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Human-organ-scale x-ray fluorescence ghost imaging for radioisotope-free diagnostics
Highly Efficient Methane Electrosynthesis Enabled by Precise, Multifaceted Interface Regulation
Inhibition of PCSK9 protects against myocardial ischemia-reperfusion injury by suppressing ferroptosis via negative regulation of the P65/MMP9 pathway
Enhancing sit-to-stand transitions and walking efficiency in older adults with a soft robotic suit
Abstract Age-related declines in muscle strength and neuromuscular control make sit-to-stand transitions and walking progressively more difficult, compromising mobility and independence. Although wearable assistive technologies have been proposed to alleviate these challenges, few have demonstrated clear benefits in facilitating sit-to-stand movements for older adults who retain a degree of independent mobility. Here, we introduce a soft hip exosuit designed to assist both sit-to-stand transitions and walking activities. In a feasibility study involving ten older adults, the exosuit increased 1-minute sit-to-stand repetitions by an average of 1.8 and reduced the metabolic cost of walking by 13.6% compared with the unassisted condition. These improvements were achieved while preserving natural kinematics, lower-limb stability, and maintaining a strong sense of agency. Our findings demonstrate that soft exosuits can enhance sit-to-stand and walking performance in older adults while preserving biomechanical naturalness and user autonomy, highlighting their potential for practical home-integrated mobility assistance.
Environment-adaptive track mechanism with continuously transformable grousers
High-yield visible-to-ultraviolet upconversion by ZnSe quantum dots with dynamic triplet transfer
Abstract Triplet–triplet annihilation upconversion sensitized by quantum dot is often limited by the short exciton lifetime, necessitating tethered triplet transmitter. Here, we report a transmitter-free system of ZnSe quantum dot and 2,5-diphenyloxazole achieving 24% upconversion quantum yield, the highest for quantum dot sensitization upconversion. The upconversion quantum yield peaks at 30 mM 2,5-diphenyloxazole. Transient spectroscopy shows the triplet energy transfer efficiency is over 80% regardless of the 2,5-diphenyloxazole concentration, but the triplet–triplet annihilation efficiency dominates the overall upconversion quantum yield and shows a strong dependence on the 2,5-diphenyloxazole concentration that increases first from 10% to 25%, then decreases. The optimal concentration is achieved when the triplet 2,5-diphenyloxazole collision probability is highest, thus ensuring a maximum triplet–triplet annihilation efficiency. This work demonstrates a design principle of binary quantum dot upconversion system and reveals the critical role of modulating emitter concentration for optimal upconversion quantum yield.
Intermittent time-restricted feeding improves physical performance and modulates mitochondrial morphology in a muscle fiber type dependent manner in middle-aged mice
Understanding the European energy crisis through structural causal models
Abstract Natural gas supplies in Europe were disrupted and energy prices soared in the context of Russia’s invasion of Ukraine. Electricity prices in France experienced the largest relative increase among European countries, even though the share of natural gas in the electricity mix is small compared to its neighbours. In this article, we demonstrate the importance of causal statistical methods and propose causal graphs to investigate the French and Spanish electricity markets and pinpoint key influencing factors on electricity prices and net exports. We demonstrate that a causal approach resolves paradoxical results of simple correlation studies and enables a quantitative analysis of indirect causal effects and what-if scenarios. We introduce a linear structural causal model as well as non-linear tree-based machine learning combined with Shapley Flow values. The models elucidate the interplay of gas prices and the unavailability of nuclear power plants during the energy crisis as the high unavailability made France dependent on imports.
