Search Results (83)

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is characterized by the predominance of optic neuritis, myelitis, acute disseminated encephalomyelitis (ADEM), and cortical encephalitis, and can be diagnosed by the presence of pathogenic immunoglobulin G (IgG) antibodies targeting the extracellular domain of MOG in the serum and cerebrospinal fluid (CSF). Initially considered a variant of multiple sclerosis (MS) or neuromyelitis optica spectrum disorder (NMOSD), it is now widely recognized as a separate entity, supported by converging evidence from serological, pathological, and clinical studies. Patients with MOGAD often exhibit better recovery from acute attacks; however, their clinical and pathological features vary based on the immunological role of MOG-IgG via antibody- or complement-mediated perivenous demyelinating pathology, in addition to MOG-specific cellular immunity, resulting in heterogeneous demyelinated lesions from vanishing benign forms to tissue necrosis, even though MOGAD is not a mild disease. The key is the immunological mechanism of devastating lesion coalescence and long-term degenerating mechanisms, which may still accrue, particularly in the relapsing, progressing, and aggressive clinical course of encephalomyelitis. The warning features of the severe clinical forms are: (1) fulminant acute multifocal lesions or multiphasic ADEM transitioning to diffuse (Schilder-type) or tumefactive lesions; (2) cortical or subcortical lesions related to brain atrophy and/or refractory epilepsy (Rasmussen-type); (3) longitudinally extended spinal cord lesions severely affected with residual symptoms. In addition, it is cautious for patients refractory to acute stage early 1st treatment including intravenous methylprednisolone treatment and apheresis with residual symptoms and relapse activity with immunoglobulin and other 2nd line treatments including B cell depletion therapy. Persistent MOG-IgG high titration, intrathecal production of MOG-IgG, and suggestive markers of higher disease activity, such as cerebrospinal fluid interleukin-6 and complement C5b-9, could be identified as promising markers of higher disease activity, worsening of disability, and poor prognosis, and used to identify signs of escalating treatment strategies. It is promising of currently ongoing investigational antibodies against anti-interleukin-6 receptor and the neonatal Fc receptor. Moreover, due to possible refractory issues such as the intrathecal production of autoantibody and the involvement of complement in the worsening of the lesion, further developments of other mechanisms of action such as chimeric antigen receptor T-cell (CAR-T) and anti-complement therapies are warranted in the future. Full article

It is critical to inform the public of the threat heat poses to health and provide actionable guidance on mitigating this risk before, during, and after heat events. To help educate the public during heat events, Health Canada works closely with Environment and Climate Change Canada (ECCC) to distribute heat-health messaging through a weather warning system. However, the warning system’s current list of messages dates back over a decade. Continually evaluating and updating messages is critical to ensure they are based on the best evidence available. A review was conducted to assess the existing heat-health messages and propose new messages based on recent empirical studies. The proposed messages were reviewed to ensure that readability and equity considerations were integrated. Academic, public health and meteorology experts across Canada reviewed the proposed messages and applied further revisions. The original list of heat-health messages included 12 messages. Based on the evidence and external reviews provided by 42 experts (academic: n = 9; public health: n = 22; meteorology: n = 11), messages were removed, merged, added and revised. The final list used by ECCC includes 30 messages. Health Canada’s heat-health messages disseminated through ECCC’s weather warning system were revised to ensure they are important, action-oriented, evidence-based, readable, equitable, regionally applicable, and timely. Ensuring these messages reflect current knowledge will be an ongoing and iterative process to support the public’s preparedness efforts to protect themselves and others during heat events. Full article

The need for systems that forecast and respond proactively to meteorological disasters is growing amid climate variability. Although the early warning system in South Korea includes countermeasure information, it remains limited in terms of data recency, granularity, and regional adaptability. Additionally, its closed architecture hinders interoperability with external systems. This study aims to redesign the countermeasure function as an independent cloud-based platform grounded in the common standard terminology framework in South Korea. A multi-dimensional data model was developed using attributes such as crop type, cultivation characteristics, growth stage, disaster type, and risk level. The platform incorporates user-specific customization features and history tracking capabilities, and it is structured using a microservices architecture to ensure modularity and scalability. The proposed system enables real-time management and dissemination of localized countermeasure suggestions tailored to various user types, including central and local governments and farmers. This study offers a practical model for enhancing the precision and applicability of agrometeorological response information. It is expected to serve as a scalable reference platform for future integration with external agricultural information systems. Full article

