Browse Articles

Lead Lines in Severe Lead Poisoning

Preferred synthesis of armchair transition metal dichalcogenide nanotubes

Nanotubes represent an important class of crystalline materials but controlling their structures, particularly chiralities, remains a fundamental challenge. In this work, we report a strategy for synthesizing transition-metal dichalcogenide nanotubes with preferred armchair chirality. tin disulfide, molybdenum disulfide, and tungsten disulfide nanotubes are formed with high yield and structural purity inside boron nitride nanotube channels. Atomic-resolution imaging, electron diffraction, and circular dichroism reveal an armchair preference up to 83%. Density functional theory rules out structural stability as the origin of this preference but confirms that zigzag nanoribbons are energetically more stable. Machine learning potential molecular dynamics simulate that zigzag nanoribbons roll up to form armchair nanotubes, a process that is subsequently observed by in situ transmission electron microscope. This work may inspire the achievement of on-demand synthesis of various nanotubes with specific chiralities.

Seeking universal malaria-vaccine targets

Reprogramming synthesis

General-purpose artificial intelligence agents are at work in the materials chemistry laboratory

Seabed mining requires timely governance

Spain’s largest research body confronts its dark past

Spanish National Research Council has published the stories of some 500 staff purged under Francisco Franco’s dictatorship

Systems-level design of a multi-epitope immunotherapeutic vaccine targeting EBV-associated oncogenesis

Abstract Epstein–Barr virus (EBV) is an oncogenic herpesvirus associated with multiple lymphoid and epithelial malignancies. Despite extensive investigation of EBV vaccine strategies, effective therapeutic approaches capable of targeting established EBV-associated cancers remain limited. In this study, we developed an integrated immunoinformatics and structure-guided framework for the design and prioritization of therapeutic multi-epitope vaccine candidates targeting both structural glycoproteins (gp350, gB, gH/gL, and gp42) and latency-associated proteins (EBNA1, LMP1, LMP2, and BZLF1). Sixteen multi-epitope vaccine constructs were generated and evaluated through sequence validation, structural refinement, reverse vaccinology assessment, immune-response simulation, receptor interaction analysis, molecular dynamics simulations, and expression-readiness profiling. The prioritized epitope repertoire achieved projected global population coverage exceeding 98% for both MHC class I and II pathways. Structural refinement improved model quality across vaccine constructs, while immunological and safety assessments supported favorable predicted antigenicity, non-allergenic potential, non-toxicity, and developability properties. Immune simulations predicted coordinated innate, humoral, and cellular responses, with several constructs demonstrating strong predicted immunogenic profiles. Molecular docking and molecular dynamics analyses further supported predicted structural compatibility and interaction stability with immune-associated receptors under simulated conditions. Integrated multi-parameter evaluation identified Constructs 4, 7, 10, 8, and 12 as the most promising candidates, with Construct 4 exhibiting the most balanced profile across immunological, structural, safety, and expression-related properties. Collectively, this study provides a comprehensive computational framework for therapeutic EBV vaccine development and identifies prioritized vaccine candidates for experimental validation. The proposed strategy offers a scalable approach for accelerating the development of multi-epitope vaccines targeting persistent viral infections and virus-associated malignancies.

Thrust prediction for hybrid rocket motors with aerodynamic throats based on radial basis function neural networks

TFIDD: Adaptive dynamics for fast model-agnostic drift detection

A surrogate-assisted framework for the subject-specific scalable design of compliant prosthetic wrists

Evaluating the effects of soil and water conservation measures on soil moisture regimes and crop performance in Jammu’s rainfed agroecosystems

Isomeric multi-hydrogen-bonding enables blue perovskite LEDs

Interleaved premotor rTMS does not affect motor sequence learning

Abstract Acquiring new motor skills is a vital component of lifelong learning and underpins everyday activities. Performance improvements through training evolve from an initially fragile state to one that becomes increasingly resistant to disruption, a process known as motor consolidation. Recent research has indicated that learning takes place even during brief periods of rest – termed micro-offline learning. In healthy young individuals, such intervals may represent the primary source of performance enhancements during training sessions. Other studies have identified both the primary motor cortex (M1) and the premotor cortex (PMC) as pivotal neural structures for motor consolidation. Specifically, it has been demonstrated that 10 Hz interleaved repetitive transcranial magnetic stimulation (i-rTMS) to M1 during rest intervals between active motor training blocks can enhance post-training offline consolidation without influencing performance during training. Here, we examined whether 10 Hz i-rTMS to the PMC produces similar effects. Contrary to our expectations, our results suggest that premotor i-rTMS does not affect online or offline learning, at both microscopic and macroscopic temporal scales. We also measured corticospinal excitability before and after training, but no detectable effects of training or i-rTMS were observed. Taken together, these findings provide no evidence for an effect of i-rTMS of the PMC on online or offline motor sequence learning. We speculate that consolidation during offline processing in short rest periods between active training phases may not necessarily require involvement of the premotor cortex.

