Search Results (2,512)

Since late 2023, an increase in Bordetella pertussis infections has been noticed in Europe, particularly among children. Our data showed the upward trend of B. pertussis cases in the Lazio region, even among adults with severe influenza-like illnesses, highlighting the necessity for maintaining high vaccination rates across both children and adults. These findings underscore the urgent need for clinicians to maintain a high index of suspicion for B. pertussis in patients with respiratory symptoms, prioritize nasopharyngeal swabs for accurate diagnosis, assess for co-infections, verify booster vaccination status in adults, and support timely reporting to public health authorities. Full article

Natural disasters like wildfires pose significant threats to communities, which necessitates timely and effective disaster response strategies. While Aspect-based Sentiment Analysis (ABSA) has been widely used to extract sentiment-related information at the sub-sentence level, the corresponding field of Aspect-based Emotion Analysis (ABEA) remains underexplored due to dataset limitations and the increased complexity of emotion classification. In this study, we used EmoGRACE, a fine-tuned BERT-based model for ABEA, which we applied to georeferenced tweets of the 2020 California wildfires. The results for this case study reveal distinct spatio-temporal emotion patterns for wildfire-related aspect terms, with fear and sadness increasing near wildfire perimeters. This study demonstrates the feasibility of tracking emotion dynamics across disaster-affected regions and highlights the potential of ABEA in real-time disaster monitoring. The results suggest that ABEA can provide a nuanced understanding of public sentiment during crises for policymakers. Full article

Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive to climate change, and climate change and large-scale ecological restoration have led to significant changes in the dynamic of dryland vegetation. However, few studies have explored the nonlinear relationships between these factors and vegetation dynamic. In this study, we integrated trend analysis (using the Mann–Kendall test and Theil–Sen estimation) and machine learning algorithms (XGBoost-SHAP model) based on long time-series remote sensing data from 2001 to 2020 to quantify the nonlinear response patterns and threshold effects of bioclimatic variables, topographic features, soil attributes, and anthropogenic factors on vegetation dynamic. The results revealed the following key findings: (1) The kNDVI in the study area showed an overall significant increasing trend (p < 0.01) during the observation period, of which 26.7% of the area showed a significant increase. (2) The water content index (Bio 23, 19.6%), the change in land use (15.2%), multi-year average precipitation (pre, 15.0%), population density (13.2%), and rainfall seasonality (Bio 15, 10.9%) were the key factors driving the dynamic change of vegetation, with the combined contribution of natural factors amounting to 64.3%. (3) Among the topographic factors, altitude had a more significant effect on vegetation dynamics, with higher altitude regions less likely to experience vegetation greening. Both natural and anthropogenic factors exhibited nonlinear responses and interactive effects, contributing to the observed dynamic trends. This study provides valuable insights into the driving mechanisms behind the condition of vegetation in arid and semi-arid regions of China and, by extension, in other arid regions globally. Full article

Previous reviews have examined specific facets of Geographic Information Systems (GIS) in transportation planning, such as transit-focused applications and open source geospatial tools. However, this study offers the first systematic, PRISMA-guided longitudinal evaluation of GIS integration in transportation planning, spanning thematic domains, data models, methodologies, and outcomes from 2004 to 2024. This study addresses this gap through a longitudinal analysis of GIS-based transportation research from 2004 to 2024, adhering to PRISMA guidelines. By conducting a mixed-methods analysis of 241 peer-reviewed articles, this study delineates major trends, such as increased emphasis on sustainability, equity, stakeholder involvement, and the incorporation of advanced technologies. Prominent domains include land use–transportation coordination, accessibility, artificial intelligence, real-time monitoring, and policy evaluation. Expanded data sources, such as real-time sensor feeds and 3D models, alongside sophisticated modeling techniques, enable evidence-based, multifaceted decision-making. However, challenges like data limitations, ethical concerns, and the need for specialized expertise persist, particularly in developing regions. Future geospatial innovations should prioritize the responsible adoption of emerging technologies, inclusive capacity building, and environmental justice to foster equitable and efficient transportation systems. This review highlights GIS’s evolution from a supplementary tool to a cornerstone of data-driven, sustainable urban mobility planning, offering insights for researchers, practitioners, and policymakers to advance transportation strategies that align with equity and sustainability goals. Full article

