Search Results (4,079)

RNA origami enables genetically encoded, single-stranded RNA nanostructures that can self-assemble through co-transcriptional folding and are increasingly deployed as scaffolds for biosensing, synthetic biology, and nanomedicine. A recurring practical bottleneck is scalable, solution-phase readout of whether a designed scaffold has reached its intended base-paired architecture, whether it undergoes slow maturation or kinetic trapping, and how its stability is distributed across motifs. Here, we adapt microfluidic modulation spectroscopy (MMS) as a label-free structural biosensor for RNA folding by exploiting the rich 1760–1600 cm⁻¹ vibrational fingerprints of RNA bases and base pairs. MMS alternates between sample and composition-matched buffer measurements in a microfluidic transmission cell to automatically subtract the solvent background, enabling high-quality spectral measurement from microliter volumes under native solution conditions. Using a six-helix-bundle-with-clasp (6HBC) RNA origami as a model, we established an analysis workflow (baselined second derivative and constrained deconvolution) to quantify paired versus unpaired populations. Thermal ramping resolves multiple unfolding events and yields an unfolding barcode that differs between young and mature ensembles. Importantly, MMS tracks post-transcriptional maturation from a kinetically trapped young conformer toward a more compact, base-paired mature state, consistent with prior cryo-EM/SAXS observations for 6HBC RNA origami. Together, these results position MMS as a rapid, automated, and scalable complement to high-resolution structure determination for engineering dynamic RNA origami biosensors. Full article

Background/Objectives: Chronic lower-limb ulcers of mixed etiology are characterized by impaired microcirculation and persistent inflammation, leading to delayed healing, frequent hospitalizations, and a high risk of limb loss. While infrared thermography reflects local perfusion status and systemic inflammatory markers capture whole-body immune activation, these dimensions are usually assessed separately. The objective of this study was to develop and internally evaluate a composite Thermal–Inflammatory Index (TI) integrating wound-bed thermography with systemic inflammatory markers to stratify disease severity and prognosis in patients with chronic lower-limb ulcers. Methods: In this prospective observational study, 82 adults with chronic lower-limb ulcers underwent baseline infrared thermographic assessment of wound-bed temperature using a standardized protocol. Concurrently, neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) were measured. The Thermal–Inflammatory Index was constructed as a standardized composite of inverted wound-bed temperature, NLR, and CRP. A simplified TI score (0–3) was derived using predefined clinical thresholds. The primary endpoint was a composite adverse outcome defined as amputation or failure to achieve complete wound healing within 12 weeks. Secondary outcomes included a prolonged hospital stay (>7 days). Discriminative performance was assessed using receiver operating characteristic analysis, and associations were examined using correlation and logistic regression models. Results: Higher TI values were associated with colder wound beds, elevated systemic inflammatory markers, and increased disease burden. The TI demonstrated moderate discrimination for the composite adverse outcome (AUC 0.75) and prolonged hospitalization (AUC 0.71), performing comparably to the strongest single component (−T_bed, AUC 0.77) while integrating local and systemic information. Each one-standard-deviation increase in TI was independently associated with higher odds of the composite adverse outcome and a prolonged hospital stay. The simplified TI score showed clear stepwise gradients in adverse outcomes and length of hospitalization. Conclusions: The Thermal–Inflammatory Index integrates thermographic and inflammatory signals into a single, clinically interpretable biomarker of severity and prognosis in chronic lower-limb ulcers. TI and the simplified TI score may support early risk stratification using low-cost, bedside-accessible data. Full article

Global data center electricity demand is projected to double to 945 TWh by 2030, yet no optimization framework jointly sizes renewable generation, battery storage, hydrogen export infrastructure, and flexible computing loads within a single industrial hub. This paper develops a two-layer techno-economic workflow for an integrated renewable–hydrogen–data center hub in Yanbu Industrial City, Saudi Arabia. HOMER Pro provides baseline capacity sizing and dispatch across four scenarios; a Pyomo-based mixed-integer linear program, calibrated to within 2% of the baseline, then extends the system to include a 60 MW data center (30 MW critical, 30 MW flexible), multi-sink hydrogen allocation (domestic, ammonia, methanol), and low-grade waste heat recovery. Battery storage emerges as the dominant cost–carbon lever: its removal raises the levelized cost of electricity (LCOE) from 0.052 to 0.181 USD/kWh (+250%) and increases CO₂ emissions from 1.83 to 2763 kt/yr, a factor of 1510. The Integrated Hub reduces annualized costs by 8.2% (36.9 M USD/yr) and emissions by 28% relative to a separate-build counterfactual, driven by shared PV–battery infrastructure and hydrogen export revenues of 58.5 M USD/yr. Export demand raises the electrolyzer capacity factor from 8.65% to 24.3%, cutting the levelized cost of hydrogen from 10.5 to 6.8 USD/kg. Waste heat recovery reduces the levelized cost of heat by 17%, and co-location lowers the levelized cost of compute by 23% (from 0.055 to 0.042 USD/GPU/hr). These results provide quantitative design principles for industrial hub planners considering data center co-location in high-solar regions with hydrogen export ambitions. Full article

