Search Results (6,581)

Background/Objectives: Dizziness is a frequent medical complaint with neurological, otolaryngological, and psychological origins. Imaging studies such as CT (Computer Tomography), cervical X-rays, and ultrasound aid diagnosis, while MRI (Magnetic Resonance Imaging) is crucial for detecting brain abnormalities. Our purpose is to identify structural brain changes associated with vertigo, assess pre-MRI diagnostic approaches, and evaluate treatment strategies. Methods: A case-control study of 232 vertigo patients and 232 controls analyzed MRI findings, pre-MRI examinations, symptoms, and treatments. Statistical comparisons were performed using chi-square and t-tests (p < 0.05). Results: White matter lesions, lacunar infarcts, Circle of Willis variations, and sinusitis were significantly more frequent in vertigo patients (p < 0.05). Pre-MRI diagnostics frequently identified atherosclerosis (ultrasound) and spondylosis (X-ray). Common symptoms included headache, imbalance, and visual disturbances. The most frequent post-MRI diagnosis was Benign Paroxysmal Positional Vertigo (BPPV). Treatments included lifestyle modifications, physical therapy (e.g., Epley maneuver), and pharmacological therapies such as betahistine. Conclusions: MRI revealed structural brain changes linked to vertigo. Pre-MRI assessments are essential for ruling out vascular and musculoskeletal causes. A multidisciplinary treatment approach is recommended. Trial Registration: This study was registered in ClinicalTrials.gov with the trial registration number NCT06848712 on 22 February 2025. Full article

This study proposes a hybrid deep learning framework for predicting vehicle crash frequency (F_i) using nationwide traffic accident and traffic volume data from the United States (2019–2022). Crash frequency is defined as the product of exposure frequency ($N_a$) and crash risk rate ($\lambda$), a structure widely adopted for its ability to separate physical exposure from the crash likelihood. $N_a$ was computed using an extended Safety Performance Function (SPF) that incorporates roadway traffic volume, segment length, number of lanes, and traffic density, while $\lambda$ was estimated using a multilayer perceptron-based deep neural network (DNN) with inputs such as impact speed, road surface condition, and vehicle characteristics. The DNN integrates rectified linear unit (ReLU) activation, batch normalization, dropout layers, and the Huber loss function to capture nonlinearity and over-dispersion beyond the capability of traditional statistical models. Model performance, evaluated through five-fold cross-validation, achieved R² = 0.7482, MAE = 0.1242, and MSE = 0.0485, demonstrating a strong capability to identify high-risk areas. Compared to traditional regression approaches such as Poisson and negative binomial models, which are often constrained by equidispersion assumptions and limited flexibility in capturing nonlinear effects, the proposed framework demonstrated substantially improved predictive accuracy and robustness. Unlike prior studies that loosely combined SPF terms with machine learning, this study explicitly decomposes F_i into $N_a$ and $\lambda$, ensuring interpretability while leveraging DNN flexibility for crash risk estimation. This dual-layer integration provides a unique methodological contribution by jointly achieving interpretability and predictive robustness, validated with a nationwide dataset, and highlights its potential for evidence-based traffic safety assessments and policy development. Full article

Background: Cardiovascular disease (CVD) remains the leading cause of death in Europe. Despite medical advancements, modifiable risk factors—such as obesity, smoking, and physical inactivity—continue to rise, especially in high-demand professional groups like military personnel. The updated SCORE2 model offers broader assessment capabilities compared to the traditional Pol-SCORE system used in Poland. This study aimed to assess and compare cardiovascular risk using both models and evaluate self-awareness of cardiovascular risk factors among military and civilian employees. Methods: The study included military personnel and civilian defense employees who completed a health-related questionnaire and underwent clinical evaluation, including blood pressure measurement and lipid profiling. Cardiovascular risk was assessed using both Pol-SCORE (fatal events only) and SCORE2 (fatal and non-fatal events). Statistical analysis was conducted using standard parametric and nonparametric methods. Results: SCORE2 classified significantly more individuals into high or very high cardiovascular risk categories than Pol-SCORE. Differences were especially pronounced among women and civilians. Elevated blood pressure, overweight, obesity, tobacco use, and stress were commonly observed. Despite a high level of awareness about prevention, regular participation in screening was low, and many respondents underestimated their health risk, indicating the presence of unrecognized or underestimated risk. Conclusions: SCORE2 proves to be a more sensitive and comprehensive tool for cardiovascular risk evaluation. The findings emphasize the urgent need for targeted prevention strategies and health education, especially in high-risk occupational groups such as military personnel. Full article