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

Background/Objectives: This study investigated the timing of adverse events (AEs) after carbon-ion radiotherapy (CIRT) for hepatocellular carcinoma (HCC) and identified the risk factors for biliary stricture post CIRT. Methods: This retrospective study included 103 patients with HCC who had undergone CIRT (60 Gy/4 fractions). The onset, frequency, and grade of AEs after CIRT were analyzed. HCC was classified into perihilar and distal types to assess the frequency of biliary stricture, and the risk factors for biliary stricture were investigated. Results: AEs after CIRT were more frequent in patients with liver dysfunction, skin redness/dermatitis, and pigmentation. Biliary stricture occurred long after CIRT (3.0–17.0 months). Most AEs were of grade 1–2. Grade ≥ 3 AEs included biliary stricture (2.9%) and radiation gastric ulcer (1.0%), whereas grade 5 AEs included biliary stricture (1.9%). Biliary stricture was exclusively observed in patients with perihilar-type HCC. Among patients with perihilar-type HCC, those having a tumor in the portal vein trunk branch area were more prone to biliary stricture than those with a tumor in the primary portal vein branch area (p = 0.0018), and all grade ≥ 3 biliary strictures (2.9%) were observed in the portal vein trunk branch area. Patients with perihilar-type HCC and biliary stricture were more likely to have macrovascular invasion (p = 0.0052) and previous local therapy targeting the perihilar region (p = 0.0371) than those without biliary stricture. Conclusions: This study reported the detailed data of AEs post CIRT for HCC and the risk factors for biliary stricture post CIRT. Full article

Background: Hypoxic–ischemic encephalopathy (HIE) is a leading cause of severe neurological impairments in childhood. Therapeutic hypothermia (TH) is both safe and effective in neonates born at ≥36 weeks gestation with moderate to severe HIE. We aimed to evaluate short-term outcomes—including brain injury detected on magnetic resonance imaging (MRI)—in infants born at 34–35 weeks of gestation drawing on our clinical experience with neonates under 36 weeks of gestational age (GA). Methods: In this retrospective cohort study, 20 preterm infants with a GA of 34 to 35 weeks and a matched cohort of 80 infants with a GA of ≥36 weeks who were diagnosed with moderate to severe HIE and underwent TH were included. Infants were matched in a 1:4 ratio based on the worst base deficit in blood gas and sex. Maternal and neonatal characteristics, brain MRI findings and short term outcomes were compared. Results: Infants with a GA of 34–35 weeks had a lower birth weight and a higher rate of caesarean delivery (both p < 0.001). Apgar scores, sex, intubation rate in delivery room, blood gas pH, base deficit and lactate were comparable between the groups. Compared to infants born at ≥36 weeks of GA, preterm neonates were more likely to receive inotropes, had a longer time to achieve full enteral feeding, and experienced a longer hospital stay. The mortality rate was 10% in the 34–35 weeks GA group. Neuroimaging revealed injury in 66.7% of infants born at 34–35 weeks of gestation and in 58.8% of those born at ≥36 weeks (p = 0.56). Injury was observed across multiple brain regions, with white matter being the most frequently affected in the 34–35 weeks GA group. Thalamic and cerebellar abnormal signal intensity or diffusion restriction, punctate white matter lesions, and diffusion restriction in the corpus callosum and optic radiations were more frequently detected in infants born at 34–35 weeks of gestation. Conclusions: Our study contributes to the growing body of literature suggesting that TH may be feasible and tolerated in late preterm infants. Larger randomized controlled trials focused on this vulnerable population are necessary to establish clear guidelines regarding the safety and efficacy of TH in late preterm infants. Full article

