Search Results (184)

Feline chronic kidney disease (fCKD) is highly prevalent in geriatric cats, affecting up to 80%, and is a leading cause of morbidity in cats with a challenging diagnosis. This study aimed to characterize the clinical profiles, comorbidities, and quality of life of cats with fCKD in real-world clinical settings in Greece. Real-world data from 208 client-owned cats with fCKD were analyzed, including demographics, clinical findings, body and muscle condition scores, and practitioner-assigned stage according to International Renal Interest Society (IRIS) guidelines. Additionally, owners completed the VetMetrica™ Health-Related Quality of Life (HRQL) questionnaire. Associations between comorbidities, IRIS stage, and HRQL domains were assessed using appropriate statistical analysis. At least one comorbidity was present in 66.8% of cats, with oral/dental disease (29.81%) and anemia (15.38%) being the most common. HRQL scores declined significantly with advancing IRIS stage (p < 0.001). Notably, anemia showed the strongest association with reduced HRQL across all domains, including an 18.79-point reduction in Emotional Wellbeing (p < 0.001). Oral/dental disease was also significantly associated with poorer Comfort (OR 5.16) and Emotional Wellbeing (OR 7.10). Overall, comorbidities independently contributed to impaired quality of life in cats with fCKD. These findings highlight that early detection of fCKD and targeted management of comorbidities alongside renal care may substantially improve patient welfare. Full article

Plants living in wetland environments (hydrophytes) have developed metabolic adaptations to cope with hypoxia. However, the specific metabolic signatures underlying this adaptation in naturally occurring hydrophytes, compared to their mesophytic relatives, remain insufficiently explored. GC-MS was used to carry out a comparative metabolic profiling of leaves from two pairs of closely related species (the hydrophytes Iris pseudacorus and Comarum palustre versus the mesophytes I. sibirica and Argentina anserina). In total, approximately 260 compounds were detected, of which roughly 100 were annotated. Using Principal Component Analysis, we revealed that the primary source of metabolic variation was phylogenetic (genus/tribe affiliation), while a secondary gradient correlated with ecological adaptation to submergence. A common adaptive metabolic signature of hydrophytes was identified, including the accumulation of dicarboxylic acids from Krebs cycle (succinate, fumarate) and glycolytic metabolites (pyruvate), suggesting a restructuring of energy metabolism under oxygen deficiency. Furthermore, hydrophytes, particularly I. pseudacorus, accumulated higher levels of soluble sugars (sucrose, fructose, glucose) and amino acids, thereby supporting energy supply and alternative NAD(P)H reoxidation pathways. Species-specific differences in the accumulation of antioxidants (e.g., flavonoids, ascorbate) were also observed, indicating diverse strategies for managing oxidative stress. Our findings contribute to identifying a “metabolic fingerprint” associated with waterlogging tolerance. Full article

Differentiated thyroid carcinoma (DTC) is the most common malignant endocrine tumor, with a generally favorable prognosis. Imaging, including iodine radioactive isotope scintigraphy (IRIS), is crucial for diagnosis and follow-up. While ¹³¹I has long been used for both therapeutic and diagnostic purposes, ¹²³I is reserved for diagnostic imaging due to its shorter half-life and γ emissions. This review highlights the utility of ¹²³I scintigraphy, especially in pre-treatment assessment and dosimetry for DTC. It is particularly valuable before radioiodine (RAI) ablation, providing accurate imaging in patients with iodine-refractory (IR) or biochemically incomplete response (BIR) DTC. When compared to post-therapeutic ¹³¹I scans, ¹²³I scintigraphy appears to have a lower sensitivity for detecting metastatic lesions, particularly in lymph nodes and lungs. However, its diagnostic performance compared to low-dose diagnostic ¹³¹I is more variable, with some studies suggesting superiority due to the absence of stunning. Further research is needed to standardize its use and optimize its role in guiding DTC management. Full article

Decisions made by pilots and drivers suffering from depression can endanger the lives of hundreds of people, as demonstrated by the tragedies of Germanwings flight 9525 and Air India flight 171. Since the detection of depression is currently based largely on subjective self-reporting, there is an urgent need for fast, objective, and reliable detection methods. In our study, we present an artificial intelligence-based system that combines iris-based identification with the analysis of pupillometric and eye movement biomarkers, enabling the real-time detection of physiological signs of depression before driving or flying. The two-module model was evaluated based on data from 242 participants: the iris identification module operated with an Equal Error Rate of less than 0.5%, while the depression-detecting CNN-LSTM network achieved 89% accuracy and an AUC value of 0.94. Compared to the neutral state, depressed individuals responded to negative news with significantly greater pupil dilation (+27.9% vs. +18.4%), while showing a reduced or minimal response to positive stimuli (−1.3% vs. +6.2%). This was complemented by slower saccadic movement and longer fixation time, which is consistent with the cognitive distortions characteristic of depression. Our results indicate that pupillometric deviations relative to individual baselines can be reliably detected and used with high accuracy for depression screening. The presented system offers a preventive safety solution that could reduce the number of accidents caused by human error related to depression in road and air traffic in the future. Full article