Background/Objectives: The combination drug sulfamethoxazole/trimethoprim (ST) is a broad-spectrum antibiotic used against various infections; however, it is associated with several serious adverse events. The ST package inserts contain warnings about these adverse events. However, warnings vary internationally, and specific measures to address ST-related adverse events are unclear. Therefore, we aimed to comprehensively evaluate ST-related adverse events using the Japanese Adverse Drug Event Report (JADER) database and analyze the onset time for each event. Methods: Adverse events due to ST were analyzed using the JADER database between April 2004 and June 2023. The reported odds ratio and 95% confidence interval (95% confidence interval [CI]) were calculated, with a signal detected if the 95% CI lower limit exceeded 1. The Weibull distribution was used to characterize the onset time of adverse events with detected signals. Results: The total number of cases in the JADER database during the study period was 862,952, and the number of adverse events involving ST as a suspected drug was 4203. Adverse events associated with ST include hyperkalemia, syndrome of inappropriate antidiuretic hormone secretion, hematopoietic cytopenia, acute renal failure, hypoglycemia, disseminated intravascular coagulation syndrome, hepatic disorder, and the Stevens–Johnson syndrome/toxic epidermal necrolysis. Conclusions: Weibull analysis indicated an early failure-type onset time for all adverse events, suggesting the need for intensive adverse event monitoring of ST, especially in the first month of use. These findings may support revising drug package inserts in Japan to better reflect the identified risks. Full article

Historical districts face pressing disaster preparedness challenges due to their special spatial properties—risks compounded by static approaches that overlook dynamic fire–pedestrian interactions. This study employs an agent-based model (ABM) for fire simulations and AnyLogic pedestrian dynamics to address these gaps in Dukezong Ancient Town, Yunnan Province, China, considering diverse ignition points, seasonal temperatures, and wind conditions. Dynamic simulations of 16 scenarios reveal critical spatial impacts: within 30 min, ≥28% of streets became impassable, with central ignition points causing faster obstructions. Static models underestimate evacuation durations by up to 135%, neglecting early stage congestions and detours caused by high-temperature zones. Congestions are concentrated along main east–west arterial roads, worsening with longer warning distances. A mismatch between evacuation flows and shelter capacity is found. Thus, a three-stage interaction simplification is derived: localized detours (0–10 min), congestion-driven delays on critical roads (11–30 min), and prolonged structural damage afterward. This study challenges static approaches by highlighting the “fast alert-fast congestion” paradox, where rapid alerts overwhelm narrow pathways. Solutions prioritize multi-route guidance systems, optimized shelter access points, and real-time information dissemination to reduce bottlenecks without costly infrastructure changes. This study advances disaster modeling by bridging disaster development with dynamic evacuation, offering a replicable framework for similar environments. Full article

Following the U.S. Food and Drug Administration’s warning against power morcellators due to potential cell dissemination of occult malignancy, there has been a shift away from minimally invasive approaches. This concern also overshadows the well-documented advantages of minimally invasive surgery in benign gynecology. Objectives: To evaluate whether intraperitoneal cell dissemination during laparoscopic surgery for uterine fibroids can be reduced by (i) the choice of morcellation method and/or (ii) copious irrigation after the procedure. Methods: This prospective multicenter comparative pilot study included 72 women undergoing laparoscopic myomectomy (LM) or total laparoscopic hysterectomy (TLH) for benign conditions. Women were divided into four groups in order to compare different types of morcellation, including a reference group without morcellation: (i) LM with power morcellation (n = 21, Group A), (ii) TLH with en-bloc transvaginal tissue removal without morcellation (n = 17, Group B), (iii) TLH with manual vaginal morcellation (n = 19, Group C), and (iv) TLH with contained manual vaginal morcellation (n = 15, Group D). Patients receiving cold knife morcellation were randomized into Groups C or D. In order to assess cell spread before surgery, after surgery but before morcellation, after morcellation, and after abdominal irrigation with a total of 3000 mL saline solution, peritoneal washings were collected at six timepoints. Results: After specimen removal (TP3), cell spread was significantly higher in cases with power morcellation [13/19 (68%) in Group A] compared to transvaginal cold knife morcellation, both contained and uncontained [Group C 1/14 (7%) and Group D 1/19 (9%)] (p < 0.001), or to TLH with en bloc removal [Group B 1/17 (6%)]. Saline irrigation reduced the positive cytologies. After 3000 mL (TP6), the difference between Group A and the TLH groups was not significant [4/18 (22%) vs. 3/45 (7%), p = 0.079]. Conclusions: Our study shows that (i) transvaginal cold knife morcellation results in significantly less peritoneal cell dissemination than power morcellation, and (ii) peritoneal irrigation with 3000 mL of saline significantly reduces residual cell presence. These findings could support maintaining minimally invasive approaches while addressing safety concerns. Full article

