Search Results (1,313)

Background/Objectives: This overview provides a comprehensive safety evaluation of the approved live-attenuated vaccine VLA1553 (IXCHIQ^®) for active immunization for the prevention of disease caused by chikungunya virus (CHIKV) in clinical trials. Methods: Protocol-defined solicited systemic events (i.e., fever, arthralgia, myalgia, fatigue, and headache) and other unsolicited arthralgia-related events were evaluated. Additionally, during a regulatory review, a broader definition of adverse events of special interest (broad-definition AESIs) (fever and ≥1 AESI symptom within 30 days post-vaccination) was evaluated post hoc. Results: The most frequently reported solicited systemic events post-VLA1553 included fever (13.5%), arthralgia (17.2%), myalgia (23.9%), fatigue (28.5%), and headache (31.6%), with very few prolonged symptoms. The incidence of unsolicited arthralgia-related events (arthritis, osteoarthritis, musculoskeletal stiffness, joint stiffness, and joint swelling) was comparable between VLA1553 and placebo groups. Broad-definition AESIs were observed in 11.7% (361/3082) participants (VLA1553) and 0.6% (6/1033) participants (placebo), with a duration of 1–182 days (median: 4 days; prolonged broad-definition AESI [≥1 symptom lasting ≥ 30 days] occurred in 0.5% of participants) (VLA1553) and 4–27 days (median: 8 days) (placebo). Most symptoms contributing to broad-definition AESIs were solicited. In the VLA1553 group, the most common of these symptoms, in addition to fever, were headache (9.1% of participants), fatigue (8.6%), myalgia (7.0%), and arthralgia (5.2%). There were few severe cases (1.6% of participants in the VLA1553 group). Conclusions: In clinical trials, VLA1553 showed an acceptable safety profile that was consistent with other live-attenuated vaccines. The incidence of broad-definition AESIs was mainly limited to the immediate post-vaccination period, and broad-definition AESI symptoms were mostly solicited systemic adverse events. Full article

Background: pGX9501 is a prophylactic DNA vaccine encoding the spike protein of SARS-CoV-2 and can induce immune response in the human body so as to prevent COVID-19. With respect to non-clinical studies, pGX9501 has been demonstrated to induce both cellular and humoral immune responses in various animal models. It was found that the level of antibody titers following a two-dose regimen was higher than that following a single-dose regimen in nonhuman primate challenge model. Methods: In China, a phase I, randomized, double-blind, placebo-controlled clinical trial has been conducted in Huashan Hospital, Shanghai, China to evaluate the safety, tolerability, and immunogenicity of DNA vaccine pGX9501 administered intradermally (ID) followed by electroporation (EP) in 45 Chinese healthy volunteers aged 18 to 59 years old. Results: No adverse events of special interest (AESIs), death, or treatment-related SAEs occurred in this study. All the treatment-related (vaccine or EP) adverse events (TRAEs) were of grade 1 and 2 in severity. The solicited AEs were reported in thirty-two (32/36, 88.9%) and nine (9/9, 100.0%) subjects, respectively, in the DNA vaccine and placebo group. The frequency of solicited AEs did not increase with vaccine dose level and frequency. The DNA vaccine pGX9501 effectively enhanced both humoral and cellular immune responses in a dose-dependent manner, with increased antibody GMTs and peak seroconversion rates observed on day 42. The significant rise in IFN-γ levels confirmed the vaccine’s ability to induce cellular immune responses. Variations in the microbiome structure suggested a tangible impact of the gut microbiota on vaccine immunogenicity. Conclusions: The findings from this study confirm the immunogenicity and safety of the DNA vaccine pGX9501 and point to the potential role of the gut microbiota in vaccine immune responses. These insights provide practical references for the future design and development of DNA vaccines. Full article

Background/Objectives: Significant weight loss, whether through bariatric surgery or medication-assisted approaches, presents unique challenges for body contouring procedures. A thorough preoperative evaluation is essential to optimize outcomes and minimize risks. Methods: A comprehensive literature search was conducted across various databases to identify studies on assessment, nutritional optimization, thromboembolic risk, and surgical planning for post-weight-loss patients, with a particular focus on those undergoing medication-assisted weight loss using Glucagon-like peptide-1 (GLP-1) agonists. Results: A detailed review of medical history, comorbidities, weight loss trajectory, and nutritional status is essential. Common conditions such as diabetes, hypertension, and sleep apnea often improve after weight loss but require ongoing management. Nutritional deficiencies, particularly in vitamins and minerals, necessitate dietary counseling and supplementation. Patients who have undergone significant weight loss are at increased risk of thromboembolic events, particularly after body contouring procedures. Surgical planning should be patient-centered, setting realistic expectations and employing a strategic, staged approach when necessary to optimize outcomes. GLP-1 agonists users require special consideration due to their distinct metabolic and physiological profiles. Conclusions: Optimizing preoperative assessment, nutrition, and thromboprophylaxis is critical for safe and effective body contouring in post-weight-loss patients. With the increasing prevalence of medication-assisted weight loss, surgical strategies must adapt to address the distinct anatomical and physiological features of these patients. Full article