Background: Human metapneumovirus (hMPV) is a respiratory pathogen that causes illness ranging from mild upper respiratory tract infections to severe pneumonia, particularly in individuals with comorbidities. Fatal cases of hMPV-induced hemorrhagic pneumonia are rare and likely under-reported. Diagnosis is often delayed due to overlapping symptoms with other respiratory viruses and the rapid progression of the disease. Case presentation: We report the case of a 55-year-old man with a complex medical history, including liver cirrhosis and diabetes mellitus, who developed acute viral pneumonia. Initial symptoms appeared three days before a sudden clinical deterioration marked by shortness of breath, hemoptysis, and respiratory failure. A nasopharyngeal swab taken on the third day of illness tested positive for hMPV by qRT-PCR. The patient died the following day. Postmortem molecular testing confirmed hMPV in lung tissue and alveolar contents. Autopsy revealed bilateral hemorrhagic pneumonia with regional lymphadenopathy. Histopathological examination showed alveolar hemorrhage, multinucleated cells, neutrophilic infiltration, activated autophagy in macrophages, and numerous cytoplasmic eosinophilic viral inclusions. Conclusions: This is the first documented case of fatal hMPV pneumonia in Armenia. It highlights the potential severity of hMPV in adults with chronic health conditions and emphasizes the need for timely molecular diagnostics. Postmortem identification of characteristic viral inclusions may serve as a cost-effective histopathological marker of hMPV-associated lung pathology. Full article

Extreme heat poses growing health risks in tropical regions, yet public perception of this threat remains understudied in the Caribbean. This study examines how residents in Puerto Rico perceived heat-related health risks and how these perceptions relate to vulnerability and protective behaviors during the extreme heat events of the summer of 2020. We conducted a cross-sectional telephone survey of 500 adults across metropolitan and non-metropolitan areas of Puerto Rico, using stratified probability sampling. The questionnaire assessed heat risk perception, sociodemographic characteristics, health status, prior heat exposure, and heat-related behaviors. While most participants expressed concern about climate change and high temperatures, fewer than half perceived heat as a high level of personal health risk. Higher levels of risk perception were significantly associated with being male, aged 50–64, unemployed, and in fair health, having multiple chronic conditions, and prior experience with heat-related symptoms. Those with symptoms were nearly five times more likely to report high levels of risk perception (OR = 4.94, 95% CI: 2.93–8.34). In contrast, older adults (65+), despite their higher level of vulnerability, reported lower levels of risk perception and fewer symptoms. Nighttime heat exposure was widespread and strongly associated with heat-related symptoms. Common coping strategies included the use of fans and air conditioning, though economic constraints and infrastructure instability limited access. The findings highlight the disparity between actual and perceived vulnerability, particularly among older adults. Public health strategies should focus on risk communication tailored to vulnerable groups and address barriers to heat adaptation. Strengthening heat resilience in Puerto Rico requires improved infrastructure, equitable access to cooling, and targeted outreach. Full article

Extreme heat is a pressing public health threat. This study assesses and describes the interrelationships between beliefs about heat waves, individuals’ precautionary behaviors during heat waves, and demographic factors. In May 2022, we surveyed 1051 residents (aged 25–90 years) in Southern Spain, a region that experiences frequent heat waves. We found that many participants engaged in heat wave avoidance (80.5%, e.g., spending more time indoors), impact reduction (63.7%, e.g., drinking more water), or prosocial behavior (31.6%, e.g., helping others). However, one in four (25.9%) respondents also indicated that they personally do not need to worry about heat waves. Heat wave beliefs and behaviors were modestly correlated with demographic characteristics. Individuals who view themselves as less vulnerable to heat-related health risks (“impervious” beliefs) were less likely to report altering their behavior during heat waves. Public health efforts aiming to change behavior during heat waves may anticipate “impervious” beliefs and demographic differences in risk perception and heat-related behaviors. Full article