Reliability and validity of the DEFISS score for predicting post-extubation dysphagia and dysphagia-related reintubation after stroke
Abstract Post-extubation dysphagia is frequent after severe stroke and can lead to pneumonia, delayed recovery, and dysphagia-related reintubation. We evaluated the Determine Extubation Failure in Severe Stroke (DEFISS) score, a bedside tool combining stroke-specific clinical factors, duration of mechanical ventilation, and a brief oral motor function assessment to support pre-extubation risk stratification. In a prospective single-center cohort, three blinded raters (novice, intermediate, expert) independently scored DEFISS immediately before planned extubation, which followed routine clinical care. After extubation, all patients underwent flexible endoscopic evaluation of swallowing by assessors blinded to DEFISS. The primary outcome was dysphagia-related reintubation within 120 h, and construct validity was assessed against the Fiberoptic Endoscopic Dysphagia Severity Scale. Thirty-nine stroke patients (mean age 73.9 ± 11.6 years; 54% female) were included; five (12.8%) experienced dysphagia-related reintubation. Interrater reliability was excellent (ICC_single 0.887; ICC_average 0.959), with similarly high reliability for the oral motor function component (ICC_single 0.874). DEFISS correlated with endoscopic dysphagia severity (ρ = 0.44, p = 0.005). Using a prespecified cutoff (DEFISS ≥ 4), odds of dysphagia-related reintubation increased (OR 11.1, p = 0.035) with sensitivity 0.80 and specificity 0.73. DEFISS may provide a pragmatic triage tool to prioritize early FEES and targeted dysphagia management in critically ill stroke patients.
Flow matching for reaction pathway generation
Abstract Elucidating reaction mechanisms requires efficient generation of transition states (TSs) and products. Existing diffusion and sequence-based models accelerate parts of this process over traditional string-based methods, but typically still require manual enumeration of either TSs or products, and stochastic diffusion dynamics can be inefficient and hard to control. We introduce MolGEN, a conditional flow-matching framework that uses deterministic optimal transport to map Gaussian priors to chemical distributions. For TS generation, MolGEN improves TS geometry and barrier-height prediction over diffusion models while enabling sub-second sampling. For reaction product generation, it achieves competitive top- k accuracy while preserving mass and electron balance. Using the same backbone for TS and product sampling, MolGEN enables template-free generative exploration of reaction networks without the repeated quantum-chemistry searches required by prior methods. For the γ -ketohydroperoxide decomposition network, it produces more valid TSs than string-based methods using only 12 quantum-chemistry evaluations instead of 1156, and identifies a lower-barrier pathway.
Analysis of ultra-deep five-level underground station excavation in soft soil and its impact on existing structures
Mediterranean outflow waters supply North Atlantic convection sites
Cross-material physics-informed machine learning framework for optimizing nanofiller loading in epoxy nanocomposites for high-voltage insulation
Abstract Epoxy-based nanocomposites are promising solid insulation materials for high-voltage applications because of their high dielectric strength, mechanical robustness, and processability. However, identifying the optimal nanofiller loading that maximizes dielectric breakdown strength (BDS) remains challenging because conventional trial-and-error approaches are costly, time-consuming, and difficult to generalize across material systems. This study proposes a cross-material physics-informed machine learning framework integrating four structurally distinct nanofillers: Zn/Al-LDH, Mg/Al-LDH, γ-Al 2 O 3 , and α-Al 2 O 3 , where the alumina nanoparticles were synthesized from recycled aluminum beverage cans as a sustainable material source. For each system, 15 breakdown measurements per concentration were statistically validated using Weibull analysis. Among all systems, α-Al 2 O 3 exhibited the highest BDS of 46.8 kV/mm at 5 wt%, corresponding to approximately 56% improvement over neat epoxy. Dataset augmentation was performed using PCHIP interpolation combined with Gaussian noise injection and validated through Leave-One-Out Reconstruction analysis, which showed interpolation errors below 7.76% for internal concentration points. Composite relative permittivity at intermediate concentrations was estimated using the Maxwell–Garnett model and incorporated as a physically constrained input feature. Five regression algorithms were trained and benchmarked on material-specific datasets, achieving R 2 values up to 0.959 with experimental validation errors below 5.2%. A cross-material model was further developed by replacing categorical material identity with intrinsic filler permittivity as a physics-based descriptor, enabling a transferable across multiple investigated nanofiller systems using a common descriptor. The cross-material model achieved R 2 = 0.919 with prediction errors below 6%. The proposed framework provides a scalable and experimentally validated route for optimizing epoxy insulation systems for GIS/GIL spacer applications.