Pulsating heat pipes (PHPs) are promising passive heat-transfer devices for compact thermal management; however, their performance is highly sensitive to channel geometry. In particular, the operating-condition-dependent influence of sinusoidal corrugation amplitude on the condenser side remains unclear, despite its importance for oscillation regulation and heat dissipation. This numerical study investigates a single-loop PHP with sinusoidally corrugated condensers (A = 0.25 and 0.5 mm) under heat fluxes of 5000–12,500 W/m² and filling ratios of 40–60%, using a uniform-diameter PHP as the baseline. The results show that the configuration with A = 0.25 mm exhibits better start-up performance, especially at low heat fluxes, whereas both corrugated configurations provide better thermal performance than the baseline. At a filling ratio of 50%, the thermal-resistance reductions for A = 0.25 and A = 0.5 mm are 14.5% and 9.2% at 5000 W/m² and 8.4% and 10.5% at 12,500 W/m², respectively. An operating-condition-dependent amplitude-matching relationship is identified: The smaller amplitude is more favorable for start-up under weak driving conditions, whereas the larger amplitude tends to provide lower thermal resistance and higher equivalent thermal conductivity under strong driving conditions. These findings provide useful guidance for condenser-geometry optimization in single-loop PHPs. Full article

Background/Objectives: Heart rate variability (HRV) and cerebral autoregulation (CAR) reflect physiologic processes that may influence neurological injury in children supported with extracorporeal membrane oxygenation (ECMO). Although abnormalities in both have been associated with adverse neurological outcomes, their physiologic relationship during ECMO remains unclear. Methods: This retrospective single-center study evaluated the association between HRV and CAR during the first 24 h of ECMO support and assessed their independent relationships with neurological outcome. Patients with at least two hours of simultaneous HRV and CAR monitoring within 24 h of ECMO initiation were included. HRV metrics were derived from artifact-free NN intervals across time, frequency, and nonlinear domains, while CAR was quantified using the cerebral oximetry index (COx), with impaired CAR defined as COx > 0.3. Associations between HRV indices and COx were examined using Spearman correlations at hourly and 24 h resolutions. Unfavorable outcome was defined as death or a Pediatric Cerebral Performance Category (PCPC) score ≥3 at discharge with deterioration from baseline. Results: Eighty-nine patients met inclusion criteria, and 16% demonstrated impaired CAR. HRV measures were reduced relative to age-adjusted norms in both CAR groups without significant differences between groups. Correlations between HRV indices and COx were consistently weak. Overall, 50% experienced unfavorable neurological outcomes. In adjusted logistic regression models, NN skewness and COx were independently associated with outcome, although only NN skewness remained significant in interaction analyses. Conclusions: HRV and CAR exhibited limited physiological coupling during early ECMO support, while each measure provided independent prognostic information with respect to neurological outcome. Full article

Overtaking maneuvers can induce significant changes in the airflow field between vehicles, potentially compromising the stability and safety of the overtaken vehicle. This study investigates the aerodynamic characteristics during overtaking in a platoon of vehicles using the 1:2.5 DrivAer fastback model as the subject of analysis. To simulate the external flow during overtaking within a vehicle platoon, the Reynolds-Averaged Navier–Stokes (RANS) equations are employed under steady-state, incompressible flow assumptions. A baseline simulation is first performed for a single vehicle, and the results are validated against experimental data to ensure the reliability of the numerical method. The simulation is subsequently extended to a two-vehicle platoon configuration with a longitudinal spacing of half a vehicle length. Under steady platoon driving conditions, no significant lateral aerodynamic disturbances are observed between adjacent vehicles, and a two-vehicle platoon is subjected to relatively small lateral forces. However, during the overtaking process, notable variations in aerodynamic forces and moments occur. In particular, the lateral force coefficient and yaw moment coefficient of two-vehicle platoons reach their peak values at about two vehicle lengths ahead of the critical overtaking position. Furthermore, during the overtaking maneuver, the aerodynamic characteristics of the overtaken vehicle exhibit continuous fluctuations. The resulting variations in the lateral force coefficient and cornering stiffness have a sustained impact on vehicle handling stability, providing crucial insights for enhancing vehicle maneuverability. Full article