Following World Health Organization (WHO) validation of lymphatic filariasis (LF) elimination as a public health problem, countries are required to implement post-validation surveillance (PVS) to detect potential resurgence and ensure sustained elimination. WHO’s guidelines released in 2025 recommend implementation of at least two of four PVS strategies—targeted surveys, integration into standardised surveys, health facility-based screening, and molecular xenomonitoring (MX) of mosquitoes. This review synthesised global evidence on PVS activities from 2007 to 2025 in the 23 countries and territories validated as having eliminated LF. Studies were identified through PubMed, Scopus, Embase, Web of Science, and the WHO Institutional Repository for Information Sharing (IRIS). Data on publication information, surveillance strategies, priority populations, and operational challenges and enablers were extracted. Narrative synthesis using deductive content analysis was applied. Thirty documents from 17 countries were included. Targeted surveillance and integration of PVS with other health programmes were the most common approaches noted (reported in ten and nine countries, respectively), followed by MX (seven countries) and health facility-based screening (four countries). Surveillance often focused on migrants and previous hotspots, with operational challenges linked to limited funding, workforce, and supply chains. Documents indicated that Sri Lanka, Thailand, China, and South Korea developed sustained PVS through national policies and domestic funding. Findings highlight the need for clear, contextualised guidance to operationalise sustainable PVS in different settings. Full article

Bicarbonate deficiency is a common complication of acute kidney injury (AKI) and chronic kidney disease (CKD), resulting from impaired renal bicarbonate handling. It promotes bone demineralization and calcium–phosphate (CaxP) imbalance. In dogs, elevated CaxP has been linked to increased frequency and severity of bicarbonate deficiency. This 10-year study evaluated the prevalence and degree of bicarbonate deficiency in 618 cats diagnosed with AKI, acute-on-chronic kidney disease (ACKD), and CKD, and its association with azotemia and mineral imbalance. A retrospective analysis was conducted on serum biochemical profiles, including creatinine, urea, ionized and total calcium, phosphate, CaxP, and bicarbonate. Cats with incomplete datasets or receiving sodium bicarbonate therapy were excluded. According to IRIS guidelines, bicarbonate deficiency was defined as <16 mmol/L and categorized as moderate (12–16 mmol/L) or severe (<12 mmol/L). Deficiency was found in 45% of cats, of which 63% were moderate and 37% severe. Prevalence was higher in AKI (58%) and ACKD (60%) compared to CKD (38%) (p = 0.002). Negative correlations between bicarbonate and creatinine, phosphate, and CaxP were detected in AKI and CKD, while in ACKD, only creatinine and phosphate correlated. Deficiency increased with disease severity in AKI (p = 0.0145) and CKD (p < 0.0001). Cats with CaxP > 70 mg²/dL² had higher deficiency rates (p < 0.0001). However, 21% with elevated CaxP had normal bicarbonate, suggesting mineral imbalance may occur independently of acidosis. Full article

This study investigates the potential of Floating Car Data (FCD) collected from Volkswagen Group vehicles since 2022 for monitoring pavement conditions along two Italian road stretches. While such data are primarily gathered to analyze vehicle dynamics and mechanical behaviour, here, they are repurposed to support road network assessment through the estimation of the International Roughness Index (IRI). Daily aggregated datasets provided by NIRA Dynamics were analyzed to evaluate their reliability in detecting spatial and temporal variations in surface conditions. The results show that FCD can effectively identify critical sections requiring maintenance, track IRI variations over time, and assess the performance of surface rehabilitation, with high consistency on single-lane roads. On multi-lane roads, limitations emerged due to data aggregation across lanes, leading to reduced accuracy. Nevertheless, FCD proved to be a cost-efficient and continuously available source of information, particularly valuable for identifying temporal changes and supporting the evaluation of maintenance interventions. Further calibration is needed to enhance alignment with high-performance measurement systems, considering data density at the section level. Overall, the findings highlight the suitability of FCD as a scalable solution for real-time monitoring and long-term maintenance planning, contributing to more sustainable management of road infrastructure. Full article