The National Football League draft is one of the most important events in the creation of a successful franchise in professional American football. Selecting players as part of the draft process, however, is difficult, as a multitude of factors affect decisions to opt for one player over another; a few of these include collegiate statistics, team need and fit, and physical potential. In this paper, we utilize a machine learning approach, with various types of models, to optimize the NFL draft and, in turn, enhance team performances. We compare the selections made by the system to the real athletes selected, and assess which of the picks would have been more impactful for the respective franchise. The specific investigation allows for further research by altering the weighting of specific factors and their significance in this decision-making process to land on the ideal player based on what a specific team desires. Using artificial intelligence in this process can produce more consistent results than high-risk traditional methods. Our approach extends beyond a basic Random Forest classifier by simulating complete draft scenarios with player attributes and team needs weighted. This allows comparison of different draft strategies (best-player-available vs. need-based) and demonstrates improved prediction accuracy over conventional methods. Full article

In response to the technical challenges of traditional reservoir inversion techniques in determining inter-well wavelets and estimating geological statistical parameters, this study proposes an artificial intelligence high-resolution reservoir inversion technique based on seismic waveform constraints. This technology integrates multi-source heterogeneous data such as lithology characteristics, logging curves, and seismic waveforms through a deep learning neural network framework, and constructs an intelligent reservoir prediction model with geological and physical constraints. Results demonstrate that the proposed technique significantly enhances prediction accuracy for thin sand layers by effectively extracting high-frequency seismic information and establishing robust nonlinear mapping relationships. Inversion errors of reservoir parameters were reduced by more than 25%, while a vertical resolution of 0.5 m was achieved. Predictions agreed with actual drilling data with an accuracy of 86%, representing an 18% improvement over traditional methods. In practical applications, the technique successfully supported new well placement, contributing to a 22% increase in initial oil production in the pilot area. Furthermore, this study establishes a standardized technical procedure: “Time–Depth Modeling-Phase-Controlled Interpolation-Intelligent Inversion”. This workflow provides an innovative solution for high-precision reservoir characterization in regions with limited well control and complex terrestrial depositional systems, offering both theoretical significance and practical value for advancing reservoir prediction technology. Full article

Background: Limb amputation is a life-altering event with substantial physical, psychological, and social consequences. Despite advances in healthcare, amputation remains a major global health concern, particularly in regions with high burdens of diabetes and vascular disease. This study aims to analyze demographic characteristics, etiologies, and trends in amputations over a ten-year period at a tertiary-care center. Methods: We retrospectively reviewed medical records of patients who underwent amputation at our tertiary-care hospital. Collected variables included patients’ demographics, etiology, level of amputation, type of admission, and surgical specialty involved. Descriptive statistics were used to summarize the data. Associations between categorical variables were analyzed using chi-square tests, with post hoc pairwise comparisons adjusted using the Bonferroni method where applicable. Continuous variables were compared using the Mann–Whitney U test. A p-value of <0.05 was considered statistically significant. All analyses were conducted using IBM SPSS version 26.0. Results: A total of 647 patients underwent amputation, with a mean age of 56 years and a male predominance (65%). Diabetic complications were the leading cause (67.7%), followed by trauma (11.7%) and vascular diseases (11.6%). Lower limb amputations were more prevalent, with toe amputations being the most frequent (39%). Emergency procedures accounted for 72% of cases, and vascular surgery was the most involved specialty, followed by orthopedic surgery. Conclusions: Our study highlights a substantial burden of amputations, predominantly involving the lower limb, as well as a significant association with diabetic complications. These findings emphasize the urgent need for integrated diabetic care, early interventions, and public health strategies to reduce the burden of amputations in Saudi Arabia. Full article

