Search Results (151)

Oxidative stress plays a central role in the progression of inflammatory and degenerative diseases, highlighting the need for natural compounds with antioxidant and anti-inflammatory potential. This study investigated the biological activity of the dichloromethane extract of Maclura tinctoria leaves (DcMt), which was selected for further analyses after initial screening demonstrated superior antioxidant activity compared with the hexane extract (HxMt). Antioxidant capacity was evaluated by DPPH and FRAP assays, while cellular effects were assessed in RAW 264.7 macrophages through analyses of viability, cytokine gene expression, COX-2 modulation, catalase activity, and cell migration. LC-DAD-ESI-MS profiling revealed a well-defined chromatographic composition dominated by four major constituents, which were isolated and structurally elucidated by NMR and MS as prenylated flavonoids, several of which are reported here for the first time in M. tinctoria. DcMt exhibited strong antioxidant activity and preserved cell viability under oxidative stress, with optimal effects at 25 µg/mL, accompanied by increased catalase activity. The extract modulated inflammatory markers by increasing IL-10 and IL-6 gene expression, maintaining IL-1β levels, and regulating COX-2 expression. In addition, DcMt promoted macrophage migration, further supporting its potential role in modulating inflammatory responses. Importantly, all biological assays were performed using the crude extract, and the contribution of individual compounds remains to be further investigated. These findings support M. tinctoria as a promising source of bioactive compounds with antioxidant and immunomodulatory potential. Full article

In molten salt reactors (MSRs), molten salt performs dual essential roles as fuel and coolant. The continuous circulation of the fuel salt in the primary loop inevitably leads to significant neutron activation of loop components, particularly the structural alloys of the heat exchanger (HX) and the coolant salt within the HX. This activation is strongly influenced by delayed neutron fluxes generated by the migration of delayed neutron precursors (DNPs) within the flowing fuel salt. Accurate quantification of the radioactivity of primary HX components is essential for establishing reliable modular replacement strategies, optimizing shutdown maintenance schedules, and ensuring operational safety. To address this requirement, a comprehensive simulation methodology has been developed to model the DNP transport through the primary HX in a small modular molten salt reactor (SM-MSR). It aims to quantitatively evaluate activation levels of HX structural alloys and circulating coolant salt within the HX. Comparative simulations were conducted to contrast scenarios with dynamic DNP migration and static-fuel scenarios excluding it. The results indicate that consideration of DNP migration increases the neutron flux at the top region of the HX by approximately three orders of magnitude compared with the static-fuel scenario. This elevates coolant salt radioactivity by over 50%. Significant increases in irradiation damage parameters (displacements per atom and helium production) are observed in the upper sections of HX structural alloys. These findings highlight the necessity of incorporating DNP migration effects for accurate prediction of primary loop component neutron activation. This provides a reference for future shielding design optimization, irradiation damage assessments, and shutdown dose rate calculations in the SM-MSR. Full article

This study aims to develop and experimentally evaluate an artificial neural network-based temperature control strategy for hot-air carrot drying within an IoT-enabled cyber-physical system. The experimental setup employs an Arduino Mega 2560 equipped with AM2302 (air temperature sensor), MLX90614 (infrared surface temperature sensor), and SHT35 (relative humidity sensor), an HX711 load cell, and a WS68 anemometer, with cloud communication provided by an ESP8266 module for remote monitoring via Wi-Fi. The neural controller, implemented using the Arduino Neurona library, regulates the dryer temperature in real time, enabling drying kinetics analysis under ANN-based thermal control to investigate its capability to maintain thermal stability. Three initial loads (2, 4, and 6 kg) were analyzed to determine the thermal efficiency. In the dehydration experiments, the 2 kg load reached a final moisture content of 10% in 4.4 h, consuming 1390 kJ with a thermal efficiency of 83%. The 4 kg load exhibited the best time–energy balance (6.6 h, 1850.0 kJ, 88%), while the 6 kg load achieved the highest efficiency (8.1 h, 2250.0 kJ, 91%). These results demonstrate the effectiveness of neural-network-based control implemented on low-cost microcontrollers to enhance thermal efficiency in food dehydration processes. Full article

