Search Results (117)

Lipid nanoparticles are a clinically validated platform for delivering nucleic acids, but performance is constrained by multiscale physiological barriers spanning circulation, vascular interfaces, extracellular matrices, cellular uptake, and intracellular trafficking. This review links composition–structure–function relationships for ionizable lipids, helper phospholipids, cholesterol, and PEG-lipids to systemic fate, endothelial access, endosomal escape, cytoplasmic stability, and nuclear transport. We outline strategies for tissue and cell targeting, including hepatocyte ligands, immune and tumor selectivity, and selective organ targeting through compositional tuning, together with approaches that modulate escape using pH-responsive chemistries or fusion-active peptides and polymers. We further examine immunomodulatory co-formulation, route and schedule effects on biodistribution and immune programming, and manufacturing and stability levers from microfluidic mixing to lyophilization. Across these themes, we weigh trade-offs between stealth and engagement, potency and tolerability, and potency and manufacturability, noting that only a small fraction of endosomes supports productive release and that protein corona variability and repeat dosing can reshape tropism and clearance. Convergence of standardized assays for true cytosolic delivery, biomarker-guided patient selection, and robust process controls will be required to extend LNP therapeutics beyond the liver while sustaining safety, access, and scale. Full article

Hepatitis B virus (HBV) remains a major global health concern, as it is not only one of the most common hepatotropic viruses but also ranks as the seventh leading cause of mortality worldwide. The most significant routes of infection include vertical transmission (from mother to child before, during, or after birth, including transplacental infection) and horizontal transmission in early childhood through close household contact with infected parents. The aim of our study was to assess the prevalence of chronic and occult hepatitis B virus infection among pregnant women in St. Petersburg (Russia), including molecular characterization. We analyzed plasma samples from 1368 local pregnant women. ELISA screening for HBV markers included qualitative detection of HBsAg, anti-HBs IgG, and anti-HBcore IgG. HBV DNA was identified using highly sensitive nested PCR, followed by whole-genome sequencing for HBV DNA-positive cases. Our study evaluated the prevalence of serological and molecular HBV markers and their association with age, vaccination status, and number of pregnancies. Serological markers HBsAg, anti-HBs IgG, and anti-HBcore IgG were detected in 1.9%, 63.8%, and 12.9% of participants, respectively. HBV DNA was found in 4.7% of pregnant women, including 2.8% with occult HBV infection (OBI). We observed a positive correlation between anti-HBcore IgG and age, but an inverse correlation with anti-HBs IgG; an inverse correlation between anti-HBcore IgG and vaccination status, while anti-HBs IgG showed a positive correlation; and a positive correlation between HBsAg, anti-HBcore IgG, and HBV DNA with the number of pregnancies. We also analyzed the prevalence of clinically significant mutations, including drug resistance mutations, escape mutations (affecting diagnostic detection and vaccine efficacy), and mutations associated with disease progression. The detection of HBsAg-negative HBV infection was linked to circulating viral variants carrying escape mutations, which evade HBsAg detection in diagnostic assays and neutralization by vaccine-induced antibodies. The predominance of HBV isolates in pregnant women harboring dual-threat mutations (those causing diagnostic failure via HBsAg negativity, reduced vaccine/immunoglobulin efficacy, viral reactivation, disease progression) poses a significant public health risk and warrants further investigation. Full article

