Key tasks in the development of guideline recommendations include determining the magnitude of desirable and undesirable health effects, the overall net effect and assessing the certainty of evidence. Developing and using decision thresholds can support these tasks and increase transparency, however evidence of the procedural steps is limited. We describe a systematic, step-by-step approach of how to develop and use decision thresholds and apply this approach to guide decision-making during the development of the Swedish Guideline of Caffeine in Preterm Infants. Through an iterative consensus-based process, we applied the GRADE Guidance to set decision thresholds by using a variety of different sources of evidence, including register data, systematic reviews of values of outcomes, and surveys to content experts, and discussion, feedback and consensus within working groups and the guideline panel. We used 15 distinct steps across three phases to derive decision thresholds. Phase 1 included five steps related to preparing the evidence: Identify relevant outcomes; develop health outcome descriptors; assess the importance of outcomes; determine the incidence of outcomes- both positive outcomes and outcomes regarded as harms/side effects; and conduct or identify systematic reviews of relative importance of outcomes. Phase 2 included six steps relating to refining decision thresholds for the magnitude of effects: Draft initial thresholds with methodologists; refine thresholds within a working group including content experts; determine disutility-value; refine thresholds within a working group; obtain consensus with guideline panel and decision makers; and receiving further interest-holder feedback. Phase 3 include four steps related to applying the decision thresholds to; magnitude of effects of individual outcomes; estimate the net effect; rate the certainty of the evidence; explore the impact of interest-group- or subgroup-specific thresholds. We provide a practical application of GRADE guidance for developing, reporting and using explicit decision thresholds that can be applied in other scenarios. We found that the use of explicit thresholds facilitated a number of steps in applying GRADE in evidence to decision processes. Overall, thresholds were considered useful by the panel and methodologists for determining magnitude of effects, estimating the balance of effects and for reaching a recommendation.
In this work, we explore the uses of biased sampling simulations including constant-velocity SMD (cv-SMD) and umbrella sampling to study molecular permeation of three highly distinct solutes spanning over 3 orders of magnitude in the permeability space, across a model of the blood-brain barrier (BBB). These molecules range from among the slowest permeants known (temozolomide; Papp ∼ 10-6 cm s-1) to among the fastest compound known (ethanol; Papp ∼ 10-3 cm s-1). We arrive at the transmembrane solute permeability, Psim, by the Inhomogeneous Solubility-Diffusion equation combined with an unbiasing procedure involving the Green-Kubo relations, to find a ∼1 order of magnitude agreement with experiments. We find that the converged thermodynamics of crossing span distinct topologies for each of the compounds considered, while noting that there is an apparent relationship between the thermodynamic barrier height (ΔG‡) and experimental permeability, Papp for these molecules.
Cerebrovascular reactivity (CVR), a promising marker of neurovascular responsiveness, is commonly measured using blood-oxygenation-level-dependent magnetic resonance imaging (BOLD-MRI) during a vasoactive gas challenge. While CVR magnitude (vascular response strength) has been widely studied, CVR delay (response time) is comparatively underexplored yet may provide valuable insight into vascular dysfunction across several neurological conditions. We systematically reviewed publications assessing delay using gas-challenge BOLD-MRI up to October 2025, identifying 200 relevant papers. Only 44 (22%) papers investigated delay in detail; the remainder only applied delay correction to improve CVR magnitude accuracy. Findings in disease were mixed and often limited by small sample sizes and methodological differences. Hypercapnic stimuli, typically delivered via fixed-inspired or fixed-expired methods, were most commonly used. While cross-correlation was the most popular delay estimation method, several alternatives, including haemodynamic response function fitting and Fourier analysis, have been proposed, but systematic comparisons against standard delay estimation methods remain limited, especially in clinical populations. Our review highlights inconsistencies in delay measurement and interpretation, with delay mostly treated as a confounder rather than a meaningful physiological parameter. Greater methodological validation and harmonisation are needed to realise the potential of CVR delay as a novel biomarker of brain health and disease.