Background: Chronic kidney disease (CKD) is increasingly prevalent, leading to more patients requiring hemodialysis. Medium cut-off (MCO) membranes, such as the ELISIO™ HX dialyzer, may enhance middle-to-large molecule removal and reduce inflammation compared with conventional high-flux membranes. This study evaluated the efficacy and safety of ELISIO™ HX versus a standard high-flux dialyzer (Toraylight NS-21S) in terms of molecular reduction rate and inflammation. Methods: We performed a single-center, prospective, randomized crossover study with 12 hemodialysis patients, each treated with Toraylight NS-21S and ELISIO™ HX over four weeks. Pre- and post-dialysis levels of urea, creatinine, albumin, creatine kinase, phosphorus, parathyroid hormone, C-reactive protein (CRP), procalcitonin, interleukin 6 (IL-6), and β2-microglobulin were measured. Pre–post differences were assessed using dialyzer analysis, period-effect and carryover analysis, and non-inferiority analysis. Results: ELISIO™ HX was non-inferior to Toraylight NS-21S for creatinine, urea, phosphorus, procalcitonin, and β2-microglobulin. No significant serum albumin changes were observed with either dialyzer. Adverse events were infrequent and comparable between the dialyzers. Conclusions: ELISIO™ HX appears non-inferior to Toraylight NS-21S and suggests good safety and tolerability. These findings should be interpreted with caution given the study’s limited power. Full article

Globally, antibiotic resistance is a growing concern, motivating the search for alternatives. Bovine mastitis is an inflammatory disease of the udder caused by various microorganisms, many of which are resistant to various antibiotics, impacting the quality of dairy products and farmer income. In this study, the in vitro bioactivity of the methanol leaf extract, fractions (ethyl acetate (CeEtOAc), butanol (CeBuOH), hexane (CeHx), dichloromethane CeDCM), and water (CeAq), and a purified compound, quercetin-3-O-rhamnoside isolated from the CeEtOAc fraction of Combretum elaeagnoides Klotzsch, were investigated against six Staphylococcus aureus (S. aureus) strains isolated from clinical cases of bovine mastitis and two reference ATCC strains (S. aureus ATCC 29213 and S. epidermidis ATCC 35984). Methods used for assessing bioactivity included serial microdilution for antibacterial efficacy, crystal violet staining and p-iodonitrotetrazolium (INT) metabolic assays for anti-biofilm activity, and a microdilution assay for anti-quorum-sensing potential. The anti-inflammatory assays included 15-lipoxygenase enzyme inhibition and nitric oxide assays. Cytotoxicity screening was conducted using a tetrazolium-based colorimetric assay against bovine dermis cells. The extracts and fractions exhibited moderate to good antibacterial activity with minimum inhibitory concentration (MIC) values ranging from 0.07 to 1.04 mg/mL, with the ethyl acetate fraction being the most effective. The anti-biofilm activity of the extract, fractions, and isolated compound (quercetin-3-O-rhamnoside) varied at time zero (T0), with inhibition ranging from 3% to 100%. The CeDCM and CeEtOAc fractions exhibited the most potent anti-biofilm effects after 24 h, with inhibition ranging from 24% to 91%. The extracts and fractions exhibited significant inhibition (>50%) of biofilm within the incubation times (T0–T48), and quercetin-3-O-rhamnoside alone had >60% inhibition at 48 h. The CeEtOAc fraction had the most significant anti-quorum-sensing activity (IC₅₀ < 0.08 mg/mL). The methanol extract and fractions exhibited significant anti-inflammatory activity, inhibiting nitric oxide production (IC₅₀: 7–26 µg/mL). In contrast, the CeAq, CeHx, and CeDCM fractions showed the best inhibitory activity against the 15-lipoxygenase enzyme (IC₅₀ = 3–4 µg/mL). The extracts and fractions were non-cytotoxic to bovine dermis cells (LC₅₀ = 0.88–1 mg/mL). Combretum elaeagnoides extract and its fractions are recommended for further investigation as potential herbal treatments for the management of mastitis and its symptoms. Full article

