Search Results (226)

Objectives: To assess the role of a real-time therapeutic drug monitoring (TDM)-guided expert clinical pharmacological advice (ECPA) program of isavuconazole in preventing under- or overexposure with the intent of improving efficacy and safety outcomes in the critically ill patients. Methods: This retrospective study included critical patients receiving intravenous isavuconazole for prophylaxis or treatment of invasive fungal infections (IFI) and undergoing at least one TDM-guided ECPA in the period 1 March 2021–31 March 2025. Desired isavuconazole exposure was defined as trough concentrations (C_min) of 1.0–5.1 mg/L. Efficacy outcome was assessed by means of bronchoalveolar (BAL) galactomannan (GM) index, breakthrough IFI, and 30-day mortality rate, whereas safety was assessed by means of hepatic test disturbances (HTD). Univariate analysis was carried out for assessing potential variables associated with isavuconazole under- or overexposure and for comparing features of solid organ transplant (SOT) recipients vs. non-SOT patients. Proportions of isavuconazole C_min underexposure, desired exposure, and overexposure were assessed at different timepoints from starting therapy. Trends over time of HTD in relation to isavuconazole exposure were assessed separately in patients having HTD or not at baseline. Results: Overall, 32 critical patients were included. A total of 166 TDM-guided ECPAs were provided. Median (IQR) average isavuconazole C_min was 3.5 mg/L (2.1–4.6 mg/L). Proportions of ECPAs with isavuconazole C_min under- and overexposure were 4.2% (7/166) and 16.3% (27/166), respectively. Patients experiencing underexposure had higher body mass index (30.1 vs. 25.5 kg/m²; p < 0.001). Trends of isavuconazole C_min under- and overexposure changed over time, significantly decreasing the former (10.5% <7 days vs. 4.3% 7–28 days vs. 0.0% >28 days; p < 0.001) and increasing the latter (5.3% <7 days vs. 12.8% 7–28 days vs. 29.3% >28 days; p < 0.001). HTD occurred in 15/32 patients, most of whom (10/15) were affected just at baseline. Patients with transient or persistent overexposure trended toward a higher risk of HTD compared to those without (33.3% vs. 8.3%; p = 0.11). Conclusions: A real-time TDM-guided approach could be a valuable tool for optimizing isavuconazole exposure, especially whenever dealing with obese patients or with prolonged treatment. Full article

In the domain of intelligent inspection, the precise recognition of pointer meter readings is of paramount importance for monitoring equipment conditions. To address the challenges of insufficient robustness and diminished detection accuracy encountered in practical applications of existing methods for recognizing pointer meter readings based on object detection, we propose a novel approach that integrates YOLOv11-OBB rotating object detection with adaptive template matching techniques. Firstly, the YOLOv11 object detection algorithm is employed, incorporating a rotational bounding box (OBB) detection mechanism; This effectively enhances the feature extraction capabilities related to pointer rotation direction and dial center, thereby boosting detection robustness. Subsequently, an enhanced angle resolution algorithm is leveraged to develop a mapping model that establishes a relationship between pointer the deflection angle and the instrument range, facilitating precise reading calculation. Experimental findings demonstrate that the proposed method achieves a mean Average Precision (mAP) of 99.1% in a self-compiled pointer instrument dataset. The average relative error of readings is 0.41568%, with a maximum relative error of less than 1.1468%. Furthermore, the method exhibits robustness and reliability when handling low-quality meter images characterized by blur, darkness, overexposure, and tilt. The proposed approach provides a highly adaptable and reliable solution for pointer meter reading recognition in the intelligent industrial field, with significant practical value. Full article