The aim of this paper is to test whether biological macromolecules carry information through two distinct, separable channels. The conformational channel (C-channel), governed by three-dimensional structure and the Coulomb potential, sets binding geometry, catalysis, and stability. The spectral channel (S-channel), the one-dimensional electron-ion interaction potential (EIIP) profile and its characteristic frequency fRRM, is proposed to mediate resonant molecular recognition. In quantum information biology, recognition - a protein selecting a partner among thousands of candidates - is modelled as a decision following quantum-probabilistic laws despite macroscopic physics. This requires the channels to form a bipartite system whose state space factorises as a tensor product HC⊗HS of separable degrees of freedom. Whether the channels are coupled, independent, or complementary is the empirical prerequisite tested here. We analyse 87,389 single-nucleotide missense substitutions across 222 non-redundant, full-length proteins (51-4684 residues, <40% pairwise identity, >40 functional families), classifying each as fRRM-silent or fRRM-disruptive over seven physicochemical metrics, with within-protein clustering handled explicitly (intraclass correlation, design effect, and a protein-level cluster bootstrap). We report two principal findings. First, across the full sample fRRM is essentially uncorrelated with every conformational determinant, namely Grant ham distance, hydropathy, molecular weight, and helix and sheet propensity (all |ρ|<0.1), establishing channel independence. Second, the silent-versus-disruptive contrast reproduces: disruptive substitutions are marginally more conformationally conservative on every metric, yet each difference, though statistically significant, is negligible in magnitude (|d|<0.2), a consistent but negligible-magnitude anti-correlated tendency, not a substantive coupling. The sequence-level state is therefore separable, a product state in HC⊗HS rather than an entanglement-like or complementary one, and this holds residue by residue (aspartate is the principal spectral hotspot, tryptophan is conserved structurally yet remains spectrally neutral). We interpret these results within the quantum-like framework: the protein is a dual-channel processor whose spectral "software" (frequency-domain recognition) can be updated independently of its conformational "hardware" (spatial binding), providing the separable substrate that quantum-like molecular decision-making requires.
Acute sympatho-excitation increases peripheral blood pressure (BP) through sympathetically mediated vasoconstriction. Aortic BP and pulsatile hemodynamics are stronger predictors of cardiovascular risk and outcomes compared to brachial BP. How pulsatile hemodynamics respond to sympatho-excitation and the impact on aortic BP are incompletely understood. The purpose of this study was to assess the effects of maximal voluntary apnea and the cold pressor test (CPT) as sympatho-excitatory perturbations on aortic BP and measures of pulsatile hemodynamics. Radial artery pressure waves were acquired at rest and during maximal voluntary end-expiratory apnea, end-inspiratory apnea, and the CPT in 28 healthy young adults. Radial artery pressure waves were transformed into aortic pressure waves and underwent wave morphology, wave separation, and pressure time integral analyses. Aortic systolic BP and augmentation index (a surrogate measure of wave reflection) increased during end-inspiratory (100±7 vs. 110±14 mmHg; 15±12 vs. 24±11%, both p<0.001) and end-expiratory apnea (100±10 vs. 111±12 mmHg; 12±13 vs. 21±12%, both p<0.001). Reflection magnitude (42±7 vs. 48±6%, p<0.001) and wasted pressure effort relative to the product of flow and aortic characteristic impedance pressure-time integral ratio (WPE:QZc, 45±18 and 62±19 %, p<0.001) increased during the CPT. Change in backward pressure wave amplitude was the only significant predictor of the change in aortic systolic BP across apneas and the CPT models. The apnea-chemoreflex (via voluntary breath holds) and nociceptive pain response (via the CPT) increased measures of arterial wave reflection which played a significant role in increasing aortic systolic BP in healthy young adults.
This study examined the associations among social rejection, self-compassion, and self-esteem among university students in Pakistan. Drawing on Sociometer Theory as a general conceptual framework, the study explored whether self-compassion was indirectly associated with the link between perceived social rejection and self-esteem. A cross-sectional design was employed with a convenience sample of 301 students recruited from public and private universities in Pakistan. Participants completed the Social Rejection Scale, the Short Form of the Self-Compassion Scale (SCS-SF), and the Rosenberg Self-Esteem Scale (RSES). Data were analyzed using Pearson correlation, hierarchical regression, and bootstrapped mediation analyses. Social rejection was negatively associated with both self-compassion and self-esteem, whereas self-compassion was positively associated with self-esteem. The indirect association between social rejection and self-esteem through self-compassion was statistically significant and consistent with a pattern of partial mediation. However, given the cross-sectional design, the findings should be interpreted as patterns of association rather than evidence of causal relationships. The magnitude of the indirect association was modest, suggesting that additional psychological processes may also be relevant to understanding how individuals respond to experiences of social rejection. Although the study was conducted among Pakistani university students, cultural variables were not directly measured. Consequently, cultural interpretations should be understood as contextual considerations rather than as evidence of culturally specific mechanisms. Overall, the findings suggest that social rejection, self-compassion, and self-esteem are related in ways that are broadly consistent with existing theoretical perspectives and prior empirical research. Future studies employing longitudinal, multi-method, and culturally informed approaches may help clarify the direction and nature of these associations.