Underwater wireless power transfer (UWPT) enables long-term deep-sea floor exploration by providing contactless energy replenishment for autonomous underwater vehicles (AUVs). However, conventional single-transmitter systems suffer reduced coupling and efficiency caused by high-loss underwater dielectrics and docking-induced perturbations. We propose a parallel-resonant dual-transmitter configuration based on the parity–time (PT) symmetric gain–loss-balanced modal framework. The proposed dual-transmitter single-receiver (DTSR) system forms a stronger and more symmetric field in the receiver than the single-transmitter baseline, counteracting the high-loss dielectric and improving the misalignment tolerance. According to the PT symmetry coupled-mode theory, we analyze how the quality factor and coupling strength determine the admissible PT-unbroken operating region over the docking-induced coupling range. An experimental prototype validates the analysis by comparing operating frequency and efficiency between DTSR and the single-transmitter baseline under distance (4.8–13.5 cm) and load (2.0–4.3 kΩ) variations. The results show that DTSR increases the critical coupling distance by 20–30% and reduces efficiency sensitivity to distance and load variations. These results suggest that the system can provide more robust and stable UWPT for AUV recharging under high-loss dielectric and perturbation, conducive to practically implementing AUV recharging in deep-sea operations. Full article

The efficacy of immunotherapy in colorectal cancer (CRC) has long been considered to be closely associated with microsatellite instability (MSI) status. Patients with microsatellite stable (MSS) tumors typically exhibit poor responses to PD-1/PD-L1 inhibitors and a poor prognosis, often being categorized as immunologically ‘cold’ tumors. However, some MSS patients can still achieve favorable therapeutic responses, sometimes even surpassing those of certain MSI patients. Immune-cold and immune-hot tumor phenotypes are largely determined by the abundance, clonal expansion, and functional states of tumor-infiltrating T cells. This suggests that immunotherapy responses are driven by dynamic remodeling of T-cell clonality rather than by MSI status alone. To elucidate the underlying T cell clonal dynamics, integrated single-cell transcriptome (scRNA-seq) and T cell receptor sequencing (scTCR-seq) data analyses from 43 blood and tissue samples of MSI and MSS colorectal cancer patients before and after anti-PD-1 therapy were performed. Using our developed TCR reconstruction pipeline (TORBiT), we systematically analyzed the clonal architecture of the TCR repertoire, inter-tissue migration, and its association with T-cell functional state transitions. From a TCR clonal kinetic perspective, we revealed two distinct modes of immune Coercion that may further affect the immune response: a “high-fluctuation, deep-exhaustion” pattern in MSI tumors and a “high-baseline, strong-suppression” pattern in MSS tumors. These findings provide a novel theoretical foundation and research perspective for understanding the responsiveness and resistance mechanisms to immune checkpoint inhibitors. Full article

Accurate and reliable short-term traffic flow prediction is crucial for managing urban congestion but is challenged by the complex spatio-temporal dependencies inherent in traffic systems. Conventional single models, such as Long Short-Term Memory (LSTM) and Temporal Convolutional Network (TCN), often fail to capture these nonlinear dynamics. To address this, we propose a novel Bayesian-Optimized Mixture of Experts (BO-MoE) framework. This hybrid architecture utilizes a Mixture of Experts (MoE) to dynamically integrate multiple specialized deep learning models, allowing it to adapt to diverse and complex traffic patterns. Bayesian Optimization (BO) is further integrated to automate hyperparameter tuning, significantly enhancing predictive accuracy and model efficiency. We evaluated BO-MoE on three real-world traffic datasets. Empirical results demonstrate that our model consistently outperforms strong baselines, including TCN. Specifically, on PEMS04, it reduces MAE, RMSE, and MAPE by 1.97%, 1.19%, and 3.23%, respectively, while on PEMS08, the corresponding reductions reach 3.83%, 1.26%, and 5.49%. On the NZ dataset, BO-MoE also achieves superior performance, with improvements comparable to those on PEMS benchmarks. Full article