Glycerol metabolism triggers trypanosome differentiation into transmissible forms in mammalian tissue-like conditions
Abstract In the mammalian host, Trypanosoma brucei proliferates as slender bloodstream forms before undergoing quorum-sensing (QS)-dependent differentiation into non-dividing transmissible stumpy-QS forms, a process that both controls parasitaemia and enables transmission to the tsetse fly. However, this model does not explain how transmission occurs in chronically infected patients and cattle, where parasite densities are often too low to trigger QS-mediated differentiation. We identify a relevant glycerol-dependent pathway driven by adipocyte-derived glycerol that offers an explanation for this transmission paradox. We show that, at low parasite density, and with physiological levels of glycerol (0.2 mM) and glucose (4 mM) mimicking adipose and hypodermal interstitial fluids, glycerol promotes the emergence of novel proliferative forms that we termed, slender-Glyc forms. These cells are transmissible, unlike the slender forms, since they ( i ) differentiate in vitro into procyclic forms, which appear in the midgut of the infected flies, and ( ii ) establish infections in the fly. In addition, at high parasite density, tissular amounts of glycerol extends the lifespan of stumpy-QS forms (named stumpy-QS/Glyc), increasing transmission chances for tissue parasites, especially in the skin. Altogether, our findings suggest that local metabolic conditions, either on their own or in combination with parasite density, can drive transmission capacity.
Fabrication and characterisation of hydroxypropyl methylcellulose/ethyl cellulose/polyvinylpyrrolidone based composite wafers as an anti-bacterial dressing: a promising approach for curcumin delivery
Compressive learning scaffolds higher-order network structure to enhance human knowledge acquisition
A deep-learning based gait classification and anomaly detection framework for healthcare surveillance
Extracellular matrix stiffness directs region-specific lung epithelial differentiation revealed by hPSC-derived lung organoids
Abstract Regional epithelial lineages of the human respiratory system reside within an extracellular matrix (ECM) whose mechanics vary along the airway–alveolar axis, yet how ECM stiffness directs epithelial fates remains unclear. Here, utilizing human pluripotent stem cell-derived lung organoids embedded in stiffness-tunable hydrogels as an in vitro model, we show ECM stiffness governs region-specific epithelial differentiation. Stepwise softening of ECM stiffness yields airway organoids with proximal-to-distal airway epithelial compositions and biomimetic physiological functions. During alveolar differentiation, increased stiffness promotes alveolar type 2 (AT2) and type 1 (AT1) maturation and drives AT2-to-AT1 transition. Furthermore, RNA sequencing reveals ECM stiffness regulates epithelial fates primarily through mechanotransduction pathways. Finally, these organoids reproduce the infection tropisms of SARS-CoV-2 variants. Together, this research elucidates ECM stiffness as a critical determinant of epithelial cell fate specification and region-specific lung organoid generation, which offers a valuable in vitro model for studying region-specific lung development, diseases pathogenesis, and drug screening.
Impact of zero‑output crisp range recentering on the performance of FPIDD2 controllers for multi-area LFC–AVR systems
Abstract Modern interconnected power systems with high penetration of renewable energy sources (RES) and large‑scale use of electric vehicles (EVs) experience recurring frequency and voltage disturbances. Accordingly, the main objective in this work is to overcome this limitation in a power system under coordinated load frequency control (LFC) and automatic voltage regulation (AVR), which requires highly accurate control strategies. Fuzzy logic‑based controllers are among the most promising approaches for disturbance rejection, control precision, system stability, and robust performance. However, their performance is often limited because the selection of crisp ranges (i.e., the universes of discourse of the fuzzy variables) is usually set heuristically. In this paper, the crisp output range of a Fuzzy Proportional Integral Derivative Double Derivative (FPIDD 2 ) controller, which is based on a previous study, is reconfigured while maintaining the original rule base and membership function structure unchanged. This reconfiguration is presented to change the controller’s response by recentering (shifting) the zero output membership function rightward, thereby improving control sensitivity and dynamic performance. The effectiveness of the proposed approach is validated via MATLAB simulation on a multi‑area interconnected power system under realistic operating conditions, including stochastic input fluctuations due to renewable energy source penetration and electric vehicle participation, as well as nonlinear constraints such as generation ramp‑rate limits and governor dead zones. Several metaheuristic optimizers, including Particle Swarm Optimization (PSO), Gorilla Troops Optimizer (GTO), and Marine Predators Algorithm (MPA), are used to further evaluate the robustness of the proposed method. The results demonstrate that optimized FLC configuration with modified crisp ranges significantly improves controller sensitivity, damping characteristics, and robustness. Consequently, the Integral of Time- Absolute Error (ITAE) is reduced by up to 69% compared to the original controller configuration.