Rice grains largely depend on nitrogen (N) remobilization from leaves. However, the dynamics of N species in source (leaf) and sink (grain) tissues and the effects of the external N supply remain unclear. This study investigated the dynamic changes and metabolic characteristics of major N fractions in flag leaves and grains under high-nitrogen (HN) and low-nitrogen (LN) treatments during grain filling. The concentrations of grain nitrate-N (NO₃⁻-N) and amino acid-N (AAs-N) decreased, whereas ammonium-N (NH₄⁺-N) showed dynamic changes, leading to an increased proportion of inorganic N (IN). The total N (TN) in the grain was negatively correlated with NO₃⁻-N but positively correlated with NH₄⁺-N (LN: r = 0.75; HN: r = 0.92). In flag leaves, only NO₃⁻-N increased. Despite similar overall trends, the magnitudes of these changes varied among the N treatments. The grain TN was predominantly supported by AAs-N: under HN, AAs-N accounted for 74.1-50.0%, which consistently exceeded IN (25.9-49.9%); in contrast, under LN at the middle-to-late stages, IN (50.2-69.7%) exceeded AAs-N (49.8-30.3%). HN strengthened the positive correlation between grain NH₄⁺-N and TN, whereas LN intensified the correlations among the leaf N fractions. LN accelerated TN and AAs-N degradation and promoted NO₃⁻-N accumulation and N remobilization in leaves. Furthermore, LN upregulated grain N-assimilating enzymes and leaf NiR, whereas HN maintained relatively high leaf NR and GS. Transcriptomic analysis revealed that hormone signals were involved in regulating rice N metabolism. During rice grain filling, NO₃⁻-N, NH₄⁺-N, and AAs-N in grains and leaves dynamically changed and were differentially regulated by enzyme activity and gene expression, ultimately clarifying source‒sink nitrogen dynamics for optimized nitrogen management.
Combining optical and magnetic functionalities into memristors is an attractive option to expand applications into image recognition, information storage, and low power processing. Here, we have fabricated ferromagnetic-fullerene-manganese oxide structures that display a hysteretic, nonlinear I-V characteristic and a photovoltaic effect with a photocurrent dependent on the relative alignment of the magnetization and the light polarization vector. Reversible, voltage-induced oxygen migration from manganese oxide into the molecular layer reduces the resistivity of the device by several orders of magnitude, eliminates the nonlinear transport, and quenches the photovoltaic response, giving rise to an optically sensitive memristor where the photocurrent is dependent on both the electrical and magnetic history of the device. Density functional theory calculations attribute the origin of these effects to changes in the electronic structure at the Fermi level and a reduction of the interface dipole upon ionic migration. These results open research pathways towards single-molecule scale memristive memories with optical excitation, electrical readout and magnetic sensing functionalities.