Carbapenem resistance is considered one of the greatest current threats to public health, particularly in the management of infections in clinical settings. Carbapenem resistance in bacteria is mainly due to mechanisms such as the production of carbapenemases (such as the imipenemase IMP, or other enzymes like VIM, NDM, and KPC), that can be detected by several laboratory tests, including immunochromatography and automated real-time PCR (qPCR). Methods: As part of local studies to monitor carbapenem-resistant bacteria in Costa Rica, two cases were initially identified with inconsistent IMP detection results. A possible gene drop-out in the automated qPCR test was suggested based on the negative result, contrasting with the positive result by immunochromatography and whole-genome sequencing. We hypothesized that molecular testing could be optimized through the development of tailored assays to improve the detection of IMP genes. Thus, using IMP gene sequences from the local isolates and regional sequences in databases, primers were redesigned to extend the detection of IMP alleles of regional relevance. Results: The tailored qPCR was applied to a local collection of 119 carbapenem-resistant isolates. The genomes of all 14 positive cases were sequenced, verifying the results of the custom qPCR, despite the negative results of the automated testing. Conclusions: Guided by whole-genome sequencing, it was possible to extend the molecular detection of IMP alleles circulating in Latin America using a tailored qPCR to overcome IMP gene drop-out and false-negative results in an automated qPCR. Full article

Accurate prediction of landslide-induced displacement is essential for the structural integrity and operational safety of buildings and infrastructure situated in geologically unstable regions. This study introduces a novel hybrid predictive framework that synergistically integrates Gaussian Process Regression (GPR) with Temporal Convolutional Neural Networks (TCNs), herein referred to as the GTCN model, to forecast displacement at building monitoring points subject to landslide activity. The proposed methodology is validated using time-series monitoring data collected from the slope adjacent to the Zhongliang Reservoir in Wuxi County, Chongqing, an area where slope instability poses a significant threat to nearby structural assets. Experimental results demonstrate the GTCN model’s superior predictive performance, particularly under challenging conditions of incomplete or sparsely sampled data. The model proves highly effective in accurately characterizing both abrupt fluctuations within the displacement time series and capturing long-term deformation trends. Furthermore, the GTCN framework outperforms comparative hybrid models based on Gated Recurrent Units (GRUs) and GPR, with its advantage being especially pronounced in data-limited scenarios. It also exhibits enhanced capability for temporal feature extraction relative to conventional imputation-based forecasting strategies like forward-filling. By effectively modeling both nonlinear trends and uncertainty within displacement sequences, the GTCN framework offers a robust and scalable solution for landslide-related risk assessment and early warning applications. Its applicability to building safety monitoring underscores its potential contribution to geotechnical hazard mitigation and resilient infrastructure management. Full article

Background: Choroidal nevi are common, benign tumors. These tumors rarely cause adverse retinal sequalae, but when they do, they can lead to disruption of the outer retina and vision loss. In this paper, we used high-resolution retinal imaging modalities, optical coherence tomography (OCT) and adaptive optics scanning laser ophthalmoscopy (AOSLO), to longitudinally monitor retinal sequelae of a submacular choroidal nevus. Methods: A 31-year-old female with a high-risk choroidal nevus resulting in subretinal fluid (SRF) and a 30-year-old control subject were longitudinally imaged with AOSLO and OCT in this study over 18 and 22 months. Regions of interest (ROI) including the macular region (where SRF was present) and the site of laser photocoagulation were imaged repeatedly over time. The depth of SRF in a discrete ROI was quantified with OCT and AOSLO images were assessed for visualization of photoreceptors and retinal pigmented epithelium (RPE). Cell-like structures that infiltrated the site of laser photocoagulation were measured and their count was assessed over time. In the control subject, images were assessed for RPE visualization and the presence and stability of cell-like structures. Results: We demonstrate that AOSLO can be used to assess cellular-level changes at small ROIs in the retina over time. We show the response of the retina to SRF and laser photocoagulation. We demonstrate that the RPE can be visualized when SRF is present, which does not appear to depend on the height of retinal elevation. We also demonstrate that cell-like structures, presumably immune cells, are present within and adjacent to areas of SRF on both OCT and AOSLO, and that similar cell-like structures infiltrate areas of retinal laser photocoagulation. Conclusions: Our study demonstrates that dynamic, cellular-level retinal responses to SRF and laser photocoagulation can be monitored over time with AOSLO in living humans. Many retinal conditions exhibit similar retinal findings and laser photocoagulation is also indicated in numerous retinal conditions. AOSLO imaging may provide future opportunities to better understand the clinical implications of such responses in vivo. Full article