Background/Objectives: Tafamidis, a transthyretin kinetic stabilizer, increases circulating transthyretin levels in treated patients. While this effect is well documented, its underlying mechanism remains incompletely understood. This study aimed to evaluate the performance of physiologically based pharmacokinetic (PBPK) model performance and to calibrate a hypothesis-consistent quantitative systems pharmacology (QSP) model of tafamidis and transthyretin dynamics to explore mechanistic hypotheses underlying the clinically observed increase in circulating transthyretin and the associated dose–response relationship. The PBPK model constitutes the primary framework, while the coupled QSP component illustrates how tafamidis exposure predictions can be used to evaluate mechanistic hypotheses of TTR turnover. Methods: A PBPK–QSP model was constructed in Simcyp (V23) using LUA-based modules. The PBPK part was parameterized from the literature and validated against data from therapeutic single-dose, therapeutic multiple-dose, and supratherapeutic dose clinical studies. The QSP part of the model describes tafamidis–TTR binding kinetics, stabilization, and clearance of bound complexes. Simulations were performed in thirty virtual healthy male subjects aged 30–40 years, incorporating physiological variability in baseline TTR concentrations. Results: Mean predicted versus observed ratios of tafamidis AUC and $C_{max}$ values were within a 1.3-fold range across validation studies. The integrated model reproduced the clinically reported 33% increase in TTR concentration through a calibrated clearance-scaling factor. It supports the hypothesis that reduced clearance of tafamidis-bound TTR may explain the observed effect without modifying TTR synthesis. Dose-sensitivity simulations indicated that patients with low baseline TTR may achieve adequate stabilization at reduced doses, while those with higher baseline TTR concentration may require higher doses. Conclusions: The developed PBPK–QSP model not only reproduces tafamidis pharmacokinetics and TTR responses but also proposes a plausible mechanistic hypothesis consistent with clearance modulation of stabilized TTR contributing to the clinical effect. Full article

This study examines information recovery under structured partial observation in multi-informant questionnaire systems. Rather than predicting an external ground truth, we evaluate the recoverability of an operational full-information decision rulewhen only partial informant views are available. In the empirical SNAP-IV calibration study, this reference is intentionally defined as a deterministic function of the combined informant views, so the combined-view result is treated only as an oracle-style ceiling and the substantive analysis concerns how single-view recovery degrades when one informant is withheld. To examine whether a similar qualitative pattern extends beyond this calibration setting, we additionally evaluate a latent-state simulation in which the reference decision is generated from an unobserved latent state and informant views are noisy observations. Across both settings, single-view recoverability declines as inter-rater disagreement increases, whereas combined-view representations remain more stable. In the empirical study, combined-view models achieved near-ceiling recovery performance (e.g., 90.9% for Logistic Regression and 91.3% for MLP), while Teacher-only recovery dropped from approximately 78% to 63% under higher disagreement ($p=0.0005$, Cohen’s $d=1.9$). Additional non-learned single-rater score-threshold baselines exhibited the same qualitative degradation pattern, indicating that the effect is not specific to fitted machine learning models. Importantly, this work is methodological: it does not propose new learning algorithms or clinical prediction models, but instead presents a conceptual–methodological framework, together with model-agnostic recoverability quantities, for quantifying missing-view information loss under incomplete, heterogeneous observations. Full article

Underwater acoustic single-beacon positioning technology achieves localization by integrating vehicle motion with range measurements acquired from acoustic ranging devices, offering advantages such as system simplicity, flexible deployment, and high cost-effectiveness. However, its accuracy is limited by weak initial observability and degraded observation geometry. To address this, a sensor data correction and collaborative optimization framework is proposed. A hybrid outlier rejection strategy first suppresses acoustic multipath and sensor noise. To compensate for systematic sensor errors ignored in conventional Virtual Long Baseline methods, an affine transformation maps the true trajectory to the sensor-indicated one, reformulating error compensation as a correction to virtual beacon coordinates. To further mitigate the accuracy degradation caused by degenerated geometric configurations, this paper proposes a collaborative algorithm that integrates Chan initialization with affine transformation optimization. This approach formulates the positioning problem as an optimization task, simultaneously estimating the position information and affine transformation parameters through iterative refinement to achieve high-precision localization. The process begins with Chan’s algorithm, which provides an initial estimate from the virtual sensor array. This estimate is then refined under affine constraints to achieve high-precision localization. Experimental results show the method improves positioning accuracy by 36.30% compared to baseline algorithms, demonstrating significant performance enhancement. Full article