The mandibular third molar (MTM) is frequently present in mandibular angle fractures treated with the Champy technique. Clinical research on MTM management has focused predominantly on postoperative complications, and several studies have suggested that retention may confer a stabilizing effect on the fracture - the so-called "splinting effect" proposed by Wolujewicz. However, this stabilizing role has never been quantitatively verified at the biomechanical level, and the geometric feature of the retained tooth responsible for this effect has not been identified. The aim of this theoretical biomechanical study was to test, by means of finite element analysis (FEA), whether a retained MTM improves the mechanical stability of Champy fixation across a range of impaction types, and to identify the key geometric determinant of any such effect. A mandibular finite element model was constructed from the cone-beam computed tomography data of an adult volunteer. Ten impaction configurations were established by combining three Pell and Gregory depth positions (A, B, C) with four Winter angulations (mesioangular, distoangular, vertical, horizontal). For each configuration, an MTM-retained and an MTM-extracted model were created, yielding 20 models in total. All models shared identical boundary conditions, material properties, and loading (bilateral molar clenching, 230 N). The primary outcome was interfragmentary displacement; secondary outcomes included plate and screw von Mises stress and proximal cortical bone maximum principal strain. Six candidate geometric variables of the retained tooth were measured and related to the stabilizing contribution (the percentage increase in displacement upon extraction) using descriptive correlation analysis. In all ten impaction configurations, the MTM-retained model exhibited a smaller interfragmentary displacement than its extracted counterpart. Extraction increased displacement by 68%-172%, and this pattern was corroborated by consistent increases in plate stress (26%-61%), screw stress (23%-55%), and cortical bone strain (10%-47%). Among the geometric variables examined, the trans-fracture cross-sectional area of the tooth - the area of its cross-section at the fracture plane - showed the strongest association with the stabilizing contribution (r = 0.86, ρ = 0.79), whereas volume-based measures, including mesial segment volume (r = 0.14), were substantially weaker. Impaction depth and angulation did not act as independent determinants; configurations spanning all three depth positions followed a common cross-sectional-area trend. Under the conditions of this finite element model, retention of the MTM was associated with improved biomechanical stability of Champy fixation in every impaction configuration studied. The magnitude of this stabilizing effect was governed primarily by the cross-sectional area of the tooth at the fracture plane rather than by the conventional angulation- or depth-based classifications, which appeared to act only indirectly through the cross-section they produce. These findings are theoretical and derived exclusively from computational simulation; they require corroboration by in vitro testing and prospective clinical studies before informing clinical decision-making.
Current understanding of the role of ocean variability in air-sea exchange is constrained to large and mesoscale dynamics. Oceanic fronts and filaments with horizontal spatial scales of order 0.1 to 10 km-denoted submesoscale-are challenging to observe due to their fast-evolving flow and small spatiotemporal scales of variability. Observations investigating the air-sea fluxes at the submesoscale have shown substantial fluxes of heat, moisture, and momentum, affecting the structure of the overlying atmosphere. Here, modulations of the turbulent atmospheric boundary layer driven by ocean temperature anomalies are investigated using submesoscale-resolving ship and airborne measurements, providing in situ evidence of the atmospheric response to ocean submesoscale temperature variability. Observations suggest near-surface turbulent mixing driven by strong air-sea fluxes of heat and momentum, modifying the vertical structure of the planetary boundary layer. Linear regression coefficients between wind speed and sea surface temperature anomalies reveal a response similar in magnitude to that seen at larger scales, with an integrated change of 0.23 m s-1 °C-1, but occurring over smaller length-scales, implying sharper gradients. Lagged correlations and scaling analysis imply a combined influence of horizontal advection and vertical turbulent mixing of momentum in the atmosphere, previously only described by numerical simulations. Observed cross-frontal wind divergences over the lower 200 m suggest coherent circulations with vertical velocities of order 1 cm s-1. These observations confirm the rapid adjustment of the marine boundary layer to submesoscale ocean temperature variability and the importance of submesoscale-driven air-sea fluxes in changing the properties of the lower atmosphere, processes not resolved in most forecasting and prediction models.