Background/Objectives: The integration of strength training in grassroots youth soccer remains limited, often due to persistent myths regarding its safety and utility. This study evaluated the effectiveness of a tailored, playful strength training program in young players and analyzed the influence of the Relative Age Effect (RAE) on physical development and training response. Methods: A 14-week quasi-experimental pretest–posttest design was conducted with 27 federated male soccer players aged 9–10 years (experimental: n = 15; control: n = 12). The intervention consisted of twice-weekly, game-based strength training sessions integrated into the regular team routine. Outcomes included validated anthropometric (BMI) and functional (handgrip strength, standing long jump, Illinois agility test) indicators. RAE was analyzed according to birth quartile. Non-parametric statistical analyses and effect size (r) calculations were used. Results: The experimental group achieved significantly greater pre–post gains in handgrip strength than controls (right and left). Agility and standing long jump improved within the experimental group, but between-group differences were not significant. BMI decreased within the experimental group, yet the net between-group difference in BMI change was not significant in the context of a higher baseline BMI (p = 0.047). Although the Relative Age Effect (RAE) influenced baseline BMI, no moderating effect was detected on performance variables or training-induced changes in this sample. Conclusions: In U10 soccer players, a playful, context-integrated strength program produced superior gains in handgrip strength compared with usual practice. Improvements in agility and standing long jump were observed within the intervention group, but did not exceed those of the controls. BMI changes were not different between the groups and must be interpreted with caution, given baseline imbalances. In this sample, RAE did not moderate training response. Full article

Urban forests are natural habitat areas within urban ecosystems that enhance physical, mental, and social well-being. By integrating natural and cultural values into the urban landscape, these areas offer individuals opportunities to interact with nature and engage in various recreational activities. Recreational activities increase physical activity levels, help reduce stress, strengthen mental health, and foster social interaction, thereby significantly protecting and improving public health. This study aims to evaluate the recreational performance of urban forests—an essential component of the urban ecosystem—through a multidimensional approach. In this context, ecological (topography, vegetation, water resources, soil structure, climate), physical (accessibility, infrastructure, area size), social (activity diversity, usage intensity, community events), and cultural (landscape values, urban identity, conservation status of cultural landscapes) factors were considered as key indicators. Bursa Atatürk Urban Forest was selected as the study area, and the methodology integrated SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis with weighted multi-criteria decision-making techniques. In addition, the qualitative data obtained were supported by statistical analysis methods to reveal the relationships among the criteria quantitatively. Through this holistic approach, the recreational performance of the urban forest was evaluated scientifically, leading to the conclusion that the area’s strengths should be preserved, its weaknesses improved, and its cultural landscape values managed sustainably. The study provides a valuable decision-support framework capable of guiding strategic planning for the future. Full article

The circadian rhythm controls the sleep/wake cycle and a wide variety of metabolic and physiological functions. Clock genes regulate it in response to both external and endogenous stimuli, and their expression may change because of aging, leading to an increased risk of health problems. Despite the well-described benefits of physical exercise as a circadian synchronizer, there is a lack of literature regarding the role of chronic exercise intensity in clock gene expression during aging. This article aims to analyze the differential expression of genes that regulate the biological clock under the effects of variable-intensity aerobic swimming training in aging mice, determining whether these exercise regimens interfere with the genomic regulation of the circadian rhythm. For this purpose, the mice were exposed to low- and high-intensity exercise and had their heart and gastrocnemius tissues molecularly analyzed by cDNA synthesis and qPCR to determine the expression levels of the selected genes: Clock, Arntl, Per1, Per2, Cry1, Cry2, and Nr1d1. The results showed that low-intensity exercise, performed at workloads below the anaerobic threshold, significantly changed their expression in the gastrocnemius muscle (p < 0.05), while high-intensity exercise had no statistically significant effects (p > 0.05), with the heart being immune to exercise influence except when it comes to the Per1 gene, for which expression was increased (p = 0.031) by low-intensity exercise. Additionally, both body weight and lactate thresholds had no change during the experiment (p > 0.05), while the maximum supported workload was maintained for high-intensity exercise (p > 0.05) and increased for low-intensity exercise (p < 0.01), with the control group experiencing a decay instead (p < 0.05). Thus, the present study highlights the importance of chronic exercise in modulating clock genes and opens exciting possibilities for circadian medicine, such as improvements in exercise capacity, heart condition, and lipid metabolism for subjects of low-intensity regimens. Full article

