Search Results (180)

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

The application of non-thermal (cold) plasmas is considered an environmentally friendly method that could affect plant metabolism and cellular development or can be used for the commercial production of natural products that cannot be chemically synthesized. In the present study, the non-embryogenic callus of iris (Iris reichenbachii Heuff.) was treated with a Radio Frequency (RF) plasma needle device using He as a working gas. We investigated short-term (up to seven days) and long-term (up to one year) changes on morphological, physiological and biochemical levels. An increased production of O₂⁻ and H₂O₂ was observed in the callus tissue after plasma treatment. The enzymes SOD and CAT represented the frontline in the antioxidant defense against reactive oxygen species (ROS) produced during the first hour of treatment, while POX was the leading antioxidant enzyme seven days after plasma treatment. Significant long-term morphological changes were observed in the calli due to the increased mitotic activity of the plant cells. In addition, three flavonoids (naringenin, apigenin and acacetin) and two isoflavonoids (irisolidone and irilone) were detected only in the plasma-treated tissue even one year after plasma treatment. The present study emphasizes the application of the plasma technique to promote meristematic activity and stimulate the production of specialized metabolites in iris calli. Full article

Motivation: Benign paroxysmal positional vertigo (BPPV) is characterized by torsional nystagmus induced by changes in head position, where accurate quantitative assessment of subtle torsional eye movements is essential for precise diagnosis. Conventional videonystagmography (VNG) techniques face challenges in accurately capturing the rotational components of pupil movements, and existing automated methods typically exhibit limited performance in identifying torsional nystagmus. Methodology: The objective of this study was to develop an automated system capable of accurately and quantitatively detecting torsional nystagmus. We introduce the Torsion Transformer model, designed to directly estimate torsion angles from iris images. This model employs a self-supervised learning framework comprising two main components: a Decoder module, which learns rotational transformations from image data, and a Finder module, which subsequently estimates the torsion angle. The resulting torsion angle data, represented as time-series, are then analyzed using a 1-dimensional convolutional neural network (1D-CNN) classifier to detect the presence of nystagmus. The performance of the proposed method was evaluated using video recordings from 127 patients diagnosed with BPPV. Findings: Our Torsion Transformer model demonstrated robust performance, achieving a sensitivity of 89.99%, specificity of 86.36%, an F1-score of 88.82%, and an area under the receiver operating characteristic curve (AUROC) of 87.93%. These results indicate that the proposed model effectively quantifies torsional nystagmus, with performance levels comparable to established methods for detecting horizontal and vertical nystagmus. Thus, the Torsion Transformer shows considerable promise as a clinical decision support tool in the diagnosis of BPPV. Key Findings: Technical performance improvement in torsional nystagmus detection; System to support clinical decision-making for healthcare professionals. Full article

Nitrogen is a crucial element that impacts rice yield and its constituent factors. The effects of reduced nitrogen levels on yield constitute is a complex quantitative trait that is controlled by multiple genes, and its genetic basis requires further exploration. In this study, 562 MAGIC line population and 284 germplasm varieties were used for genome-wide association analysis (GWAS) and haplotype analysis, aiming to detect quantitative trait loci (QTL) and candidate genes associated with tolerance to low nitrogen levels. The ratio of effective panicle number per plant (REPN), total number of grains per panicle (RTGN), seed setting rate (RSSR), thousand grain weight (RTGW), biomass (RBM), harvest index (RHI), and grain yield per plant (RGY) of low to normal nitrogen conditions were measured in this study. The RBM and RHI were directly closely related to RGY, while the RSSR indirectly and positively affected RGY through RHI, and the REPN and RTGN mainly indirectly and positively affected RGY through RBM. LOC_Os06g06440 was the most likely gene affecting low-nitrogen-tolerance-related traits in rice within the region, ranging from 2.898 Mb to 3.046 Mb (148 kb) on chromosome 6, and the haplotype AA, with a significantly larger mean RGY of 0.95 and 1.53 in the MAGIC and germplasm varieties, respectively, was the advanced allele of LOC_Os06g06440. Nine xian (indica) varieties (IRIS_313-11624, IRIS_313-10932, CX382, B067, B249, IRIS_313-8215, IRIS_313-10544, B052, and B233) carrying the superior haplotype (AA) of LOC_Os06g06440 and having a higher RGY were selected for the molecular marker-assisted selection of low nitrogen tolerance in rice. These results will enhance our knowledge of the genetic basis of tolerance to low levels of nitrogen and provide valuable information for improving tolerance to low levels of nitrogen in rice-breeding programs. Full article

Subclinical chronic kidney disease (sCKD) predisposes one to acute kidney injury (AKI) and chronic kidney disease (CKD). Reduced kidney functional reserve (KFR) detects sCKD in preclinical studies and predicts AKI after cardiac surgery. We evaluated renal protection in a rat model of kidney injury where ischaemia–reperfusion injury (IRI) was induced after sCKD. Dual treatment boosting nicotinamide adenine dinucleotide (NAD) by nicotinamide riboside (NR) combined with the mitochondria-targeted antioxidant SkQR1 protected the KFR and reduced structural kidney damage, including markers of vascular integrity and the relative blood volume (rBV). The dual treatment upregulated Sirt1 and Nrf2, increased the nuclear localisation of the mitochondrial biogenesis regulator PGC-1α and the mitochondrial protein marker COX4, and upregulated the antioxidant gene NOQ1. These observations suggest mitochondrial protection and modulation of the cellular redox state provided long-term structural and functional protection against kidney injury superimposed on background sCKD. Full article