Monkeypox virus (MPXV) experienced an unprecedented global outbreak in 2022, characterized by a significant departure from historical patterns: a rapid spread of the epidemic to more than 110 non-traditional endemic countries, with more than 90,000 confirmed cases; a fundamental shift in the mode of transmission, with human-to-human transmission (especially among men who have sex with men (MSM)) becoming the dominant route (95.2%); and genetic sequencing revealing a key adaptive mutation in a novel evolutionary branch (Clade IIb) that triggered the outbreak. These features highlight the significant evolution of MPXV in terms of host adaptation, transmission efficiency, and immune escape ability. The aim of this paper is to provide insights into the viral adaptive evolutionary mechanisms driving this global outbreak, with a particular focus on the role of immune escape (e.g., novel mechanisms of M2 proteins targeting the T cell co-stimulatory pathway) in enhancing viral transmission and pathogenicity. At the same time, we systematically evaluate the cross-protective efficacy and limitations of existing vaccines (ACAM2000, JYNNEOS, and LC16), as well as recent advances in novel vaccine platforms, especially mRNA vaccines, in inducing superior immune responses. The study further reveals the constraints to outbreak control posed by grossly unequal global vaccine distribution (e.g., less than 10% coverage in high-burden regions such as Africa) and explores the urgency of optimizing stratified vaccination strategies and facilitating technology transfer to promote equitable access. The core of this paper is to elucidate the dynamic game between viral evolution and prevention and control strategies (especially vaccines). The key to addressing the long-term epidemiological challenges of MPXV in the future lies in continuously strengthening global surveillance of viral evolution (early warning of highly transmissible/pathogenic variants), accelerating the development of next-generation vaccines based on new mechanisms and platforms (e.g., multivalent mRNAs), and resolving the vaccine accessibility gap through global collaboration to build an integrated defense system of “Surveillance, Research and Development, and Equitable Vaccination,” through global collaboration to address the vaccine accessibility gap. Full article

Human induced pluripotent stem cells (iPSCs) offer immense potential as a source for cell therapy in spinal cord injury (SCI) and other diseases. The development of hypoimmunogenic, universal cells that could be transplanted to any recipient without requiring a matching donor could significantly enhance their therapeutic potential and accelerate clinical translation. To create off-the-shelf hypoimmunogenic cells, we used CRISPR-Cas9 to delete B2M (HLA class I) and CIITA (master regulator of HLA class II). Double-knockout (DKO) iPSC-derived neural progenitor cells (NPCs) evaded T-cell-mediated immune rejection in vitro and after grafting into the injured spinal cord of athymic rats and humanized mice. However, loss of HLA class I heightened susceptibility to host natural killer (NK) cell attack, limiting graft survival. To counter this negative effect, we engineered DKO NPCs to overexpress macrophage migration inhibitory factor (MIF), an NK cell checkpoint ligand. MIF expression markedly reduced NK cell-mediated cytotoxicity and improved long-term engraftment and integration of NPCs in the animal models for spinal cord injury. These findings demonstrate that MIF overexpression, combined with concurrent B2M and CIITA deletion, generates hiPSC neural derivatives that escape both T- and NK-cell surveillance. This strategy provides a scalable route to universal donor cells for regenerative therapies in SCI and potentially other disorders. Full article

Public health crises triggered by viral infections pose severe threats to individual health and disrupt global socioeconomic systems. Against the backdrop of global pandemics caused by highly infectious diseases such as COVID-19 and Ebola virus disease (EVD), the development of innovative prevention and treatment strategies has become a strategic priority in the field of biomedicine. Neutralizing antibodies, as biological agents, are increasingly recognized for their potential in infectious disease control. Among these, nanobodies (Nbs) derived from camelid heavy-chain antibodies exhibit remarkable technical advantages due to their unique structural features. Compared to traditional neutralizing antibodies, nanobodies offer significant cost-effectiveness in production and enable versatile administration routes (e.g., subcutaneous injection, oral delivery, or aerosol inhalation), making them particularly suitable for respiratory infection control and resource-limited settings. Furthermore, engineered modification strategies—including multivalent constructs, multi-epitope recognition designs, and fragment crystallizable (Fc) domain fusion—effectively enhance their neutralizing activity and suppress viral immune escape mechanisms. Breakthroughs have been achieved in combating pathogens such as the Ebola virus and SARS-CoV-2, with mechanisms involving the blockade of virus–host interactions, induction of viral particle disintegration, and enhancement of immune responses. This review comprehensively discusses the structural characteristics, high-throughput screening technologies, and engineering strategies of nanobodies, providing theoretical foundations for the development of novel antiviral therapeutics. These advances hold strategic significance for addressing emerging and re-emerging infectious diseases. Full article