Ethiopian pastoralist communities are facing a recurrent drought crisis that significantly affects the availability of water and pasture resources for communities dependent on livestock. The increasing intensity, duration and frequency of droughts in the pastoral community in Ethiopia have drawn the attention of multiple stakeholders and increased stakeholder debates on the role of early warning systems (EWSs) for anticipatory action to build climate resilience in the pastoral community. The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), in collaboration with various partners, has developed an interactive web-based digital EWS to provide near real-time information on water and pasture conditions in pastoral and agro-pastoral regions of Ethiopia. In this study, a stakeholder analysis was conducted to identify key stakeholders, understand stakeholder needs, and facilitate collaboration towards sustaining the EWS. The stakeholder analysis revealed the roles and information needs of key actors engaged in livestock water and pasture monitoring and early warning systems aimed at improving the pastoral communities’ resilience. The analysis showed a pressing need for access to real-time information on water and pasture availability and seasonal climate forecasts by local communities for effective and optimal resources management. Local and national governments need similar data for evidence-based decision-making in resource allocation and policy development. International and non-governmental organizations (INGOs) require the same information for efficient humanitarian responses and targeted development interventions. The private sector seeks insights into market dynamics to better align production strategies with community needs. An EWS serves as a vital tool for development partners, facilitating improved planning, coordination, and impact assessment. It also emphasizes the importance of proactive collaboration among stakeholders, including local communities, government bodies, INGOs, and academic and research institutions. Enhanced communication strategies, such as partnerships with local media, are essential for timely information dissemination. Ultimately, sustained collaboration and adaptive strategies are crucial for optimizing the impact of an EWS towards improving the livelihoods and resilience of pastoral communities amid climate variability. Full article

Extreme rainfall events are significant manifestations of climate change, causing substantial impacts on urban infrastructure and public life. This study takes the extreme rainfall event in Beijing in 2023 as the background and utilizes data from Sina Weibo. Based on large language models and prompt engineering, disaster information is extracted, and a multi-factor coupled disaster multi-sentiment classification model, Bert-BiLSTM, is designed. A disaster analysis framework focusing on three dimensions of theme, location and sentiment is constructed. The results indicate that during the pre-disaster stage, themes are concentrated on warnings and prevention, shifting to specific events and rescue actions during the disaster, and post-disaster, they express gratitude to rescue personnel and highlight social cohesion. In terms of spatial location, the disaster shows significant clustering, predominantly occurring in Mentougou and Fangshan. There is a clear difference in emotional expression between official media and the public; official media primarily focuses on neutral reporting and fact dissemination, while public sentiment is even richer. At the same time, there are also variations in sentiment expressions across different affected regions. This study provides new perspectives and methods for analyzing extreme rainfall events on social media by revealing the evolution of disaster themes, the spatial distribution of disasters, and the temporal and spatial changes in sentiment. These insights can support risk assessment, resource allocation, and public opinion guidance in disaster emergency management, thereby enhancing the precision and effectiveness of disaster response strategies. Full article

The Australian Bureau of Meteorology provides flood forecasting and warning services across Australia for most major rivers in Australia, in cooperation with other government, local agencies and emergency services. As part of this service, the Bureau issues a flood watch product to provide early advice on a developing situation that may lead to flooding up to 4 days prior to an event. This service is based on (a) an ensemble of available Numerical Weather Prediction (NWP) rainfall forecasts, (b) antecedent soil moisture, stream and dam conditions, (c) hydrological forecasts using event-based models and (d) expert meteorological and hydrological input by Bureau of Meteorology staff, to estimate the risk of reaching pre-specified river height thresholds at locations across the continent. A flood watch provides information about a developing weather situation including forecasting rainfall totals, catchments at risk of flooding, and indicative severity where required. Although there is uncertainty attached to a flood watch, its early dissemination can help individuals and communities to be better prepared should flooding eventuate. This paper investigates the utility of forecasts of daily gridded national runoff to inform the risk of riverine flooding up to 7 days in advance. The gridded national water balance model (AWRA-L) runoff outputs generated using post-processed 9-day Numerical Weather Prediction hindcasts were evaluated as to whether they could accurately predict exceedance probabilities of runoff at gauged locations. The approach was trialed over 75 forecast locations across North East Australia (Queensland). Forecast 3-, 5- and 7-day accumulations of runoff over the catchment corresponding to each location were produced, identifying whether accumulated runoff reached either 95% or 99% historical levels (analogous to minor, moderate and major threshold levels). The performance of AWRA-L runoff-based flood likelihood was benchmarked against that based on precipitation only (i.e., not rainfall–runoff transformation). Both products were evaluated against the observed runoff data measured at the site. Our analysis confirmed that this runoff-based flood likelihood guidance could be used to support the generation of flood watch products. Full article