In deformation measurements, processing overexposed images poses challenges due to the welding process or metal reflection. To track the deformation surface, an Adaptive Brightness Global Digital Image Correlation method is proposed. First, the effective range is determined based on the extent of image overexposure. Second, an improved Dark Channel Prior method is employed to adjust the brightness of overexposed images. Third, by calculating the parameter results of Finite Element Partitioning, Adaptive Brightness Global Digital Image Correlation can be utilized to conduct deformation measurements. The proposed method can adjust both the image brightness and Finite Element Partitioning for Global Digital Image Correlation. The experimental results demonstrate that the improved dark channel method modifies the image brightness without altering its brightness distribution. The modified image can significantly increase the Mean Intensity Gradient within different partitions. This method overcomes the difficulty in measuring the weld deformation during the welding process and can achieve dynamic deformation measurement using overexposed images. Finally, the evolution processes of unstable deformation and angular deformation in the whole welding field are obtained, which can assist in optimizing the welding process. Full article

X-ray ptychography is an ultrahigh resolution imaging technique widely used in synchrotron radiation facilities. Its imaging performance relies on the quality of the acquired signals. However, the X-ray detectors used often suffer from signal loss due to sensor gaps, beamstops, defective pixels, overexposure, or other factors, resulting in degraded image quality. To suppress and compensate for the effects of signal loss, we proposed the known probe approach to partially recover the lost signals and introduced the high probe divergence strategy by investigating the effects of probe divergence on reconstruction quality under signal loss conditions. Both simulation and experiment results show that high probe divergence can effectively suppress the impact of signal loss on reconstruction quality while using a known probe as the initial probe for reconstruction can largely recover missing signals in Fourier space, resulting in a much better image than using a guessed initial probe. These strategies allow for high-quality imaging in the presence of signal loss without secondary data acquisition, significantly improving experimental efficiency and reducing radiation damage compared to previous strategies. Full article

Aquatic floating debris detection is a key technological foundation for ecological monitoring and integrated water environment management. It holds substantial scientific and practical value in applications such as pollution source tracing, floating debris control, and maritime navigation safety. However, this field faces ongoing challenges due to water surface polarization. Reflections of polarized light produce intense glare, resulting in localized overexposure, detail loss, and geometric distortion in captured images. These optical artifacts severely impair the performance of conventional detection algorithms, increasing both false positives and missed detections. To overcome these imaging challenges in complex aquatic environments, we propose a novel YOLOv8-based detection framework with integrated polarized light suppression mechanisms. The framework consists of four key components: a fisheye distortion correction module, a polarization feature processing layer, a customized residual network with Squeeze-and-Excitation (SE) attention, and a cascaded pipeline for super-resolution reconstruction and deblurring. Additionally, we developed the PSF-IMG dataset (Polarized Surface Floats), which includes common floating debris types such as plastic bottles, bags, and foam boards. Extensive experiments demonstrate the network’s robustness in suppressing polarization artifacts and enhancing feature stability under dynamic optical conditions. Full article

Platinum wires, known for their excellent electrical conductivity and durability, are widely used in high-precision industries, such as aerospace and automotive. These wires are typically coated with polyamide for protection; however, specific manufacturing processes require the coating to be selectively removed. Although traditional chemical stripping methods are effective, they are associated with high costs, safety concerns, and long processing times. As a result, laser ablation has emerged as a more efficient, precise, and cleaner alternative, especially at the microscale. In this study, ultraviolet nanosecond laser ablation was applied to remove polyamide coatings from ultra-thin platinum wires in a water-assisted environment. The presence of water enhances the process by promoting thermal management and minimizing debris. Key processing parameters, including the scanning speed, overlap percentage, and line distance, were evaluated. The optimal result was achieved at a scanning speed of 1200 mm/s, line distance of 1 µm, and single loop in water-ambient, where coating removal was complete, surface roughness remained low, and wire tensile strength was preserved. This performance is attributed to the effective energy distribution across the wire surface and reduced thermal damage due to the heat dissipation role of water, along with controlled overlap that ensured full coverage without overexposure. A thin, well-maintained water layer confined above the apex of the wire played a crucial role in regulating the thermal flow during ablation. This setup helped shield the delicate platinum substrate from overheating, thereby maintaining its mechanical integrity and preventing substrate damage throughout the process. This study primarily focused on analyzing the main effects and two-factor interactions of these parameters using Analysis of Variance (ANOVA). Interactions such as Speed × Overlap and Speed × Line Distance were statistically examined to identify the influence of combined factors on tensile strength and surface roughness. In the second phase of experimentation, the parameter space was further expanded by increasing the line distance and number of loops to reduce the overlap in the X-direction. This allowed for a more comprehensive process evaluation. Again, conditions around 1200 mm/s and 1500 mm/s with 2 µm line distance and two loops offered favorable outcomes, although 1200 mm/s was selected as the optimal speed due to better consistency. These findings contribute to the development of a robust, high-precision laser processing method for ultra-thin wire applications. The statistical insights gained through ANOVA offer a data-driven framework for optimizing future laser ablation processes. Full article