Architectural design seeks to address many challenges, one of which is creating buildings that can quickly and safely evacuate people. Therefore, it is even more important to pay attention to the safety of personnel evacuation. Past disasters have shown that the number of casualties in large sports stadiums can be as severe as those caused by plane crashes. This study uses a case study approach to analyze the evacuation of spectators in a 40,000-seat stadium, comparing the practical application of three performance verification methods. The results indicate that Simulex’s visual dynamic simulation effectively reflects how walking speeds decrease in crowded conditions and how bottlenecks form along evacuation routes. People tend to gather at corners, leading to congestion and uneven distribution of evacuees, with several escape staircases being underutilized. The Guide to Safety at Sports Grounds is suitable for the early planning stages of architectural design, while the “Verification Guideline of Buildings Evacuation Safety Performance-based Design” is better suited for the detailed design phase to ensure compliance with the safety standard of evacuating spectators within 8 min. Compared to planning and designing based solely on regulations or empirical verification formulas, using visualization software allows for effective adjustments to evacuation routes before finalizing the design, balancing crowd flow across all safety exits and improving evacuation efficiency during the operational phase. Full article

The Quantum Snowflake Algorithm (QSA) is a novel metaheuristic for both continuous and discrete optimization problems, combining collision-based diversity, quantum-inspired tunneling, superposition-based partial solution sharing, and local refinement steps. The QSA embeds candidate solutions in a continuous auxiliary space, where collision operators ensure that agents—snowflakes—reject each other and remain diverse. This approach is inspired by snowflakes which prevent collisions while retaining unique crystalline patterns. Large leaps to escape deep local minima are simultaneously provided by quantum tunneling, which is particularly useful in highly multimodal environments. Tests on challenging functions like Lévy and HyperSphere showed that the QSA can more reliably obtain very low objective values in continuous domains than conventional swarm or evolutionary approaches. A 200-city Traveling Salesman Problem (TSP) confirmed the excellent tour quality of the QSA for discrete optimization. It drastically reduces the route length compared to Artificial Bee Colony (ABC), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Quantum Particle Swarm Optimization (QPSO), and Cuckoo Search (CS). These results show that quantum tunneling accelerates escape from local traps, superposition and local search increase exploitation, and collision-based repulsion maintains population diversity. Together, these elements provide a well-rounded search method that is easy to adapt to different problem areas. In order to establish the QSA as a versatile solution framework for a range of large-scale optimization challenges, future research could investigate multi-objective extensions, adaptive parameter control, and more domain-specific hybridisations. Full article

Venous hypertension in the pelvic veins can result in the development of varicosities in the perineum, and sometimes also in the lower extremities. These varicose veins are anatomically and functionally different from typical varicosities associated with an incompetence of the saphenous veins. Since the pelvic cavity is anatomically separated from the lower extremity and perineum by muscles and skeleton, there are only a few routes through which pelvic veins can communicate with extra-pelvic veins. These routes should primarily be examined during diagnostic workout. In this review article, clinical anatomy concerning varicose veins of pelvic origin is presented, and the anatomically-driven diagnostics for these atypical varicose veins are discussed. Focus on ultrasonographic detection of the escape points, which are located at the sites where the incompetent intra-pelvic and extra-pelvic veins are connected—such as the perineal veins, veins running alongside the round ligament of the uterus, the obturator vein, as well as the inferior and superior gluteal veins—is emphasized. Full article

On the occasion of building fires, the risk of smoke, which adversely influences escape conditions, must be minimised. One way to reduce the risk is, for example, to pressurise the escape route in order to limit the infiltration of smoke. Careful determination of the design parameters of the pressurisation system is of great importance. This study will propose a new leakage area for single-leaf smoke control doors based on the analysis of the leakage area of the doors in the EN 12101-13 standard, estimating the leakage rate through closed doors. This value is half the currently recommended value, regardless of the opening direction. The determination of the leakage area is supported by measurements in pressurised smoke-free lobbies with single-leaf smoke control doors opening into and outwards from a pressurised space. The measurements are performed using the fans of the lobbies’ pressurisation systems to provide the required air volume. The suitability of this method has also been tested using blower door assembly measurements. The newly proposed leakage area takes into account the increased air tightness of the smoke control doors, thereby ensuring that the optimum air volume to be supplied by the pressurisation system can be determined. The results of this research suggest an appropriate leakage area value for designers when using the calculation method proposed by the applicability of the investigated standard. Full article