Empirical studies have suggested that travelers’ risk attitudes affect their choice behavior when travel conditions are stochastic. By considering the travelers’ risk attitudes, we extend the classical two-route model, in which road capacities vary due to such shocks as bad weather, accidents, and special events. Two information regimes have been investigated. In the zero-information regime, we postulate that travelers acquire the variability in route travel time based on past experiences and choose the route to minimize the travel time budget. In the full-information regime, travelers have pre-trip information of the road capacities and thus choose the route to minimize the travel time. User equilibrium states of the two regimes have been analyzed, based on the canonical BPR travel time function with power coefficient $p$. In the special case $p=1$, the closed form solutions have been derived. Three cases and eleven subcases have been classified concerning the dependence of expected total travel times on the risk attitude in the zero-information regime. In the general condition $p>0$, although we are not able to derive the closed form solutions, we proved that the results are qualitatively unchanged. We have studied the benefit gains/losses by shifting from the zero-information to the full-information regime. The circumstance under which pre-trip information is beneficial has been identified. A numerical analysis is conducted to further illustrate the theoretical findings. Full article

Damage assessment methods fall into contact and non-contact approaches. Contact methods, like physical measurements, material sampling, and ultrasonic testing, provide detailed data but are time-consuming and require specialized equipment. In contrast, non-contact methods assess damage remotely, allowing for faster, safer, and large-scale evaluations, especially useful in post-disaster scenarios. However, there are currently no standardized non-contact methods for assessing damage levels in confined masonry walls after damaging seismic events in Peru. On the other hand, an experimental database of cyclic loading tests on confined masonry walls is available, supporting numerical simulations with calibrated mathematical models to estimate damage levels. This research extends the application of this database by analyzing the crack pattern imagery from the tested walls and correlating it with the lateral deformation (drift) to identify the damage levels. A high-accuracy crack measurement technique was developed, combining a convolutional neural network to generate a binary crack mask and a binary search algorithm to extract polylines and convert them into length measurements, achieving a detection accuracy of 78%. The measured crack patterns were normalized into an index, which was then correlated with the amplitude of the lateral deformation in each hysteretic loop. Finally, a relationship was established between drift and the damage level index. These findings contribute to the development of a rapid, non-contact damage assessment method for confined masonry walls in seismic-prone regions. Full article

Background: Long-term clinical trials and real-world data have established a comprehensive risk–benefit profile for ibrutinib, informing adverse event (AE) management strategies to optimize safety and efficacy. Methods: We retrospectively assessed the incidence of AEs of special interest and management strategies in all patients treated with ibrutinib for chronic lymphocytic leukemia (CLL) in Saskatchewan, Canada, since 2014. Results: Among 187 patients (median age 75.7 years, 63% male), the median time from ibrutinib treatment initiation to data cutoff was 3.1 years. Approximately two-thirds of patients received ibrutinib for relapsed CLL (33.7% second-line and 32.6% third-line and beyond), with 33.7% receiving it first-line. All patients initiated ibrutinib as monotherapy at 420 mg. AEs of interest were observed in 81.3% of patients, with 42.8% experiencing ≥2 AEs. No grade 5 AEs were reported. Among the 284 first-onset AEs observed in 152 patients, 90.8% were successfully managed, allowing treatment continuation. The median time to successful management ranged from 27.0 days (range: 12.5–73.0) for infections to 84.0 days (range: 55.0–141.0) for hypertension. Both AE and discontinuation rates were comparable or favourable to previous reports. Conclusion: This real-world analysis suggests that ibrutinib may be safely used in the majority of CLL patients encountered in routine practice. Full article

Yellow fever is a viral disease with historical importance since epidemics caused thousands of deaths at the end of the 19th century in Argentina. That event was associated with the presence of Aedes aegypti. After the mosquito eradication in South America in the 1960–1970 decade, no epidemic was detected related to this species but epizootics have occurred due to sylvatic vectors belonging to Haemagogus and Sabethes genera. Due to the recolonization of Ae. aegypti and its expanded distribution, the risk of the urbanization of yellow fever has increased over time. However, the reasons why the urban cycle of the yellow fever virus (YFV) has not occurred in South America so far are unknown. We explore the vector competence of Ae. aegypti for YFV transmission. The mosquitos evaluated belonged to colonies from center and northwest cities from Argentina, taking into account the particular genetic features of this mosquito species detected in this country from 2016. We used a viral strain originally isolated in 2009 from Sabethes albiprivus in the country. Viral infection in mosquito body, legs, and saliva was evaluated to estimate the rates of infection, dissemination, and transmission. Our results indicate that both mosquito colonies are competent vectors in the transmission of the YFV but with differences between them. Regarding the infection timeline, we observed a very early infection in the La Plata colony at 3 DPI in contrast to previous studies. This research improves our understanding of the risks of urban YFV transmission in Argentina, highlighting the need for surveillance and specialized vector control strategies in urban settings to prevent yellow fever outbreaks. Full article