The aviation industry aims to reduce environmental impact by adopting alternative propulsion systems, including hydrogen-based, hybrid-electric, and all-electric architectures, requiring a new Thermal Management System (TMS). In addition, new design methods are needed for the TMS, at the system and component levels, to handle various fluids and varying fluid properties. Within the TMS, heat exchangers are critical components that may require significant space and must be considered early in the design process. This paper presents a parametric sizing methodology for heat exchangers suitable for early design phases within a Multidisciplinary Design Analysis and Optimization (MDAO) framework, specifically for cryogenic heat transfer. The method combines physical equations with validated empirical relationships, using iterative solver algorithms for sizing. To address multi-variable design challenges, the methodology integrates discretization schemes for fluid properties, temperature, and energy calculations, and constraint-based optimization with a weighted-sum approach for solution selection. The methodology is validated with a commercial heat exchanger, and cross-validated with a cryogenic Heat Exchanger (HX). A case study for an all-electric hydrogen fuel cell aircraft architecture with a 7.6 MW propulsion system is presented to demonstrate the effectiveness of the methodology. The presented heat exchanger performance can be predicted across multiple conditions quickly enough to enable large design space exploration. Overall, the presented model is a crucial element for the design of a TMS for future aircraft with hydrogen-based propulsion systems. Full article

The valorization of agro-industrial waste could be a strategy to improve organic waste management. The production of activated carbon (AC) is a path to use for this waste, with the aim of reducing its negative effects. AC is characterized by a high internal surface area, chemical stability, and oxygen-containing functional groups in its structure. This work is focused on the valorization of agro-industrial waste such as pineapple peel and coconut shells. These are made up of sucrose, glucose, fructose, and other essential nutrients, as well as cellulose, hemicellulose, and lignin. Activated Carbon was obtained with slow pyrolysis at 400 °C, for 4 h in a stainless-steel tubular reactor with physical activation. The obtained samples were analyzed using SEM, TGA, FTIR, and BET to verify the morphology, thermal degradation, functional groups and pores ratio of the AC, highlighting the presence of materials pore >10 µm. The TGA residual materials gave 16.3% of pineapple peel AC ashes and 0.2% of coconut AC. A C=C, C-H_X, CO, and OH stretching were observed in 400–4000 cm⁻¹. The peak intensity decreased once the biodiesel was treated with AC, because the traces of water and functional groups interacted actively, resulting a high content of bases. Activated carbon was used for dry cleaning of the obtained biodiesel from residual oil, which was effective in reducing pH and moisture levels in the biodiesel samples. Pore distribution was determined by BET, 5.6 nm for pineapple peel and 39.8243 nm for coconut shells. The obtained activated carbon offers a sustainable alternative to traditional carbon sources and contributes to the circular economy by recycling waste biomass. Full article

To address the problem of wellbore instability in the development of deep coalbed methane reservoirs in Daniudi gas field, this study takes the coal seam cores from Member 1 of the Taiyuan Formation at a depth of approximately 2880 m as the research object. Through CT scanning, scanning electron microscopy (SEM), mineralogical analysis, laboratory mechanical tests, and drilling fluid interaction experiments, the study investigated the coal seam fabric characteristics, mechanical response, anisotropy, and the interaction between drilling fluids and the formation. Based on the double-weak-plane criterion, a wellbore collapse prediction model was established, and instability risk assessment under multi-factor coupling conditions was carried out. Experimental and computational results indicate that the deep coal seam exhibits significant heterogeneity in fabric structure, the clay minerals show low swelling potential, and the bright coal and semi-bright coal are prone to instability due to their dual pore structures. The average uniaxial compressive strength (UCS) of the coal cores is 16.3 MPa, which is weaker than that of the roof, floor, and dirt band. The coal also exhibits anisotropy, with the lowest strength occurring when the loading direction forms an angle of 30–60° with the weak planes, corresponding to 67.5% of the intrinsic compressive strength. Immersion in drilling fluid causes the coal rock strength to decay in a pattern of “rapid decline in the initial stage—gradual decrease in the middle stage—stabilization in the later stage.” After 24 h, the strength is only 55–65% of that in the dry state. Due to its excellent plugging and inhibition performance, HX-Coalmud drilling fluid delays strength loss more effectively than the strongly inhibitive composite salt drilling fluid. The wellbore instability risk assessment indicates that as the drilling time is extended, the collapse pressure rises significantly. After 7 and 20 days of contact between the wellbore and drilling fluid, the equivalent collapse pressure density increases by 0.08–0.15 g/cm³ and 0.13–0.20 g/cm³, respectively. Therefore, homogeneous isotropic models tend to underestimate the risk of wellbore collapse. The findings can provide theoretical and technical support for the safe drilling of deep coalbed methane in Daniudi gas field. Full article