Low-quality power grid image data can greatly affect the effect of deep learning in the power industry. Therefore, adopting accurate image quality assessment techniques is essential for screening high-quality power grid images. Although current blind image quality assessment (BIQA) methods have made some progress, they usually use only one type of feature and ignore other factors that affect the quality of images, such as noise and brightness, which are highly relevant to low-quality power grid images with noise, underexposure, and overexposure. Therefore, we propose a multi-dimension distortion feature network (MDFN) based on CNN and Transformer, which considers high-frequency (edges and details) and low-frequency (semantic and structural) features of images, along with noise and brightness features, to achieve more accurate quality assessment. Specifically, the network employs a dual-branch feature extractor, where the CNN branch captures local distortion features and the Transformer branch integrates both local and global features. We argue that separating low-frequency and high-frequency components enables richer distortion features. Thus, we propose a frequency selection module (FSM) which extracts high-frequency and low-frequency features and updates these features to achieve global spatial information fusion. Additionally, previous methods only use the CLS token for predicting the quality score of the image. Considering the issues of severe noise and exposure in power grid images, we design an effective way to extract noise and brightness features and combine them with the CLS token for the prediction. The results of the experiments indicate that our method surpasses existing approaches across three public datasets and a power grid image dataset, which shows the superiority of our proposed method. Full article

Tea is one of the most widely consumed beverages globally and a significant dietary source of fluoride. This systematic review aimed to identify and evaluate the factors influencing fluoride concentration in tea infusions. A comprehensive literature search was conducted in March 2025 across PubMed, Scopus, and Web of Science databases, following PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and the PICO framework. Eligible studies investigated fluoride release in tea infusions, published in English from the year 2000 onward. Thirty articles met the inclusion criteria, and the risk of bias in the articles was assessed using the Joanna Briggs Institute (JBI) quality checklist. Fluoride concentration in tea infusions varied widely across studies, ranging from 0.008 to over 8 mg/L. Key factors influencing fluoride release included tea type (with black and green teas showing the highest values), leaf form (powdered and bagged teas released more fluoride than loose leaves), brewing time and temperature, water composition, and the presence of additives such as spices. A longer brewing time and higher temperature consistently increased fluoride extraction. Lower pH or water hardness also significantly affected fluoride availability. Regional origin of tea and production methods were additional sources of variation. Fluoride release in tea is influenced by a complex interplay of botanical, environmental, and preparation-related factors. These findings are clinically relevant, particularly for populations at risk of fluoride overexposure. Further standardized research is needed to inform safe consumption guidelines and public health recommendations. Full article