Background: The profile of germline genetic variants among colorectal cancer patients in Panama has not yet been explored. Methods: We recruited 95 patients with colorectal cancer in an Oncology Reference Hospital Unit in the Azuero region of central Panama, which exhibited the highest prevalence of colorectal cancer in Panama. DNA analysis was performed with a panel of 113 genes with germline mutations for cancer (TruSight^® Cancer Sequencing Panel from Illumina, San Diego, CA, USA). Results: Among the 95 cases, 10 pathogenic/likely pathogenic variants (P/LP) were identified in the MUTYH, TP53, CHEK2, PALB2, ATM, and BARD1 genes, representing 10% of the total. The variant 1103G>A (p.Gly368Asp) in MUTYH was the most prevalent. The variant at c.1675_1676delCAinsTG (p.Gln559Ter) in PALB2 is new and is reported for the first time in this study. Variants were most frequently detected in the MUTYH and CHEK2 genes, affecting four and two patients, respectively. Notably, none of the 95 Panamanian patients in the initial colorectal cancer cohort had mutations in mismatch repair (MMR) genes. These genes are among the most frequently mutated in other cohorts around the world. Conclusions: The atypical profile of germline genetic variants in this population may be related to the unique characteristics of the Azuero population in Panama’s central region. This profile may partly explain the high prevalence of colorectal cancer among its inhabitants. Full article

During the automated picking of table grapes, the automatic recognition and segmentation of grape pedicels, along with the positioning of picking points, are vital components for all the following operations of the harvesting robot. In the actual scene of a grape plantation, however, it is extremely difficult to accurately and efficiently identify and segment grape pedicels and then reliably locate the picking points. This is attributable to the low distinguishability between grape pedicels and the surrounding environment such as branches, as well as the impacts of other conditions like weather, lighting, and occlusion, which are coupled with the requirements for model deployment on edge devices with limited computing resources. To address these issues, this study proposes a novel picking point localization method for table grapes based on an instance segmentation network called Progressive Global-Local Structure-Sensitive Segmentation (PGSS-YOLOv11s) and a simple combination strategy of morphological operators. More specifically, the network PGSS-YOLOv11s is composed of an original backbone of the YOLOv11s-seg, a spatial feature aggregation module (SFAM), an adaptive feature fusion module (AFFM), and a detail-enhanced convolutional shared detection head (DE-SCSH). And the PGSS-YOLOv11s have been trained with a new grape segmentation dataset called Grape-⊥, which includes 4455 grape pixel-level instances with the annotation of ⊥-shaped regions. After the PGSS-YOLOv11s segments the ⊥-shaped regions of grapes, some morphological operations such as erosion, dilation, and skeletonization are combined to effectively extract grape pedicels and locate picking points. Finally, several experiments have been conducted to confirm the validity, effectiveness, and superiority of the proposed method. Compared with the other state-of-the-art models, the main metrics $F1$ score and mask mAP@0.5 of the PGSS-YOLOv11s reached 94.6% and 95.2% on the Grape-⊥ dataset, as well as 85.4% and 90.0% on the Winegrape dataset. Multi-scenario tests indicated that the success rate of positioning the picking points reached up to 89.44%. In orchards, real-time tests on the edge device demonstrated the practical performance of our method. Nevertheless, for grapes with short pedicels or occluded pedicels, the designed morphological algorithm exhibited the loss of picking point calculations. In future work, we will enrich the grape dataset by collecting images under different lighting conditions, from various shooting angles, and including more grape varieties to improve the method’s generalization performance. Full article