This paper proposes a flood risk visualization method that is (1) readily transferable (2) hyperlocal, (3) computationally inexpensive, and (4) geometrically accurate. This proposal is for risk communication, to provide high-resolution, three-dimensional flood visualization at the sub-meter level. The method couples a laser scanning point cloud with algorithms that produce textured floodwaters, achieved through compounding multiple sine functions in a graphics shader. This hyper-local approach to visualization is enhanced by the ability to portray changes in (i) watercolor, (ii) texture, and (iii) motion (including dynamic heights) for various flood prediction scenarios. Through decoupling physics-based predictions from the visualization, a dynamic, flood risk viewer was produced with modest processing resources involving only a single, quad-core processor with a frequency around 4.30 GHz and with no graphics card. The system offers several major advantages. (1) The approach enables its use on a browser or with inexpensive, virtual reality hardware and, thus, promotes local dissemination for flood risk communication, planning, and mitigation. (2) The approach can be used for any scenario where water interfaces with the built environment, including inside of pipes. (3) When tested for a coastal inundation scenario from a hurricane, 92% of the neighborhood participants found it to be more effective in communicating flood risk than traditional 2D mapping flood warnings provided by governmental authorities. Full article

Klebsiella pneumoniae represent a common invasive infection etiological agent, whose potential carbapenem-resistance and hypermucoviscosity complicate the patient’s management. Infection development often derives from gastrointestinal colonization; thus, it is fundamental to monitor asymptomatic K. pneumoniae colonization through surveillance protocols, especially for intensive care and immunocompromised patients. We described a six-month routine screening protocol from the Policlinico of Catania (Italy), while blood samples were collected from the same patients only in cases of a systemic infection suspicion. All the patients who had dissemination episodes were furtherly investigated through next-generation sequencing, analyzing both colonizing and disseminating strains. This study documents emerging invasive sequence types such as ST101, ST307, and ST395, mainly revealing blaNDM or blaKPC genes, along with siderophores and hyperproduction capsule markers as virulence factors. Most of the detected factors are presumably related to a specific plasmid content, which are extremely varied and rich. In conclusion, active surveillance through sequencing is essential to enhance awareness of local epidemiology within high-risk multi-drug resistance areas. A random sequencing analysis on the most warning microorganisms could enhance sequence typing (ST) awareness within specific settings, allowing for better prevention control strategies on their eventual persistence or diffusion. Full article

A nondestructive approach for accurate crop yield prediction at the field scale is vital for precision agriculture. Considerable progress has been made in the use of the spectral index (SI) derived from unmanned aerial vehicle (UAV) hyperspectral images to predict crop yields before harvest. However, few studies have explored the most sensitive wavelengths and SIs for crop yield prediction, especially for different nitrogen fertilization levels and soil types. This study aimed to investigate the appropriate wavelengths and their combinations to explore the ability of new SIs derived from UAV hyperspectral images to predict yields during the growing season of spring maize. In this study, the hyperspectral canopy reflectance measurement method, a field-based high-throughput method, was evaluated in three field experiments (Wang-Jia-Qiao (WJQ), San-Ke-Shu (SKS), and Fu-Jia-Jie (FJJ)) since 2009 with different soil types (alluvial soil, black soil, and aeolian sandy soil) and various nitrogen (N) fertilization levels (0, 168, 240, 270, and 312 kg/ha) in Lishu County, Northeast China. The measurements of canopy spectral reflectance and maize yield were conducted at critical growth stages of spring maize, including the jointing, silking, and maturity stages, in 2019 and 2020. The best wavelengths and new SIs, including the difference spectral index, ratio spectral index, and normalized difference spectral index forms, were obtained from the contour maps constructed by the coefficient of determination (R²) from the linear regression models between the yield and all possible SIs screened from the 450 to 950 nm wavelengths. The new SIs and eight selected published SIs were subsequently used to predict maize yield via linear regression models. The results showed that (1) the most sensitive wavelengths were 640–714 nm at WJQ, 450–650 nm and 750–950 nm at SKS, and 450–700 nm and 750–950 nm at FJJ; (2) the new SIs established here were different across the three experimental fields, and their performance in maize yield prediction was generally better than that of the published SIs; and (3) the new SIs presented different responses to various N fertilization levels. This study demonstrates the potential of exploring new spectral characteristics from remote sensing technology for predicting the field-scale crop yield in spring maize cropping systems before harvest. Full article