Forensic DNA phenotyping (FDP) is an important innovation approach in forensics sciences, especially when traditional DNA profiling results are limited, mostly due to the absence of reference samples. FDP is based on the detection of genetic variants in specific genes whose function is related to pigmentation mechanisms and uses the genotypes found in the sample to determine the externally visible traits (EVT) such as the iris, hair, and skin tone or color of the individual; this prediction would help and expedite human identification processes and solve criminal cases. Several technologies have been developed to facilitate EVT prediction; however, most of them have been validated only in European populations. Implementing techniques for FDP in Latin American countries is essential given the problems of disappearance and human identification that have persisted for years. Nonetheless, scientists have a great challenge due to the admixed genetic structure of the population. This review explores the current application of FDP, emphasizing its significance, practical uses, and limitations within Latin American populations. Full article

Eye-tracking technology has gained traction in the field of medical rehabilitation due to its non-invasive and intuitive nature. However, current eye-tracking methods based on object detection technology suffer from insufficient accuracy in detecting the eye socket and iris, as well as inaccuracies in determining eye movement direction. To address this, this study improved the YOLOv11 model using the EFFM and ORC modules, resulting in a 1.7% and 9.9% increase in recognition accuracy for the eye socket and iris, respectively, and a 5.5% and 44% increase in recall rate, respectively. A method combining frame voting mechanisms with eye movement area discrimination was proposed for eye movement direction discrimination, achieving average accuracy rates of 95.3%, 92.8%, and 94.8% for iris fixation, left, and right directions, respectively. The discrimination results of multiple eye movement images were mapped to a binary value, and eye movement encoding was used to obtain control commands that align with the robotic arm. The average matching degree of eye movement encoding ranged from 93.4% to 96.8%. An experimental platform was established, and the average completion rates for three object-grabbing tasks controlled by eye movements were 98%, 78%, and 96%, respectively. Full article

Uveal melanoma is the most common primary intraocular malignancy in adults, most frequently arising from the choroid, followed by the ciliary body and iris. Its diagnosis and management require precise characterization of tumor morphology, localization, and associated complications to optimize visual and systemic outcomes. Recent advances in optical coherence tomography (OCT), anterior segment OCT (AS-OCT), and OCT angiography (OCTA) have expanded the ophthalmologist’s ability to non-invasively visualize structural and vascular changes associated with this disease. In fact, enhanced depth imaging (EDI) and swept-source (SS) OCT can provide detailed views of deep ocular structures, enabling early detection of hallmark features such as subretinal fluid, retinal pigment epithelium disruption, and dome- or mushroom-shaped choroidal elevations; AS-OCT improves evaluation of lesions of the anterior segment, revealing iris architecture distortion and angle involvement; OCTA facilitates the visualization of abnormal tumor vasculature and detection of radiation-induced microvascular changes, including capillary dropout and foveal avascular zone enlargement. Moreover, these imaging modalities have demonstrated utility in differentiating uveal melanoma from pseudomelanomas, such as choroidal nevi, hemangiomas, and metastases. The present review aims at objectively assessing the use of OCT and OCTA in the diagnosis, treatment, and follow up of ocular melanoma, emphasizing their crucial role in identifying pathologic biomarkers of this potentially fatal ocular disease. Full article

The eye, in a dominant sense, can suffer disorders, such as myopia or nearsightedness, because of VDU radiation exposure. One symptom which is often caused by excessive use of VDU is eye strain. It is usually marked by an increase in the sensitivity of the eyes to light. It is known by comparing the diameter of the normal eye’s pupil and the strained eye’s pupil. People can prevent this disorder by detecting changes in the pupil’s diameter compared to the iris. Changes in the iris and pupil can be detected by using the Hough transformation to detect their shape and train perceptron neural network algorithms to recognize the patterns. As a VDI tool, an eye strain detection application can determine the condition of the user’s eyes. The level of accuracy of the method used to detect the iris and pupil using the Hough transformation is 100% for brown irises, 50% for blue irises, 33.3% for green irises, and it has a 100% accuracy in detecting an iris that is similar to the pupil and a 28.6% accuracy in detecting a pupil that is a similar color to the iris. There is also a difference in the level of accuracy of these case studies when different detection tools are used. The smartphone camera showed a 100% accuracy in detecting the iris and 28.6% accuracy in detecting the pupil. The SLR camera had a 100% accuracy in detecting the irises and 71.4% accuracy in detecting pupils, while the digital camera had 14.28% accuracy in detecting irises and a 0% accuracy in detecting a pupil. The accuracy of the perceptron algorithm in recognizing a pattern of eye strain is 70% with 20 sets of test data. Full article