AI is transforming medicine by enhancing care, reducing administrative tasks, and facilitating research. AI also raises many concerns, including a lack of clinical context awareness, data dependence, and the absence of ethical judgment. As future practitioners, medical students must be prepared for these changes. Most studies assessing students' attitudes and knowledge were conducted before AI became accessible and tailored to the needs of the population. Therefore, how medical students actually use AI remains largely unexplored. This study aimed to explore French medical students' perceptions, attitudes, and use of AI. A mixed methods study was conducted in 2025 among French medical students in their clerkship year. An online survey included open-ended questions about the definition of AI and feelings toward AI, a Likert scale item to assess specific attitudes, and multiple-choice questions about student characteristics. Quantitative analysis was performed using Kruskal-Wallis tests, chi-square tests, and exploratory multivariable linear regression to examine associations between AI knowledge, attitudes, and student characteristics. Qualitative thematic analysis was conducted inductively on open-text responses regarding perceptions of AI, feelings, training expectations, and use. Of the 1377 responses received, 1342 were included. Students had a median age of 23 (IQR 22-24) years and were predominantly in their fifth year. Only 5% (67/1342) provided a correct definition of AI, while 57.4% (770/1342) gave incorrect responses. Attitudes toward AI were generally positive, with a median score of 7 (IQR 5-8). Students with unknown AI definitions had significantly lower attitude scores (P=.02), although the magnitude of the difference was small (ε²=0.005). In multivariable analysis, belonging to the unknown AI definition category remained associated with a lower general attitude toward AI score compared with the incorrect category (regression coefficient β=-0.72, 95% CI -1.17 to -0.28; P=.001). Regarding education, 48.5% (651/1342) of students preferred AI training outside the formal curriculum. Qualitative analysis revealed 5 themes: representation, nuanced optimism, critical consideration, replacement, and AI use. Students describe AI as a robot, an improved search engine, or an unlimited data source. Their nuanced optimism blends enthusiasm for efficient patient care and the opportunity to focus more on the patient relationship, with concerns about dehumanization, energy costs, and skill regression. Critical consideration underscores distrust from ethical dilemmas and data security risks. Replacement concerns arise from shifting professional roles, though many believe human empathy remains irreplaceable. Regarding AI use, students highlight its potential for administrative aid, personalized training, and clinical support. Medical students report generally positive but varied attitudes toward AI, despite having a limited understanding of its foundations. Ecological concerns, fears of skill loss, and ethical issues coexist with widespread self-directed use of AI for learning. These findings provide a descriptive baseline for future evaluations of AI-related training, particularly regarding critical appraisal, ethical issues, and self-directed AI use.
Systemic sclerosis (SSc) is a rare autoimmune disease characterized by vasculopathy and fibrosis of the skin and internal organs. Individuals with SSc often suffer from chronic acid reflux and dysphagia due to loss of esophageal motility. However, the pathogenesis of esophageal dysmotility in SSc is poorly understood. To determine whether distinct changes in esophageal epithelial cells contribute to esophageal involvement in SSc, we investigated the stratified squamous esophageal epithelium from proximal and distal biopsies using single-cell RNA sequencing (n=306,372 cells) in individuals with SSc compared those with gastroesophageal reflux disease (GERD) and healthy controls. The proportion of epithelial cells in the apical, superficial compartment of the esophageal epithelium was reduced in SSc (9.4% vs 21.6% in HCs). Differential gene expression in SSc was primarily limited to the superficial compartment (3,572 genes vs. 232 in all other compartments, based on pseudobulk analysis), with significant upregulation of extracellular matrix and keratinization genes. These cellular and molecular changes in SSc were highly correlated with those seen in GERD, indicating they were secondary to reflux; however, their magnitudes were more pronounced in the proximal esophagus, suggesting that esophageal dysmotility leads to greater proximal acid exposure, which may contribute to aspiration. SSc-specific gene dysregulation implicated immunoregulatory pathways likely pertinent to pathogenic mechanisms. Ligand-receptor interaction analysis revealed enhanced pro-fibrotic signaling between fibroblasts and epithelial cells in SSc. Cell type localization and SSc-specific changes were confirmed by spatial molecular imaging. By offering a comprehensive view of transcriptional dysregulation at single-cell resolution in human esophageal epithelial cells in SSc compared to GERD and healthy tissue, this work clarifies the state of epithelial cells in SSc-induced esophageal dysfunction.
Per- and polyfluoroalkyl substances (PFAS) are persistent synthetic compounds that have contaminated millions of hectares of agricultural land through decades of biosolids application. Conventional remediation approaches, such as thermal destruction or excavation, are prohibitively expensive, carbon intensive, and leave affected farmland unfit for agriculture. Here, we present a potential scalable remediation strategy that combines phytoremediation, biochar production, and enhanced weathering to simultaneously remove PFAS from soil, immobilize residual contamination, and achieve durable carbon dioxide removal (CDR). Using stochastic modeling constrained by experimental data, we show that soil pH management through alkaline rock amendment can accelerate PFOS removal, shortening remediation timelines by more than a decade under typical contamination levels. Pyrolysis of harvested biomass effectively destroys PFAS and produces biochar, which, when reapplied to soil, substantially reduces leaching to groundwater and the surrounding environment. National-scale simulations across the estimated one million hectares of PFAS-impacted cropland indicate a combined CDR potential of approximately 11 Mt CO2 y-1, equivalent to 4 to 6% of the US 2050 carbon removal target. We estimate a median remediation cost of $1,460 USD ha-1 y-1-more than an order of magnitude lower than current technologies, with costs substantially reduced through carbon removal revenues valued near the social cost of carbon. This integrated thermal and phytoremediation framework provides a viable pathway to restore contaminated farmland, mitigate PFAS exposure risks, and contribute meaningfully to national climate mitigation goals.