Platelet-rich gel (PRG) is a fibrin-based biobased biomaterial generated by activating platelet-rich plasma (PRP), yet its biological characterization has commonly relied on univariate measurements of isolated mediators. This study aimed to define the multivariate biological organization of PRG and related hemocomponents (PRP, chemically induced platelet lysate (CIPL), and plasma) in a canine model under single exposure to non-steroidal anti-inflammatory drugs (NSAIDs). In a randomized crossover design (n = 6 dogs), hemocomponents were produced at baseline (0 h) and 6 h after administration of carprofen or firocoxib. Platelet and white blood cell (WBC) counts, growth factors (platelet-derived growth factor-BB (PDGF-BB) and transforming growth factor beta-1 (TGF-β1)), and cytokines (tumor necrosis factor alpha (TNF-α), interleukin-1 beta, and interleukin-10) were integrated using linear mixed-effects modeling, principal component analysis (PCA), and hierarchical clustering. PRG was derived from a leukocyte-poor PRP precursor with moderate platelet enrichment (~1.6-fold vs. whole blood) and a marked WBC reduction (~8–9-fold). In mixed-effects modeling, hemocomponent type significantly influenced the PDGF-BB:TNF-α log-ratio, with PRG (estimate −1.12; 95% CI −1.34 to −0.90) and plasma (−2.06; 95% CI −2.28 to −1.84) lower than PRP, while CIPL did not differ. Time and NSAID effects were not supported. PCA identified two orthogonal axes explaining 61.3% of total variance (PC1 = 43.7%, PC2 = 18.6%), separating a platelet/trophic dimension (log(PDGF-BB), log(TGF-β1), platelet count, PDGF-BB:TNF-α log-ratio) from an inflammatory dimension (log(TNF-α), log(IL-1β)). Overall, hemocomponent composition emerged as the primary determinant of mediator organization, supporting the interpretation of PRG as a structured, biomaterial defined by coordinated mediator networks. Full article

Recommender systems are now integral to many online platforms, including e-commerce, social media, and content streaming services. However, their widespread use also exposes them to significant security threats. One of the most critical is the shilling attack, where fake user profiles are injected to manipulate recommendation results. Such attacks undermine system fairness and erode user trust. Traditional detection methods mostly rely on a single perspective, such as a fake profile, temporal behavior or a graph structure, and they have difficulty dealing with complex and changeable attack strategies. Therefore, we propose a multi-view cross-attention (MVCA) attack detection framework. This system integrates three complementary features: the user–item interaction graph structure, the temporal behavior sequence, and the local scoring mode. We propose a bidirectional cross-attention mechanism to achieve deep information interaction, dynamically mine the potential correlations between different views, solve the collaborative optimization of each module, and improve the accuracy of identifying fake users. Extensive experiments conducted on the MovieLens and Netflix datasets have shown that MVCA generally outperforms several established baseline methods. Its strong performance in handling different types and scales of attacks demonstrates the method’s adaptability and robustness for detecting shilling attacks. Full article

Candida species are frequently detected in bile cultures during endoscopic retrograde cholangiopancreatography (ERCP), but their clinical significance and the value of antifungal treatment remain unclear. We performed a retrospective single-center cohort study of adults with growth of Candida species from bile cultures collected by ERCP performed between 2010 and 2023. We compared inpatients who received vs. those who did not receive antifungals within one week of ERCP and a subgroup with acute cholangitis. The primary outcome was a composite of death and invasive candidiasis within one year. Secondary outcomes included death, invasive candidiasis, and rehospitalization. Inverse probability of treatment weighting (IPTW) was performed using baseline characteristics. Adjusted hazard ratios and odds ratios were calculated. Among 197 inpatients, 51 (25.9%) received antifungals. At one year, the primary outcome occurred in 23 of 51 patients (45.1%) receiving antifungal therapy and in 67 of 146 patients (45.9%) who did not; the IPTW-adjusted hazard ratio was 0.93 (95% confidence interval 0.69–1.27; p = 0.66). No significant differences were seen in the acute cholangitis subgroup (n = 117). In this study, antifungal therapy was not associated with improved survival, lower rates of invasive candidiasis, or fewer readmissions. Findings support a conservative, stewardship-oriented approach to managing Candida-positive bile cultures in the absence of invasive disease. Full article