Background and Objectives: The study aims to evaluate the effects of regular physical activity on ocular structures by comparing eye anterior segment structures and retinal nerve fiber layer (RNFL) parameters between elite individual athletes and sedentary persons. Materials and Methods: This cross-sectional observational study included 75 participants (33 female and 42 male) aged 18–32 years. Participants consisted of 33 elite individual athletes (66 eyes) aged 18–32 years and 42 sedentary individuals (84 eyes) aged 18–28 years. The elite athlete group consisted of participants who had trained ≥ 3 times per week for the past 5 years and had competition experience in tennis (n = 11), badminton (n = 8), and short/middle distance running (n = 14). Sedentary participants had not engaged in regular physical activity for the last 2 years. Anterior segment structures were measured with ultrasound biomicroscopy (UBM), RNFL parameters were measured with spectral-domain optical coherence tomography (SD-OCT), and intraocular pressure (IOP) was measured with a non-contact pneumotonometer. Results: When the anterior segment parameters were compared, a significance was found in the group effect (p = 0.021, ${ƞ}_p^2$ = 0.036) in the TIA500 value, but the effects of side and gender were insignificant (p > 0.05). While the gender effect was found to be significant for the AOD500 (p = 0.030, ${ƞ}_p^2$ = 0.032) and ARA500 (p = 0.019, ${ƞ}_p^2$ = 0.038) variables, the group and side effects were statistically insignificant (p > 0.05). There was a significant difference in IOP values between sedentary individuals (15.82 ± 2.69) and athletes (14.61 ± 1.80) (p = 0.004, ${ƞ}_p^2$ = 0.057). There was a significant difference between the right (15.71 ± 2.70) and left (14.87 ± 2.02) sides (p = 0.027, ${ƞ}_p^2$ = 0.033). The effect of gender was not significant (p > 0.05). When the results were evaluated, a significant effect of the TEMPORAL side in RNFL parameters (p = 0.003, ${ƞ}_p^2$ = 0.058) was observed. Correlations were seen between the anterior segment and RNFL parameters in both groups (p < 0.05). Conclusions: Athletes exhibited lower IOP compared with sedentary individuals, with similar RNFL parameters but distinct correlation patterns with anterior segment structures. These findings suggest that ocular parameters should be evaluated in an integrated manner and that physical activity may support ocular health by contributing to IOP reduction and potentially slowing the progression of eye diseases. Full article

Background and Objectives: Many older adults face health challenges, such as physical and functional decline, which increase the risk of hospitalization and dependence. As the global population ages, it is necessary to consider the health of older adults to avoid additional health burdens while improving their quality of life. This study aimed to explore body mass index (BMI) as a factor associated with health in older adults in South Korea. Accordingly, this study investigated the associations between the BMI of older Korean adults and exercise frequency (days per week), fall experience, and the presence of chronic diseases. Materials and Methods: Data from 10,014 older adults who participated in the 2023 Korean National Survey on Older Adults conducted by the Ministry of Health and Welfare were analyzed. Analyses included statistical frequency, chi-square tests, and multivariate logistic regression. Results: Underweight older adults had a higher likelihood of falling. Among those who were underweight, the odds ratio (OR) for falls was 2.052 (95% confidence interval [CI]: 1.349–3.121; p = 0.001). Underweight individuals were also less likely to engage in regular exercise. In contrast, both normal-weight and overweight individuals were more likely to participate in frequent exercise. Among those who were underweight, the ORs for exercising for 3–4 and ≥5 days were 0.612 (95% CI: 0.388–0.966; p = 0.035) and 0.721 (95% CI: 0.527–0.987; p = 0.041), respectively. Among those who were normal weight, the ORs for exercising for 1–2, 3–4, and ≥5 days were 1.286 (95% CI: 1.020–1.621; p = 0.033), 1.226 (95% CI: 1.055–1.424; p = 0.008), and 1.307 (95% CI: 1.167–1.464; p < 0.001), respectively. Among overweight individuals, the ORs for exercising for 1–2, 3–4, and ≥5 days were 1.275 (95% CI: 1.008–1.613; p = 0.043), 1.297 (95% CI: 1.114–1.509; p = 0.001), and 1.172 (95% CI: 1.042–1.318; p = 0.008), respectively. Older adults with obesity had a higher likelihood of having chronic diseases. Among those who were underweight, the ORs for one, two, three, and four diseases were 0.420 (95% CI: 0.268–0.658; p < 0.001), 0.335 (95% CI: 0.220–0.509; p < 0.001), 0.266 (95% CI: 0.167–0.422; p < 0.001), and 0.392 (95% CI: 0.254–0.606; p < 0.001), respectively. Among those with normal weight, the ORs for two, three, and four diseases were 0.686 (95% CI: 0.579–0.813; p < 0.001), 0.606 (95% CI: 0.505–0.727; p < 0.001), and 0.609 (95% CI: 0.505–0.735; p < 0.001), respectively, compared to those with obesity. Among those who were overweight, the ORs for two, three, and four diseases were 0.800 (95% CI: 0.671–0.953; p = 0.013), 0.781 (95% CI: 0.649–0.941; p = 0.009), and 0.686 (95% CI: 0.564–0.835; p < 0.001), respectively, compared to those with obesity. Conclusions: Weight is a key factor in promoting healthy aging in older adults. It is necessary to reduce the risk of falls in underweight individuals and prevent chronic diseases in those who are obese. Regular physical activity supports interventions that address these risks. Older adults should be supported and engage in consistent exercise tailored to their physical abilities and individual characteristics to maintain or improve their health and well-being later in life. Full article