Mueller matrix polarimetry has great potential for tissue detection and clinical diagnosis due to its ability to provide rich microstructural information accurately. However, in practical in vivo tissue imaging based on backscattering Mueller matrix polarimetry, specular reflection is often inevitable, leading to overexposed regions and the following inaccurate polarization information acquisition of tissues. In this study, we probe the influence of specular reflection and overexposure on backscattering Mueller matrix polarimetry for tissue imaging and sensing. We investigate in detail the differentiation of polarization behaviors between the specular reflection and non-specular reflection tissue regions using a 3 × 3 backscattering Mueller matrix measurement. Then, we obtain the vertical projection profiles to further quantify the Mueller matrix elements of porcine liver tissue in different specular reflection regions. Finally, we calculate the polarization feature parameters derived from a 3 × 3 Mueller matrix and analyze their behavior in overexposed regions. Based on the quantitative analysis and comparisons, we obtain a group of polarization feature parameters with strong immunity to the specular reflection process. This study offers a strategy for selecting the polarization parameters during in vivo polarimetric imaging applications, provides valuable references for further eliminating the characterization errors induced by specular reflection, and may contribute to the advancement of quantitative tissue polarimetric imaging and sensing. Full article

Assessing the propensity of ingredients to induce skin sensitization through in vitro testing is crucial for worker and consumer safety. This is particularly important for novel and high-performance ingredients with complex structures, such as rheology-modifying polymers, which are extensively used in cosmetics, pharmaceuticals, and detergents. The Sens-Is assay has proven effective in distinguishing skin sensitizers from non-sensitizers for difficult-to-test ingredients when integrated into a multi-method in vitro approach. Therefore, the primary goal of this research was to explore whether the Sens-Is in vitro assay is suitable to evaluate rheology-modifying polymers. Fifteen structurally diverse rheology-modifying polymers, including natural polymers obtained by extraction, chemical synthesis, or biotechnology, spanning varying physical forms and concentrations, were evaluated. The results showed that most polymers were non-sensitizing, consistent with available in vivo data. Although polymer macromolecules generally exhibit limited skin sensitization potential due to their surface confinement, the Sens-Is assay permitted the detection of weak signals from secondary components or possible byproducts in specific cases. This work confirms Sens-Is as a useful tool in an overall approach to assessing the skin sensitization liability of polymers under development, but careful solvent selection is crucial to ensure accurate results and prevent potential overexposure due to polymer retention on the epidermal surface. Full article

The accurate identification of coal and rock at the mining face is often hindered by adverse underground imaging conditions, including poor lighting and strong reflectivity. To tackle these issues, this work introduces a recognition framework specifically designed for underground environments, leveraging joint migration and enhancement of multidimensional and full-scale visual representations. A Transformer-based architecture is employed to capture global dependencies within the image and perform reflectance component denoising. Additionally, a multi-scale luminance adjustment module is integrated to merge features across perceptual ranges, mitigating localized brightness anomalies such as overexposure. The model is structured around an encoder–decoder backbone, enhanced by a full-scale connectivity mechanism, a residual attention block with dilated convolution, Res2Block elements, and a composite loss function. These components collectively support precise pixel-level segmentation of coal–rock imagery. Experimental evaluations reveal that the proposed luminance module achieves a PSNR of 21.288 and an SSIM of 0.783, outperforming standard enhancement methods like RetinexNet and RRDNet. The segmentation framework achieves a MIoU of 97.99% and an MPA of 99.28%, surpassing U-Net by 2.21 and 1.53 percentage points, respectively. Full article

Manganese (Mn) is an essential trace element and a cofactor for several key enzymes, such as mitochondrial superoxide dismutase. Consequently, it plays an important defense role against reactive oxygen species. Despite this, Mn chronic overexposure can result in a neurological disorder referred to as manganism, which shares some similarities with Parkinson’s disease. Mn levels seem regulated by many transporters responsible for its uptake and efflux. These transporters play an established role in many inherited disorders of Mn metabolism and neurotoxicity. Some inherited Mn metabolism disorders, caused by mutations of SLC30A10 and SLC39A14, assume crucial importance since earlier treatment results in a better prognosis. Physicians should be familiar with the clinical presentation of these disorders as the underlying cause of dystonia/parkinsonism and look for other accompanying features, such as liver disease and polycythemia, which are typically associated with SLC30A10 mutations. This review aims to highlight the currently known Mn transporters, Mn-related neurotoxicity, and its consequences, and it provides an overview of inherited and acquired disorders of Mn metabolism. Currently available treatments are also discussed, focusing on the most frequently encountered presentations. Full article