Programmed death receptor 1 (PD-1) blockade produces high response rates in resectable and locally advanced cutaneous squamous cell carcinoma (CSCC), but how many doses are needed and whether surgery or radiation after immunotherapy (consolidation) adds benefit in deep responders (patients with substantial clinical responses) remain unclear. Observational inference is challenging because treatment decisions are response-guided, doses accumulate over time, and treatment selection depends on patient characteristics that also affect outcomes. We conducted a retrospective cohort study of 189 patients with resectable, borderline-resectable, locally advanced, or limited metastatic CSCC treated with immune checkpoint inhibitors as part of management (2019-2025). We summarized responses, treatment discontinuation patterns, and time-to-event outcomes. To evaluate dose-response relationships, we fit Bayesian regression models adjusting for prespecified baseline confounders. Directed acyclic graphs were used to formalize causal assumptions and identify minimally sufficient adjustment sets. For event-free survival (EFS), we used a prespecified landmark analysis among patients receiving ≥2 doses to reduce guarantee-time bias. Objective response occurred in 119/189 (63%), including 52/189 (27.5%) complete responses. Nearly half of patients received ≤2 doses (92/189, 48.7%). Among 50 complete responders managed without surgery, 1 recurrence was observed over a median follow-up of 25.4 months. Dose-response models showed a consistent but modest positive association between additional doses and response: in a linear model, each additional dose was associated with ~1.09 fold higher odds of response (posterior probability >95%). Flexible threshold models suggested early concentration of benefit, strongest at 2 versus 1 dose (93.6% posterior probability of benefit), with persistent uncertainty in effect magnitude (66% probability of ≥6 percentage-point absolute increase). In the EFS landmark modeling cohort (n=177), receipt of ≥3 versus 2 doses showed a 93% posterior probability of reduced event risk, but the 89% credible interval spanned the null (HR 0.61-1.01), indicating substantial uncertainty regarding incremental downstream benefit. In real-world CSCC, durable disease control frequently occurred after limited immunotherapy exposure, and clinical responders often did well without routine surgical consolidation. Although additional doses may modestly improve outcomes, observed gains appear concentrated early with uncertain incremental value beyond two doses. These patterns support conceptualizing treatment as frontline immunotherapy with response-guided subsequent treatment rather than fixed-duration neoadjuvant therapy.
To determine whether the presentation sequence of natural and bleached-shade options influences patient shade selection and to evaluate the association between the psychosocial impact of dental esthetics (PIDAQ) and final selected shade lightness. In this three-arm randomized controlled trial, 210 participants seeking esthetic dental treatment were randomized to three shade-presentation protocols: Group A (natural → bleached), Group B (bleached → natural), or Group C (simultaneous full range with confirmation). Participants completed the psychosocial impact of dental esthetics questionnaire (PIDAQ) prior to shade selection. Initial "first-impression" and final shade selections were recorded using the VITA 3D-MASTER system with bleached tabs (0M1-5M3). Primary outcomes included switching between selections, lightness change (ΔL), and the association between PIDAQ and final selected lightness (final L). Secondary outcomes included bleached-shade selection, color-difference discrepancies (ΔE00) versus objective baseline and clinician recommendation, and patient-reported rationale. Presentation protocol significantly affected switching frequency, ΔL* direction and magnitude, and bleached-shade selection (all p < 0.001). Switching was highest in Group A (31.4%) and lowest in Group C (1.4%). ΔL* showed protocol-dependent direction: a net shift toward lighter shades in Group A (+2.10) and toward darker shades in Group B (-0.93). Bleached-shade selection was most frequent in Group B (84.3%) and least frequent in Group A (31.4%). Higher PIDAQ scores were independently associated with lighter final selections (p < 0.001), with a significant Group × PIDAQ interaction (p = 0.006), indicating that the strength of this association varied by presentation protocol. Patient-clinician color discrepancies (ΔE00) were smallest in Group A (7.68) and largest in Group B (16.24). Shade guide presentation sequence is a modifiable determinant of patient esthetic preference and decision stability. Patients with a higher psychosocial impact related to dental appearance prefer lighter shades, but this preference is modulated by how options are presented. A structured protocol presenting the full shade range with a confirmation step minimizes decision volatility and may enhance patient-clinician alignment. Standardizing shade visualization by presenting the complete shade range consistently and incorporating a brief confirmation step can improve the predictability and transparency of patient-centered esthetic shade selection. Clinicians should be aware that early exposure to bleached options may unintentionally nudge patients toward lighter choices, particularly those with greater psychosocial concerns about their dental appearance.