Background/Objectives: Differentiated thyroid cancer (DTC) represents over 90% of all hyroid malignancies and typically has a favorable prognosis. However, approximately 30% of patients experience recurrence within 10 years after initial treatment. Conventional risk classification frameworks such as the American Thyroid Association (ATA) and AJCC TNM systems rely heavily on pathological interpretation, which may introduce observer variability and incomplete documentation. This study aimed to develop an interpretable machine-learning framework for risk stratification in DTC and to identify major clinical predictors using SHapley Additive exPlanations (SHAP). Methods: A retrospective dataset of 345 patients was obtained from the UCI Machine Learning Repository. Thirteen clinicopathological features were analyzed, including Age, Gender, T, N, M, Hx Radiotherapy, Focality, Adenopathy, Pathology, and Response. Statistical analysis and feature selection (ReliefF and mRMR) were applied to identify the most influential variables. Two modeling scenarios were tested using an optimizable neural network classifier: (1) all 10 core features and (2) reduced features selected from machine learning criteria. SHAP analysis was used to explain model predictions and determine feature impact for each risk category. Results: Reducing the input features from 10 to 6 led to improved performance in the explainable neural network model (AUC = 0.94, accuracy = 92%), confirming that T, N, Response, Age, M, and Hx Radiotherapy were the most informative predictors. SHAP analysis highlighted N and T as the dominant drivers of high-risk classification, while Response enhanced postoperative biological interpretation. Notably, when Response was excluded (Scenario III), the optimizable tree model still achieved strong predictive performance (AUC = 0.93–0.96), demonstrating that accurate preoperative risk estimation can be achieved using only clinical baseline features. Conclusions: The proposed interpretable neural network model effectively stratifies recurrence risk in DTC while reducing dependence on subjective pathological interpretation. SHAP-based feature attribution enhances clinical transparency, supporting integration of explainable machine learning into thyroid cancer follow-up and personalized management. Full article

We evaluated the effects of fenofibrate (FF) in a SU5416/hypoxia model of pulmonary arterial hypertension (PAH) with a specific focus on its influence on the renin–angiotensin system (RAS). We assessed right ventricular systolic pressure (RVSP), mean pulmonary artery pressure (mPAP), medial pulmonary artery wall thickening, right ventricular (RV) hypertrophy, systolic pulmonary artery pressure (SPAP), pulmonary artery effective elastance (PAEa), RV diastolic pressure (RVDP), RV developed pressure (RVDevP), right ventricular–pulmonary arterial coupling index (RVPAC), RV dp/dt max and dp/dt min. Levels of angiotensin II, angiotensin (1–7), angiotensin-converting enzyme 2 (ACE2), Bmpr2, Smad5 and nitrite (NO₂⁻) and nitrate (NO₃⁻) in the lung and RV were evaluated. The expression of AT1R, MAS receptors, and ACE2 in lung tissue was assessed. FF prevented the increase in RVSP, mPAP, RV hypertrophy, reduced pulmonary arterioles remodeling, and attenuated the rise in SPAP, mPAP, and PAEa. In the RV, it reduced RVDevP and prevented the decrease in dp/dt min, without affecting RVDP. RVPAC showed partial improvement. In lung tissue, FF decreased angiotensin II levels, the Ang II/Ang-(1–7) ratio, and reduced angiotensin II receptor type 1 (AT1R) expression, while preserving the receptor for the angiotensin-(1–7) (MAS) and ACE2. FF tended to restore Bmpr2/Smad5 expression. NO₂⁻ levels were preserved and tended to preserve (NO₃⁻) levels. In the RV, Ang-(1–7) increased, ACE2 was preserved, and NO₂⁻ and NO₃ levels were maintained. FF exerts protective effects in Su/Hx-induced PAH. Full article