Iris recognition is currently considered the most promising biometric method and has been applied in many fields. Current commercial and research systems typically use software solutions running on a dedicated computer, whose power consumption, size and price are considerably high. This paper presents a hardware-based embedded solution for real-time iris segmentation. From an algorithmic point of view, the system consists of two steps. The first employs a YOLOX trained to detect two classes: eyes and iris/pupil. Both classes intersect in the last of the classes and this is used to emphasise the detection of the iris/pupil class. The second stage uses a lightweight U-Net network to segment the iris, which is applied only on the locations provided by the first stage. Designed to work in an Iris At A Distance (IAAD) scenario, the system includes quality parameters to discard low-contrast or low-sharpness detections. The whole system has been integrated on one MultiProcessor System-on-Chip (MPSoC) using AMD’s Deep learning Processing Unit (DPU). This approach is capable of processing the more than 45 frames per second provided by a 16 Mpx CMOS digital image sensor. Experiments to determine the accuracy of the proposed system in terms of iris segmentation are performed on several publicly available databases with satisfactory results. Full article

In order to investigate the influence of different tire textures, pavement types, and vehicle parameters on the tire/road noise level and its spectrum characteristics, 19 kinds of asphalt pavement main structures of RIOHTrack full-scale test track were tested by the close-proximity trailer (CPXT) tire/road noise detection method. Considering investigated parameters such as tire texture, vehicle speed, and trailer axle weight, and relying on multi-functional road condition rapid detection vehicle and laboratory tests to collect a variety of road surface information and material parameters, a multiple-linear-regression model of tire/road surface noise level of RIOHTrack (Research Institute of Highway Full-scale Test Track) asphalt pavement was constructed. Finally, the causes of noise level differences among different influencing factors were further analyzed through spectrum characteristics. The results show that vehicle speed is the most important factor affecting tire/road noise. The noise level of different tires varies due to different textures, but the noise level among different trailer axle weights is roughly the same. Vehicle speed (v), FWD center deflection (D₀), surface asphalt mixture air voids (VV), sensor-measured texture depth (SMTD) and international roughness index (IRI) were selected to establish the noise prediction models of different tire textures. Noise spectrum analysis shows that the spectrum of different vehicle speeds is significantly wide in the full frequency range, and the spectrum variation of differently textured tires is mainly concentrated in a certain range of the peak frequency. The noise spectrum curve of porous asphalt concrete (PAC13) is significantly lower than that of other asphalt mixtures in the full frequency range above 800Hz, indicating a greater noise reduction effect. Full article

This study presents a smartphone-based dual-index framework for evaluating bicycle pavement conditions, aimed at supporting sustainable urban mobility and cyclist safety. Conventional assessment methods, such as the International Roughness Index (IRI), often overlook short-range discontinuities and are impractical for micromobility-scale infrastructure monitoring. To address these limitations, two perception-aligned indices were developed: the Bicycle Road Roughness Index (BRI), reflecting sustained surface discomfort, and the Faulting Impact Index (FII), quantifying acute vertical shocks. Both indices were calibrated through structured panel surveys involving 40 experienced cyclists and validated using high-frequency tri-axial acceleration data collected in both experimental and field settings. Regression analysis confirmed strong alignment between sensor signals and user perception (R² = 0.74 for BRI; R² = 0.76 for FII). A five-grade classification system was proposed, with critical FII thresholds at 87.3 m/s² for “risky” and 119.4 m/s² for “not rideable” conditions. Field validation across four diverse sites revealed over 380 hazard segments requiring attention, demonstrating the framework’s ability to identify localized risks that may be masked by traditional metrics. By leveraging off-the-shelf smartphones and open-source sensing tools, the proposed approach enables scalable, low-cost, and cyclist-centered diagnostics. The dual-index system not only enhances rideability evaluation but also supports targeted maintenance planning, real-time hazard detection, and broader efforts toward data-driven, sustainable micromobility management. Full article

Background: Patients with primary angle-closure disease (PACD), those with no history of acute angle-closure glaucoma or laser iridotomy, rarely present with prominent corneal endothelial cell density (CECD) loss. To identify factors associated with decreased CECD in PACD, anterior segment parameters were compared in patients with PACD and normal CECD and patients with PACD and decreased CECD, using anterior segment optical coherence tomography (AS-OCT). Patients and Methods: Ten patients with PACD and CECD of less than 1500/mm² without a history of cataract surgery, acute angle-closure glaucoma, or prior laser glaucoma procedures were identified at the Kyorin Eye Center from January 2018 to July 2023. Patients with an obvious corneal guttata or apparent corneal edema were also excluded. Seventeen patients with PACD and normal CECD (normal CECD group) were used as the control. Simultaneous biometry of all anterior segment structures, including the cornea, anterior chamber, and iris, were assessed using a swept-source AS-OCT system. Results: Corneal curvature radius was significantly larger in the decreased CECD group compared with the corneal refractive power in the normal CECD group (p = 0.022, Mann–Whitney test). However, no significant differences were detected in other anterior segment morphology parameters. Multiple regression analysis with CECD as the dependent variable revealed that a large corneal curvature radius was a significant explanatory variable associated with corneal endothelial loss. Conclusions: Flattened corneal curvature may be a risk factor for corneal endothelial loss in patients with PACD. Full article