffusion-weighted imaging (DWI) by explicitly separating the signal decay into components representing true molecular diffusion ($D$) and microcirculation of capillary blood (pseudo-diffusion or $D*$). This separation allows for a more comprehensive, non-invasive assessment of tissue characteristics without the need for contrast agents, thereby offering a safer alternative for breast cancer diagnosis. The primary purpose of this study was to evaluate different methods for breast tumor characterization using IVIM-DWI data treated as hyperspectral image stacks. Dice similarity coefficients and Jaccard indices were specifically used to evaluate the spatial segmentation accuracy of tumor boundaries, confirmed by experienced physicians on dynamic contrast-enhanced MRI (DCE-MRI), emphasizing detailed tumor characterization rather than binary diagnosis of cancer. Methods: The data source for this study consisted of breast MRI scans obtained from 22 patients diagnosed with mass-type breast cancer, resulting in 22 distinct mass tumor cases analyzed. MR images were acquired using a 3T MRI system (Discovery MR750 3.0 Tesla, GE Healthcare, Chicago, IL, USA) with axial IVIM sequences and a bipolar pulsed gradient spin echo sequence. Multiple b-values ranging from 0 to 2500 s/mm² were utilized, specifically thirteen original b-values (0, 15, 30, 45, 60, 100, 200, 400, 600, 1000, 1500, 2000, and 2500 s/mm²), with the last four b-value images replicated once for a total of 17 bands used in the analysis. The methodology involved several steps: acquisition of multi-b-value IVIM-DWI images, image pre-processing, including correction for motion and intensity inhomogeneity, treating the multi-b-value data as hyperspectral image stacks, applying hyperspectral techniques like band expansion, and evaluating three tumor detection methods: kernel-based constrained energy minimization (KCEM), iterative KCEM (I-KCEM), and deep neural networks (DNNs). The comparisons were assessed by evaluating the similarity of the detection results from each method to ground truth tumor areas, which were manually drawn on DCE-MRI images and confirmed by experienced physicians. Similarity was quantitatively measured using the Dice similarity coefficient and the Jaccard index. Additionally, the performance of the detectors was evaluated using 3D-ROC analysis and its derived criteria (AUC_OD, AUC_TD, AUC_BS, AUC_TD−BS, AUC_ODP, AUC_SNPR). Results: The findings objectively demonstrated that the DNN method achieved superior performance in breast tumor detection compared to KCEM and I-KCEM. Specifically, the DNN yielded a Dice similarity coefficient of 86.56% and a Jaccard index of 76.30%, whereas KCEM achieved 78.49% (Dice) and 64.60% (Jaccard), and I-KCEM achieved 78.55% (Dice) and 61.37% (Jaccard). Evaluation using 3D-ROC analysis also indicated that the DNN was the best detector based on metrics like target detection rate and overall effectiveness. The DNN model further exhibited the capability to identify tumor heterogeneity, differentiating high- and low-cellularity regions. Quantitative parameters, including apparent diffusion coefficient ($ADC$), pure diffusion coefficient ($D$), pseudo-diffusion coefficient ($D*$), and perfusion fraction ($PF$), were calculated and analyzed, providing insights into the diffusion characteristics of different breast tissues. Analysis of signal intensity decay curves generated from these parameters further illustrated distinct diffusion patterns and confirmed that high cellularity tumor regions showed greater water molecule confinement compared to low cellularity regions. Conclusions: This study highlights the potential of combining IVIM-DWI, hyperspectral imaging techniques, and deep learning as a robust, safe, and effective non-invasive diagnostic tool for breast cancer, offering a valuable alternative to contrast-enhanced methods by providing detailed information about tissue microstructure and heterogeneity without the need for contrast agents. Full article

Background/Objectives: The aim of this study was to investigate the effects of periodontal blood flow on the periapical region during various endodontic disinfection procedures. The hypothesis that periodontal blood flow reduces the increase in root surface temperature during disinfection procedures was tested. Methods: One hundred and twenty extracted human teeth were shortened to 11 mm and the root canal was prepared using the F4 ProTaper Gold system. The specimens were covered with wax and then sealed in a thermoforming sheet, leaving a gap of 0.2 mm. Cannulas were attached to simulate stable fluid circulation. Thermographic evaluation was carried out using an infrared camera. The following methods were chosen for disinfection: I, λ445 nm diode laser (0.6 W, cw); II, λ445 nm diode laser, 3 W, pulsed, duty cycle 50%, 10 Hz; III, λ445 nm diode laser, 3 W, pulsed, duty cycle 75%, 10 Hz; IV, λ970 nm diode laser, 2 W, pulsed, duty cycle 50%, 10 Hz; V, λ970 nm diode laser, 2 W, pulsed, duty cycle 75%, 10 Hz; VI, experimental plasma device (2.5 W, 3.7 V); VII, heat plugger (200.0 °C); VIII, NaOCl 3% (60 °C). The results were analyzed statistically using the Kruskal–Wallis test. When there were significant differences between the groups (p < 0.05), the pairwise Mann–Whitney test with sequential Bonferroni correction was applied. Results: The smallest temperature changes, with a median value of 0.82 °C (max. 2.02 °C, min. 0.15 °C, IQR 0.87 °C), were observed using the laser at a setting of λ445 nm, 0.6 W cw, and a circulation rate of 6 mL/min. The highest temperature changes were measured at a fluid circulation rate of 0 mL/min with a laser setting of λ445 nm, 3 W, pulsed, duty cycle 75% with a median value of 21.7 °C (max. 25.02 °C, min. 20.29 °C, IQR 2.04 °C). Conclusions: Disinfection procedures with laser, NaOCl, and an experimental plasma device can lead to an increase in root surface temperature. With the exception of the heat plugger, no significant temperature changes were observed. This study was conducted in vitro, which may limit the direct applicability of the results to clinical scenarios. Nevertheless, the simulation of blood flow showed a thermally protective effect, suggesting that clinical protocols should consider this variable when selecting thermal disinfection methods. These results support the hypothesis that periodontal blood flow may have a potentially positive influence on temperature changes during disinfection procedures. Full article

With advancing age, blood vessels undergo deterioration that causes structural and functional changes, including a progressive increase in arterial wall stiffness. Since arterial stiffness is closely linked to the potential risks of cardiovascular diseases, which remains the leading cause of global mortality, it has become essential to develop effective techniques for early diagnosis and continuous monitoring over time. Photoplethysmography, a low-cost and non-invasive technology that measures blood volume changes, has gained increasing popularity in recent years and has proven to be a potential valuable tool for estimating arterial stiffness. This study employs an in vitro experimental setup designed to simulate the cardiovascular system performing under controlled velocity and pressure conditions, in which silicone phantom models with different geometric and mechanical properties were implemented to evaluate their stiffness using a pair of photoplethysmographic sensors. These were employed to measure the pulse wave velocity, currently considered the reference technique for estimating arterial stiffness, correlated through the well-known Moens–Korteweg equation. Photoplethysmographic sensors were placed at three specific distances to determine an optimal configuration for assessing arterial stiffness. Results showed the best performance for softer vascular models at a 15 cm sensor distance, with measurements demonstrating satisfactory accuracy. Variability and standard deviation values increased with model stiffness. The aim of this study is to improve the use of photoplethysmographic sensors for monitoring the mechanical properties of blood vessels and, therefore, to prevent potential cardiovascular diseases. Full article