Today, hydrogen is already widely regarded as up-and-coming source of energy. It is essential to meet energy needs while reducing environmental pollution, since it has a high energy capacity and does not emit carbon oxide when burned. However, for the widespread application of hydrogen energy, it is necessary to search new technical solutions for both its production and storage. A promising effective and cost-efficient method of hydrogen generation and storage can be the use of solid materials, including nanomaterials in which chemical or physical adsorption of hydrogen occurs. Focusing on the recommendations of the DOE, the search is underway for materials with high gravimetric capacity more than 6.5% wt% and in which sorption and release of hydrogen occurs at temperatures from −20 to +100 °C and normal pressure. This review aims to summarize research on hydrogen generation and storage using silicon nanostructures and silicon composites. Hydrogen generation has been observed in Si nanoparticles, porous Si, and Si nanowires. Regardless of their size and surface chemistry, the silicon nanocrystals interact with water/alcohol solutions, resulting in their complete oxidation, the hydrolysis of water, and the generation of hydrogen. In addition, porous Si nanostructures exhibit a large internal specific surface area covered by SiH_x bonds. A key advantage of porous Si nanostructures is their ability to release molecular hydrogen through the thermal decomposition of SiHx groups or in interaction with water/alkali. The review also covers simulations and theoretical modeling of H₂ generation and storage in silicon nanostructures. Using hydrogen with fuel cells could replace Li-ion batteries in drones and mobile gadgets as more efficient. Finally, some recent applications, including the potential use of Si-based agents as hydrogen sources to address issues associated with new approaches for antioxidative therapy. Hydrogen acts as a powerful antioxidant, specifically targeting harmful ROS such as hydroxyl radicals. Antioxidant therapy using hydrogen (often termed hydrogen medicine) has shown promise in alleviating the pathology of various diseases, including brain ischemia–reperfusion injury, Parkinson’s disease, and hepatitis. Full article

Polygonatum cyrtonema Hua, a plant with a long history of consumption in China, serves both medicinal and edible purposes, and it exhibits numerous pharmacological effects, including promoting kidney health and enhancing immune function. However, the effect and molecular mechanism of Polygonatum cyrtonema polysaccharides (PCPs) on hyperuricemia have not yet been reported. The hyperuricemic mice model was induced by the intraperitoneal injection of potassium oxonate (PO, 300 mg/kg), combined with the intragastric administration of hypoxanthine (HX, 300 mg/kg). Biochemical assays in mice revealed that PCPs markedly lowered high serum uric acid levels, suppressed xanthine oxidase (XOD) activity, and reduced the expression of inflammatory cytokines, including interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Western blot analysis demonstrated that PCPs downregulated urate transporter 1 (URAT1), while H&E staining showed that PCPs effectively restored renal histological integrity. Here, we isolated and identified the PCPs, which consist mainly of rhamnose, glucuronic acid, galacturonic acid, glucose, galactose, and arabinose, with a molar mass ratio of 0.5:2.15:0.47:16.58:3.66:1.09. Furthermore, the galactose residue that docked with both XOD and URAT1 molecules forms more hydrogen bonds and exhibits a lower binding energy, which enables the improved regulation of both targets. We have demonstrated for the first time the improving effect of PCPs on hyperuricemia, and revealed their regulatory mechanisms by modulating xanthine oxidase, inflammatory factors, and uric acid transporters. This study not only provides new insights into the anti-hyperuricemic activity of PCPs in mice, but also lays a foundation for its potential application in the functional foods of anti-hyperuricemia. Full article

Stomata play a crucial role in plant immune responses, with their morphological characteristics closely linked to disease resistance. Accurate detection and analysis of stomatal phenotypic parameters are essential for soybean disease resistance research and variety breeding. However, traditional stoma detection methods are challenged by complex backgrounds and leaf vein structures in soybean images. To address these issues, we proposed a Soybean Stoma-YOLO (You Only Look Once) model (SS-YOLO) by incorporating large separable kernel attention (LSKA) in the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8 and Deformable Large Kernel Attention (DLKA) in the Neck part. These architectural modifications enhanced YOLOV8′s ability to extract multi-scale and irregular stomatal features, thus improving detection accuracy. Experimental results showed that SS-YOLO achieved a detection accuracy of 98.7%. SS-YOLO can effectively extract the stomatal features (e.g., length, width, area, and orientation) and calculate related indices (e.g., density, area ratio, variance, and distribution). Across different soybean rust disease stages, the variety Dandou21 (DD21) exhibited less variation in length, width, area, and orientation compared with Fudou9 (FD9) and Huaixian5 (HX5). Furthermore, DD21 demonstrated greater uniformity in stomatal distribution (SEve: 1.02–1.08) and a stable stomatal area ratio (0.06–0.09). The analysis results indicate that DD21 maintained stable stomatal morphology with rust disease resistance. This study demonstrates that SS-YOLO significantly improved stoma detection and provided valuable insights into the relationship between stomatal characteristics and soybean disease resistance, offering a novel approach for breeding and plant disease resistance research. Full article