A novel temporally resolved settle-plate air sampler was developed using 3D printing technology to improve upon traditional passive air sampling methods. Conventional settle plates provide cumulative measurements of particle or microbial loads over an entire sampling period, lacking the temporal resolution necessary to identify specific contamination events. The described device integrates a petri plate within a 3D-printed housing featuring a narrow slit that exposes only a small portion of the plate to incoming particles. A rotary mechanism, driven by a mechanical clock motor, rotates the petri plate over 12 h, allowing for time-segmented sampling. Validation experiments demonstrated the device’s ability to accurately encode the temporal history of particle deposition using both aerosolized dyes and viable microbial spores. The device effectively correlated bioaerosol deposition with ambient wind conditions during outdoor sampling. The system is inexpensive (under USD 10), requires no specialized skills to assemble, and is compatible with existing settle plate methodologies. This innovation enhances the ability to conduct air quality assessments in critical environments, enabling data-driven decisions to mitigate contamination risks. Full article

Traffic counts are essential for assessing road capacity to provide efficient, effective, and safe mobility. However, current methods for generating models for traffic count studies are often limited in their accuracy and applicability, which can lead to incorrect or imprecise estimates of traffic volume. This study focused on analyzing and predicting traffic conditions on Ikorodu Road in Lagos State. The analysis involved an examination of historical traffic data, specifically focusing on daily and hourly traffic volumes. The prediction involved the use of machine learning models, including decision trees, gradient boosting, and random forest classifiers. The results of this study revealed significant variations in traffic volume across different days of the week and times of the day, indicating peak and off-peak periods. The study also highlighted the need for a more comprehensive approach that includes additional factors, such as weather conditions, road work, and special events, which could significantly impact traffic volume. Full article

In recent years, accelerated global climate change has precipitated an increased frequency of wildfire events, with their devastating impacts on ecological systems and human populations becoming increasingly significant. Satellite remote sensing technology, leveraging its extensive spatial coverage and real-time monitoring capabilities, has emerged as a pivotal approach for wildfire early warning and comprehensive disaster assessment. To effectively detect subtle smoke signatures while minimizing background interference in remote sensing imagery, this paper introduces a novel dual-branch attention framework (CSFAttention) that synergistically integrates channel–spatial refinement with frequency spectral analysis to aggregate smoke features in remote sensing images. The channel–spatial branch implements an innovative triple-pooling strategy (incorporating average, maximum, and standard deviation pooling) across both channel and spatial dimensions to generate complementary descriptors that enhance distinct statistical properties of smoke representations. Concurrently, the frequency branch explicitly enhances high-frequency edge patterns, which are critical for distinguishing subtle textural variations characteristic of smoke plumes. The outputs from these complementary branches are fused through element-wise summation, yielding a refined feature representation that optimizes channel dependencies, spatial saliency, and spectral discriminability. The CSFAttention module is strategically integrated into the bottleneck structures of the ResNet architecture, forming a specialized deep network specifically designed for robust smoke recognition. Experimental validation on the USTC_SmokeRS dataset demonstrates that the proposed CSFResNet achieves recognition accuracy of 96.84%, surpassing existing deep networks for RS smoke recognition. Full article

Accurate energy consumption forecasting is essential for efficient power grid management, yet existing deep learning models struggle with the multi-scale nature of energy consumption patterns. Contemporary approaches like LSTM and GRU networks process raw time series directly, failing to distinguish between distinct frequency components that represent different physical phenomena in household energy usage. This study presents a novel methodological method that systematically decomposes energy consumption signals into low-frequency components representing gradual trends and daily routines and high-frequency components capturing transient events, such as appliance switching, before applying predictive modeling. Our approach employs computationally efficient convolution-based filters—uniform and binomial—with varying window sizes to separate these components for specialized processing. Experiments on two real-world datasets at different temporal resolutions (1 min and 15 min) demonstrate significant improvements over state-of-the-art methods. For the Smart House dataset, our optimal configuration achieved an R² of 0.997 and RMSE of 0.034, substantially outperforming previous models with R² values of 0.863. Similarly, for the Mexican Household dataset, our approach yielded an R² of 0.994 and RMSE of 13.278, compared to previous RMSE values exceeding 82.488. These findings establish frequency decomposition as a crucial preprocessing step for energy forecasting as it significantly improve the prediction in smart grid applications. Full article