Wildfires are affecting natural ecosystems worldwide, causing economic and human losses and exacerbated by climate change. Models of fire severity and fire susceptibility are crucial tools for fire monitoring. This case study analyses a fire event on 3 September 2019 in Vilcabamba parish, Loja province, Ecuador. This article aims to assess the severity and susceptibility of a fire through spectral indices and multi-criteria methods for establishing a fire action plan proposal. The methodology comprises the following: (i) the acquisition of Sentinel-2A products for the calculation of spectral indices; (ii) a fire severity model using differentiated indices (dNBR and dNDVI) and a fire susceptibility model using the Analytic Hierarchy Process (AHP) method; (iii) model validation using Logistic Regression (LR) and Non-metric Multidimensional Scaling (NMDS) algorithms; (iv) the proposal of an action plan for fire management. The Normalised Burn Ratio (NBR) index revealed that 10.98% of the fire perimeter has burned areas with moderate-high severity in post-fire scenes (2019) and decreased to 0.01% for post-fire scenes in 2021. The Normalised Difference Vegetation Index (NDVI) identified 67.28% of the fire perimeter with null photosynthetic activity in the post-fire scene (2019) and 5.88% in the post-fire scene (2021). The Normalised Difference Moisture Index (NDMI) applied in the pre-fire scene identified that 52.62% has low and dry vegetation (northeast), and 8.27% has high vegetation cover (southwest). The dNDVI identified 10.11% of unburned areas and 7.91% using the dNBR. The fire susceptibility model identified 11.44% of the fire perimeter with null fire susceptibility. These results evidence the vegetation recovery after two years of the fire event. The models demonstrated excellent performance for fire severity models and were a good fit for the AHP model. We used the Root Mean Square Error (RMSE) and area under the curve (AUC); dNBR and dNDVI have an RMSE of 0.006, and the AHP model has an RMSE of 0.032. The AUC = 1.0 for fire severity models and AUC = 0.6 for fire susceptibility. This study represents a holistic approach by combining Google Earth Engine (GEE), Geographic Information System (GIS), and remote sensing tools for proposing a fire action plan that supports decision making. This study provides escape routes that considered the most significant fire triggers, the AHP, and fire severity approaches for monitoring wildfires in Andean regions. Full article

Background: Escape routes are important measures for firefighters to ensure their own safety, providing predetermined paths to safe areas. Their establishment needs to consider numerous factors, such as the timeliness and safety of the routes. Aims: Optimize the path planning method previously studied by our team to ensure the dynamic nature, timeliness, and safety of the routes. Methods: (1) Propose a comprehensive safety index that encompasses both spatial and temporal safety indices, providing a more holistic approach to route safety. (2) Introduce spatial adaptive factors and spatial safety windows corresponding to the spatial safety index within the comprehensive safety index. (3) Present a new concept, the “observation cycle”, as a standard for the frequency of updating wildfire spread information, thereby addressing the issue of a lack of real-time input information. Based on this, we propose a reliable dynamic update rule for its updating. Results: Compared to the unoptimized model, the final optimized model’s planned escape routes offer impressive dynamic performance, effectively guarding against sudden changes in wildfire conditions, enhancing route safety, and ensuring timeliness. Conclusions: This research ensures that firefighters can effectively guard against the threats posed by sudden changes in wildfire conditions when escaping in wildfire environments, while also guaranteeing timeliness and safety. Full article

Tumor growth and progression require molecular interactions between malignant and host cells. In recent years, extracellular vesicles (EVs) emerged as an important pillar of such interactions, carrying molecular information from their donor cells to distant recipient cells. Thereby, the phenotype and function of the recipient cells are altered, which may facilitate tumor immune escape and tumor metastasis to other organs through the formation of pre-metastatic niches. A prerequisite for these effects of tumor cell-derived EVs is an efficient transport system from the site of origin to the body periphery. Here, we highlight the role of the lymphatic vascular system in the distribution and progression-promoting functions of tumor cell-derived EVs. Importantly, the lymphatic vascular system is the primary drainage system for interstitial fluid and its soluble, particulate, and cellular contents, and therefore represents the principal route for regional (i.e., to tumor-draining lymph nodes) and systemic distribution of EVs derived from solid tumors. Furthermore, recent studies highlighted the tumor-draining lymph node as a crucial site where tumor-derived EVs exert their effects. A deeper mechanistic understanding of how EVs gain access to the lymphatic vasculature, how they interact with their recipient cells in tumor-draining lymph nodes and beyond, and how they induce phenotypic and functional maladaptation will be instrumental to identify new molecular targets and conceive innovative approaches for cancer therapy. Full article