Introduction: Expanded hemodialysis using medium cut-off (MCO) dialyzers effectively removes middle-molecule uremic toxins, comparable to hemodiafiltration, but their single-use designation increases the dialysis costs. This study evaluated the efficacy and safety of reusing two MCO dialyzers available in Thailand. Methods: In this randomized controlled trial, hemodialysis patients were assigned to receive treatment with either Theranova^® 500 or Elisio^® 21HX dialyzers. Each dialyzer was reprocessed using peracetic acid and reused for up to 15 sessions. Dialyzer performance was assessed by the reduction ratios (RRs) of solutes, including β2-microglobulin (β2-MG), kappa and lambda free light chains (κ-FLC, λ-FLC), and interleukin-6 (IL-6), at baseline and the 2nd, 5th, 10th, and 15th sessions. Results: Forty-eight patients were enrolled (mean age 63.6 ± 13.7 years; 62.5% male) and randomized into 2 groups with comparable baseline characteristics. RRs for β2-MG, κ-FLC, and λ-FLC were similar between the groups and declined modestly over time after dialyzer reused (β2-MG: 78.2% to 72.5% vs. 77.2% to 74.5%, κ-FLC: 64.6% to 51.3% vs. 58.9% to 49.5%, and λ-FLC: 51.2% to 46.4% vs. 49.4% to 39.2% in the Theranova^® 500 and Elisio^® 21HX groups, respectively). Theranova^® 500 demonstrated significantly higher IL-6 clearance in the 2nd (29.9% vs. 16.0%; p = 0.018) and 5th (23.8% vs. 7.7%, p = 0.031) sessions. It also showed a non-significant trend toward lower dialyzer survival (HR 3.98; p = 0.085) and higher, though clinically acceptable, albumin loss (mean difference 0.56 g/session; p < 0.001), which decreased with reuse. Conclusions: Both MCO dialyzers demonstrated comparable overall performance during reuse. Theranova^® 500 provided better IL-6 clearance with manageable albumin loss. Implementation of high-quality dialyzer reuse protocols may optimize clinical efficacy and patient outcomes while balancing cost, accessibility, and environmental considerations. Full article

Background/Objectives: Despite progress in antiretroviral therapy, HIV remains a major global health challenge with over one million new infections annually. An effective vaccine is urgently needed. Germline-targeting immunogens show promise in initiating broadly neutralizing antibody (bNAb) precursors. This study developed a scalable, cGMP-compliant process to manufacture the HIV vaccine booster immunogen HxB2.WT.Core-C4b, a nanoparticle designed to direct bNAb precursor maturation after priming. Methods: A CHO cell platform was established through single-cell cloning from a high-producing stable pool. Upstream and downstream processes were optimized for scalability and yield. Three scales were tested 10 L, 40 L, and 400 L. Key parameters (pH, temperature, feeding, metabolite profiles) were systematically refined. Analytical characterization included glycosylation profiling, electron microscopy, and antigenicity testing. Viral clearance was evaluated per ICH Q5A guidelines. Results: Optimization ensured consistent yields above 130 mg/L, with titers up to 250 mg/L. The selected clone (4E22) demonstrated strong growth, viability, and reproducibility. Glycan occupancy at 18 N-linked sites, including bNAb epitopes (N276, N332), was stable across scales. Over 70% of self-assembling nanoparticle were fully assembled at the GMP level. Antigenicity and purity met cGMP release criteria. Viral clearance achieved >13-log reduction for enveloped and >7-log for non-enveloped viruses. Conclusions: This work establishes a robust, scalable platform for HIV nanoparticle immunogens. Consistent quality and yield across scales support clinical development of HxB2.WT.Core-C4b and provide a model for other glycosylated nanoparticle vaccines. The immunogen is being evaluated in clinical study HVTN 320 (NCT06796686), enabling early testing of next-generation vaccines designed to elicit broadly neutralizing antibodies. Full article