Dendrite initiation and deflection in biaxially stressed solid electrolytes

Product appearance sensory evaluation model using Qualia Theory and AHP for Chaozhou woodcarving crafts

BASG-Net: a background-aware spatial gating network for cervical cell segmentation in pap smear images

Missense but mis-spliced: germline TP53 variant c.671A > C (p.E224A) and the path from uncertainty to pathogenicity

Implementing an identification tool to accurately capture non-ambulatory fragility fractures: a quality improvement project

Non-invasive estimation of inspiratory muscle pressure and work of breathing by airway pressure extrapolation from the P0.1 maneuver during assisted ventilation

Abstract Monitoring inspiratory effort during assisted mechanical ventilation is essential to balance lung protection and respiratory muscle loading. Esophageal pressure monitoring remains the reference standard for estimating inspiratory muscle pressure and work of breathing but is invasive and rarely used in routine clinical practice. Non-invasive alternatives based on routinely available ventilator signals are therefore needed. This monocentric physiological substudy of the ICEBERG observational trial included adult patients with acute hypoxemic respiratory failure undergoing assisted mechanical ventilation. Inspiratory muscle pressure (P mus ) was first estimated non-invasively by linear extrapolation of the airway pressure drop recorded during a standardized end-expiratory occlusion (P0.1 maneuver) into early inspiration (up to 500 ms after occlusion). Using the extrapolated P mus together with airway pressure, airway resistance was calculated during early inspiration, both with and without correction for respiratory system elastance determined by occlusion maneuvers. The resulting resistance and elastance were then used to parameterize the equation of motion of the respiratory system, allowing subsequent reconstruction of the inspiratory P mus waveform over the entire breath. From the reconstructed pressure signal, peak inspiratory P mus , work of breathing, and pressure–time product were calculated. Esophageal pressure–derived measurements served as the reference standard, and agreement was assessed using linear regression and Bland–Altman analysis. Eighteen patients (age 67 ± 12 years, PaO₂/FiO₂ 198 ± 44 mmHg) contributed 33 valid measurements. Based on a patient-average analysis, non-invasively estimated P mus during early inspiration showed statistically significant correlations with esophageal pressure–derived values across all analyzed time points (all p < 0.01), with the highest agreement and lowest bias observed at 100 ms extrapolation time after the end of the P0.1 maneuver. Elastance-corrected airway resistance demonstrated slightly improved agreement compared with uncorrected resistance estimates. Work of breathing derived from non-invasive inspiratory P mus showed good agreement with reference measurements (R 2  = 0.70; bias =  − 0.05 J), whereas pressure–time product exhibited greater bias and wider limits of agreement. A P0.1-guided, non-invasive method based on airway pressure extrapolation allows feasible and physiologically meaningful estimation of inspiratory P mus during assisted ventilation. Derived work of breathing shows good agreement with esophageal pressure-based measurements, supporting the potential of this approach for non-invasive monitoring of inspiratory effort in patients with acute hypoxemic respiratory failure.

Obstetric outcomes in pregnancies with solitary huge uterine fibroids: size versus type and location

Abstract Huge uterine fibroids represent a rare but clinically significant complication of pregnancy. This study aimed to evaluate their impact on major obstetric outcomes and to determine whether fibroid type and anatomical location modify these risks. This retrospective observational study (2010–2023) compared 64 singleton pregnancies complicated by a single huge uterine fibroid (maximal diameter ≥ 10 cm) with 128 matched fibroid-free controls. Fibroids were classified sonographically by type and location. Outcomes included mode of delivery, gestational age (GA) at birth, preterm birth (PTB), neonatal birthweight, 5 min Apgar and maternal hemoglobin decline. Multivariable logistic regression was used to identify independent predictors of cesarean delivery (CS). Among 57,200 pregnancies, huge uterine fibroid was identified in approximately 1 in 670 pregnancies (0.15%). These pregnancies were associated with higher rates of CS compared with controls (39.1% vs. 8.6%, P  < 0.01), earlier GA (median 38.0 vs. 39.6 weeks, P  < 0.01), a markedly increased rate of PTB (29.7% vs. 4.7%, P  < 0.01), and greater maternal hemoglobin decline. Within the fibroid cohort, fibroid size relative to the median diameter was not associated with adverse outcomes. In contrast, intramural fibroids were strongly associated with both earlier GA and an increased risk of CS compared with subserosal lesions (adjusted OR 23.79, 95% CI 3.67–534.32, P  < 0.01). Fibroids located in the lower uterine segment or cervix were also associated with elevated CS rates. Obstetric risk of pregnancies complicated by a huge solitary fibroid is driven primarily by fibroid type and anatomical location rather than size alone, supporting individualized counseling and delivery planning.