The advancement of Arrival MANager (AMAN) is crucial for addressing the increasing complexity and demand of modern airspace. This study evaluates the operational feasibility and effectiveness of an innovative AMAN designed for en route airspace, the so-called En Route AMAN. The En Route AMAN functions as a controller support system, facilitating the sharing of information between en route air traffic controllers (ATCos), approach controllers (current AMAN), and airport controllers (Departure Managers) in airports with multiple runways. The En Route AMAN aims to support upstream ATCos by sequencing and spacing of incoming streams via speed control and runway assignment, thereby enhancing overall air traffic efficiency. Human-In-The-Loop simulations involving rated ATCos are performed under scenarios that replicate real-world traffic and weather conditions. These simulations focus on upstream airspace to assess the impact of En Route AMAN on delay mitigation and ATCos’ performance. Unlike previous studies that solely relied on theoretical models and fast-time simulation for operational feasibility evaluation, this approach incorporates ATCos’ real-time decision-making, situational awareness, and task management, addressing critical operationalization challenges. The results demonstrated that the En Route AMAN could reduce the average flight duration by up to 25.6 s and decrease the total number of ATCo instructions by up to 20% during peak traffic volume. These findings support that the En Route AMAN is both operationally viable and effective in mitigating arrival delays, highlighting the importance of Human-In-The-Loop for practical validation. Full article

With the rapid advancement of drone technology, the efficient distribution of drones has garnered significant attention. Central to this discourse is the energy consumption of drones, a critical metric for assessing energy-efficient distribution strategies. Accordingly, this study delves into the energy consumption factors affecting drone distribution. A primary challenge in drone distribution lies in devising optimal, energy-efficient routes for drones. However, traditional routing algorithms, predominantly heuristic-based, exhibit certain limitations. These algorithms often rely on heuristic rules and expert knowledge, which can constrain their ability to escape local optima. Motivated by these shortcomings, we propose a novel multi-agent deep reinforcement learning algorithm that integrates a drone energy consumption model, namely EMADRL. The EMADRL algorithm first formulates the drone routing problem within a multi-agent reinforcement learning framework. It subsequently designs a strategy network model comprising multiple agent networks, tailored to address the node adjacency and masking complexities typical of multi-depot vehicle routing problem. Training utilizes strategy gradient algorithms and attention mechanisms. Furthermore, local and sampling search strategies are introduced to enhance solution quality. Extensive experimentation demonstrates that EMADRL consistently achieves high-quality solutions swiftly. A comparative analysis against contemporary algorithms reveals EMADRL’s superior energy efficiency, with average energy savings of 5.96% and maximum savings reaching 12.45%. Thus, this approach offers a promising new avenue for optimizing energy consumption in last-mile distribution scenarios. Full article

Due to the lack of real-time planning for fire escape routes in large buildings, the current route planning methods fail to adequately consider factors related to the fire situation. This study introduces a real-time fire monitoring and dynamic path planning system based on an improved ant colony algorithm, comprising a hierarchical arrangement of upper and lower computing units. The lower unit employs an array of sensors to collect environmental data in real time, which is subsequently transmitted to an upper-level computer equipped with LabVIEW. Following a comprehensive data analysis, pertinent visualizations are presented. Capitalizing on the acquired fire situational awareness, a propagation model for fire spreading is developed. An enhanced ant colony algorithm is then deployed to calculate and plan escape routes by introducing a fire spread model to enhance the accuracy of escape route planning and incorporating the A* algorithm to improve the convergence speed of the ant colony algorithm. In response to potential anomalies in sensor data under elevated temperature conditions, a correction model for data integrity is proposed. The real-time depiction of escape routes is facilitated through the integration of LabVIEW2018 and MATLAB2023a, ensuring the dependability and safety of the path planning process. Empirical results demonstrate the system’s capability to perform real-time fire surveillance coupled with efficient escape route planning. When benchmarked against the traditional ant colony algorithm, the refined version exhibits expedited convergence, augmented real-time performance, and effectuates an average reduction of 17.1% in the length of the escape trajectory. Such advancements contribute significantly to enhancing evacuation efficiency and minimizing potential casualties. Full article