Alternative splicing enables a single precursor mRNA to generate multiple mRNA isoforms, leading to protein variants with different structures and functions. Abnormal alternative splicing is frequently associated with cancer development and progression. Recent studies have revealed a complex and dynamic interplay between epigenetic modifications and alternative splicing. On the one hand, dysregulated epigenetic changes can alter splicing patterns; on the other hand, splicing events can influence epigenetic landscapes. The reversibility of epigenetic modifications makes epigenetic drugs, both approved and investigational, attractive therapeutic options. This review provides a comprehensive overview of the bidirectional relationship between epigenetic regulation and alternative splicing in cancer. It also highlights emerging therapeutic approaches aimed at correcting splicing abnormalities, with a special focus on drug-based strategies. These include epigenetic inhibitors, antisense oligonucleotides (ASOs), small-molecule compounds, CRISPR–Cas9 genome editing, and the SMaRT (splice-switching molecule) technology. By integrating recent advances in research and therapeutic strategies, this review provides novel insights into the molecular mechanisms of cancer and supports the development of more precise and effective therapies targeting aberrant splicing. Full article

Advances in surgical and medical management of congenital heart disease have improved survival rates, leading to a growing population of adult congenital heart disease (ACHD) patients requiring specialized perioperative care. Studies indicate that ACHD patients undergoing non-cardiac surgery (NC surgery) have increased mortality and morbidity risks compared to the general population, with complication rates particularly high in those with complex defects, such as Fontan circulation, Eisenmenger syndrome, or cyanotic congenital heart disease. Key perioperative concerns include hemodynamic instability, arrhythmias, thromboembolic events, and bleeding risks. Additionally, comorbidities, such as frailty, chronic inflammation, or respiratory disease, further complicate perioperative management. Multidisciplinary collaboration is critical, involving cardiologists, anesthesiologists, and surgeons to optimize preoperative preparation and perioperative monitoring. Preoperative risk stratification is essential, integrating congenital heart lesion complexity, functional status, and procedural risk. This review underscores the importance of structured preoperative assessment, appropriate risk evaluation, and individualized perioperative strategies to improve surgical outcomes in ACHD patients undergoing NC surgery. Further research is needed to refine risk prediction models and optimize perioperative protocols tailored to this unique patient population. Full article

Aurora is caused by the collision of high-energy particles with particles in the Earth’s atmosphere. Recent advances in synthetic aperture radar (SAR) have demonstrated significant potential for ionospheric inversion at various scales, offering new insights into auroral processes. In this study, we present the first reported perturbation of C-band SAR signals induced by auroral activity during the enormous geomagnetic storm of 11 May 2024. The auroral boundaries observed by the Special Sensor Ultraviolet Spectrographic Imager (SSUSI) align closely with Sentinel-1 interferograms, despite the event occurring at mid-latitudes. A novel application of Sentinel-1 is illustrated, namely the inversion of the two-dimensional morphology and boundaries of the aurora at very high resolution and without interference from severe weather. Sentinel-1 promises to become a new method for the detection of precipitation particles, despite operating in the C-band, which is less disturbed by the ionosphere. Interferograms can also capture small-scale sporadic plasma patches associated with aurora. Furthermore, the analysis indicates that distinct polarization channels exhibit varying sensitivity towards auroral boundaries, with cross-polarization displaying heightened responsiveness. Full article

Service learning across medical schools is non-standardized and the skills that they learn can vary. Project HEART, a volunteer-based outreach program focused on teaching cardiovascular health and cardiopulmonary resuscitation (CPR) at public high schools, was implemented to encourage greater community engagement and equilibrate skill acquisition across different service projects. This pilot study characterized the benefits of providing service learning opportunities to first-year medical students. First-year medical students at a single institution were recruited to Project HEART. Following service sessions, all students completed a retrospective pre/post survey. They provided self-reported scores on a five-point Likert-type scale, grading their didactic and communication skills before and after the event. Subjective feelings of community engagement were also queried. Overall, 30 students were recruited across nine different community programs. Following participation, significantly increased confidence was seen in performing hands-only CPR (p < 0.001), public speaking (p = 0.003), teaching effectively (p < 0.001), and explaining medical terminology to laypersons (p < 0.001). Volunteers had an increased sense of community engagement (p < 0.001) and 17/30 students expressed greater consideration towards specializing in cardiology, primary care, or entering academia after participation. The study supported the proposal that service learning may promote self-determined altruism, positively influence perceptions of community stewardship, and have positive subjective benefits on medical student education. Full article