Background: Football has a high injury risk due to speed and contact, and injury patterns may vary by playing position. Positional roles affect physical and physiological demands and may influence injury characteristics. Although this has been examined in professionals, data from amateur players are scarce. This study examined the incidence, type, and severity of injuries among amateur footballers in Greece with respect to playing position. Methods: A retrospective epidemiological study analyzed musculoskeletal injuries in 222 amateur male football players during the 2022–2023 season. Data were collected via a CHERRIES-compliant online survey (SurveyMonkey^®) from May to July 2023. Eligible participants were active male athletes aged ≥18 years competing in amateur Greek leagues. Injuries were defined according to the FIFA–UEFA consensus and expressed as incidence rates per 1000 h of exposure. Statistical analyses used SPSS v25 with significance at p < 0.05. Results: Among players (mean age: 25.3 ± 5.7 years), injury prevalence ranged from 65.1% (DFs) to 79.3% (GKs) with no significant association between playing position and injury risk (p = 0.379). Injury incidence ranged from 4.5 to 5.7 per 1000 h, highest among MFs. Incidence rates ranged between 1.33 and 2.74 injuries/1000 h in matches versus 1.33 to 2.09/1000 h in training, with DFs, FWs, and MFs more prone to match injuries, whereas GKs had slightly higher training rates; however, the number of injuries did not significantly differ between games and training across positions (χ² = 5.21, p = 0.517). Muscle strains and lower-limb injuries predominated. Injury severity differed significantly by position (p = 0.001), but injury type and mechanism did not. Conclusions: GKs and MFs showed the highest prevalence and incidence, but position was not linked to overall risk. Severity differences highlight the need for position-specific prevention strategies. Full article

Political polarization in Western democracies has accelerated in the last decade, with negative social consequences. Research across disciplines on antecedents, manifestations and societal impacts is hindered by social systems’ complexity: their constant flux impedes tracing causes of observed trends and prediction of consequences, hampering their mitigation. Social physics models exploit a characteristic of complex systems: what seems chaotic at one observation level may exhibit patterns at a higher level. Therefore, dynamic modeling of complex systems allows anticipation of possible events. We use this approach to anticipate 2024 US election results. We consider the highly polarized Democrats and Republicans, and Independents fluctuating between them. We generate average group-stance scenarios in time and explore how polarization and depolarization might have affected 2024 voting outcomes. We find that reducing polarization might advantage the larger voting group. We also explore ways to reduce polarization, and their potential effects on election results. The results inform regarding the perils of polarization trends, and on possibilities of changing course. Full article

Background/Objectives: Neuropathic pain, resulting from damage or pathology affecting the somatosensory nervous system, is a prevalent form of chronic pain that significantly impacts quality of life. Combined therapies are often utilised to manage this condition. Three-dimensional printing (3DP) offers a promising approach for personalising medication doses and dosage forms to meet individual patient needs. Methods: In this study, a formulation suitable for 3D printing was developed using magnesium citrate, uridine monophosphate, vitamins B₃ (niacin), B₆ (pyridoxine), B₁₂ (cobalamin), B₉ (folic acid), and spermidine to create a novel gel-based oral tablet for the targeted treatment of neurological pain. The antioxidant potential of the active pharmaceutical ingredients (APIs) was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) methods. The physical properties of the tablets were evaluated using a texture analyser, while the in vitro release profiles were determined by high-performance liquid chromatography (HPLC). Results: Results demonstrated that pectin–gelatin tablets hardened over time, with higher citric acid concentrations further enhancing this effect. Formulation AVII exhibited good hardness and low stickiness. Formulation AV, however, showed poor performance across all physical parameters and lacked sufficient structural integrity for practical application. While uridine monophosphate, B₁₂, and B₉ showed no significant differences in the release profiles of the tablets, spermidine, B₆, and B₃ displayed statistically significant variations. Specifically, AVII outperformed AV in terms of spermidine and B₆ release, and AV showed a higher release of B₃ compared to AV. Conclusions: The AVII tablet demonstrates potential for use in combined therapy targeting neurological pain disorders. Full article