Nuclear power plants (NPPs) rely on critical, complex systems that require continuous monitoring to ensure safe operation under both normal and abnormal conditions. Despite the potential of artificial intelligence (AI) to enhance predictive capabilities in these systems, limited research has been conducted on the application of AI algorithms within NPPs. This presents a knowledge gap in the integration of AI for improving safety, reliability, and decision making in NPP. In this study, we explore the use of AI methods, including machine learning and real-time data analytics, applied to NPP components to address the nonlinearity and dynamic behavior inherent in reactor operations. Through the implementation of AI and Internet of Things (IoT) devices, we propose a system that enables early warning and real-time data transmission to regulatory authorities and decision-makers, ensuring better coordination during incidents. Lessons from past nuclear accidents, such as Chernobyl, emphasize the importance of timely information dissemination to mitigate risks. However, this integration also presents challenges, including cybersecurity risks and the need for updated regulations to address AI use in safety-critical environments. The results of this study highlight the urgent need for further research on the application of AI in NPPs, with a particular focus on addressing these challenges to ensure safe implementation. Full article

The TEST pervasive use of social media has highlighted the importance of developing sophisticated models for early information warning systems within online communities. Despite the advancements that have been made, existing models often fail to adequately consider the pivotal role of network topology and temporal dynamics in information dissemination. This results in suboptimal predictions of content propagation patterns. This study introduces the User Propagation Influence-based Linear Threshold (UPI-LT) model, which represents a novel approach to the simulation of information spread. The UPI-LT model introduces an innovative approach to consider the number of active neighboring nodes, incorporating a time decay factor to account for the evolving influence of information over time. The model’s technical innovations include the incorporation of a homophily ratio, which assesses the similarity between users, and a dynamic adjustment of activation thresholds, which reflect a deeper understanding of social influence mechanisms. Empirical results on real-world datasets validate the UPI-LT model’s enhanced predictive capabilities for information spread. Full article

While mangrove ecosystems are rich in biodiversity, they are increasingly impacted by climate change and urban pollutants. The current study provides first insights into the emergence of potentially pathogenic yeasts in Hong Kong’s mangroves. Sediment and water samples were collected from ten urban and rural mangroves sites. Initial CHROMagar^TM Candida Plus screening, representing the first application of this differential medium for water and soil samples collected from a non-clinical environment, enabled the rapid, preliminary phenotypic identification of yeast isolates from mangroves. Subsequent molecular profiling (ITS and/or 28S nrDNA sequencing) and antifungal drug susceptibility tests were conducted to further elucidate yeast diversity and drug resistance. A diversity of yeasts, including 45 isolates of 18 distinct species across 13 genera/clades, was isolated from sediments and waters from Hong Kong mangroves. Molecular profiling revealed a dominance of the Candida/Lodderomyces clade (44.4%), a group of notorious opportunistic pathogens. The findings also reveal a rich biodiversity of non-Candida/Lodderomyces yeasts in mangroves, including the first reported presence of Apiotrichum domesticum and Crinitomyces flavificans. A potentially novel Yamadazyma species was also discovered. Remarkably, 14.3% of the ubiquitous Candida parapsilosis isolates displayed resistance to multiple antifungal drugs, suggesting that mangroves may be reservoirs of multi-drug resistance. Wildlife, especially migratory birds, may disseminate these hidden threats. With significant knowledge gaps regarding the environmental origins, drug resistance, and public health impacts of pathogenic yeasts, urgent surveillance is needed from a One Health perspective. This study provides an early warning that unrestrained urbanization can unleash resistant pathogens from coastal ecosystems globally. It underscores the necessity for enhanced surveillance studies and interdisciplinary collaboration between clinicians, ornithologists, and environmental microbiologists to effectively monitor and manage this environmental health risk, ensuring the maintenance of ‘One Health’. Full article