Despite significant advancements in bridge façade defect classification, real-world automated inspections continue to face substantial challenges, including faint defect visibility, low lighting conditions, overexposure, noise interference, motion blur, and occlusions. These factors, stemming from variable environmental conditions and unstable imaging angles, severely degrade model performance. To address this issue, we introduce the Hard Defect Classification Dataset (HDCD), which systematically incorporates these six challenging conditions. Benchmarking state-of-the-art (SOTA) methods on the HDCD reveals a substantial performance drop on hard samples, highlighting the limitations of existing approaches in capturing class-specific features under adverse conditions. To enhance robustness, we propose the Prototypical Prompt Learning Framework (PPLF), inspired by prompt learning. PPLF utilizes category prototype vectors as dynamic prompts to interact with query features, guiding the model to focus on defect regions while suppressing background noise. A hierarchical feature fusion mechanism further integrates low-level texture details with high-level semantic patterns, improving defect localization and classification. Extensive experiments on ResNet-50, EfficientNetV2-L, and ViT demonstrate that PPLF consistently outperforms SOTA methods, especially achieving a 7% improvement on ResNet-50, showcasing its effectiveness in real-world civil engineering applications where robustness to challenging conditions is critical. Full article

The COVID-19 pandemic has widened the gap in mortality between different population groups. While socioeconomic status has been shown to be an important determinant of mortality, the relationship between migration status and mortality risk remains unclear. The objective of this paper is to explain whether and why foreign populations had a higher risk of mortality than Swiss nationals during the initial outbreak of the COVID-19 pandemic in Switzerland. We use original linked data to measure the risk of COVID-19 mortality for different groups of foreigners, compared to Swiss nationals, using logistic regression. We find that the risk of death from COVID-19 in 2020 was significantly higher for some groups of foreign nationals—but not all groups—compared to Swiss nationals. Increased mortality is observed among foreign communities who have been living in Switzerland for more than 20 years, notably, Italians, people of Balkan origin, and Latin Americans. For these three communities, we suggest that high mortality is due to a combination of overexposure, for socioeconomic reasons, and reduced access to health systems. These findings contribute to the understanding of migrant health disparities during pandemics and inform future public health interventions. Full article

Molybdenum is an essential trace element sourced during pregnancy from the maternal diet. Studies regarding molybdenum have primarily focused on overexposure in animal and cell culture studies. The effects of molybdenum supplementation on placental function are unknown. An immortalised trophoblast cell line was used to examine the placental cellular response to molybdenum in its bioavailable form as molybdate. Cells of the extravillous trophoblast first-trimester cell line HTR8-SVneo were cultured in complete cell media in the presence of 10 nM to 1 mM of ammonium molybdate or sodium molybdate. Following the addition of the molybdate salts, cell growth, viability, and several gene pathways were monitored. Sodium molybdate salt in doses from 10 nM to 1 mM did not affect cell growth or viability. Exposure to ammonium molybdate at a 1 mM concentration significantly decreased cell growth and viability (p < 0.05). Gene pathways involving molybdoenzyme expression, molybdenum cofactor synthesis, antioxidant response, and angiogenesis were affected following supplementation, although these effects differed depending on the dose and molybdate salt utilised. Molybdoenzyme activity was not affected by supplementation in a dose-dependent manner. The results indicate sodium molybdate is a more appropriate salt to use in vitro, as ammonium molybdate exposure reduced cell viability and growth and downregulated the expression of antioxidant genes NFE2L2 (p < 0.01), SOD1 (p < 0.001) and SOD2 (p < 0.001), suggestive of an inflammatory response. Sodium molybdate affected gene, protein, and activity levels of molybdoenzyme, antioxidant, and angiogenic molecules in vitro. This work demonstrates that sodium molybdate supplementation has pleiotropic effects in vitro and is well tolerated by placental cells at a range of nanomolar and micromolar concentrations. Full article