Organic ferroelectrics offer a molecular platform for integrating polarization dynamics with molecular design, photoresponsiveness and chiroptical functions, including light-triggered achiral-to-chiral transitions, yet these responses remain strongly shaped by crystalline packing in the solid state. Here, we vitrify a salicylideneaniline derivative that undergoes UV-triggered achiral-to-chiral conversion and show that structural disorder enables coupled chiroptical and ferroelectric responses in an amorphous molecular solid. The vitrified state loses long-range order while retaining spatially heterogeneous local polar responses, giving a coercive field of ~5.7 kV cm⁻¹ and a maximum switchable polarization of ~26 μC cm⁻². It also exhibits over an order of magnitude faster recovery from the chiral photoactivated state than the crystalline counterpart. Moreover, circularly polarized light produces helicity-dependent dielectric and thermal responses with mirror-symmetric behavior between the (S)- and (R)-enantiomers. These results connect photoinduced symmetry switching with relaxor-like dipolar dynamics in a single-component amorphous molecular ferroelectric.
Global longitudinal strain (GLS) can detect subclinical dysfunction missed by left ventricular ejection fraction (LVEF). We aim to quantify the magnitude of myocardial dysfunction using GLS across the phases of Kawasaki disease (KD). We systematically searched for studies comparing GLS measurements between children with KD and age-matched controls. Effect sizes were pooled using a random-effects model and reported as standardized mean differences (SMD) for the acute and chronic disease phases. SMDs were re-expressed as mean differences (MDs) using pooled weighted standard deviations (SDs) of 2.75% and 1.89% for the control groups in the acute and chronic phases, respectively. We included 18 observational studies comprising 907 KD patients and 764 controls. KD patients demonstrated significant GLS depression compared with controls in both the acute (SMD: 1.34, 95% CI: 0.73, 1.95, p < 0.0001, I2 = 93%; MD: 3.6%) and chronic (SMD: 0.72, 95% CI: 0.20, 1.25, p = 0.007, I2 = 92%; MD: 1.9%) phases. LVEF was reduced in the acute phase (MD: -1.09%, 95% CI: -1.57, -0.61, I2 = 0%), and normalized in the chronic phase (MD: -0.27%, 95% CI: -1.18, 0.64, I2 = 36%). Multivariable meta-regression in the acute phase identified CRP (β = 0.02, p = 0.024) plus CAA patient proportion (β = -1.13, p = 0.069) explaining 49.28% of heterogeneity, whereas vendor platform (GE vs. Philips) (β = -1.02, p = 0.007) plus age at follow-up (β = 0.02, p = 0.019) explained 56.34% of heterogeneity in the chronic phase. Despite LVEF normalization in the chronic phase of KD, myocardial dysfunction persists. This could be essential for long-term monitoring algorithms.
Active metamaterials capable of autonomous shape change and on-demand property reconfiguration under environmental stimuli represent a rapidly growing class of intelligent structures. Origami-based designs are particularly attractive owing to their capacity for large deformations, programmable geometry, and kinematic reconfigurability. In existing active origami, however, stimuli-responsive materials are embedded only in the narrow crease regions, and therefore actuating capability and mechanical performance are predominantly governed by crease rotation, limiting the achievable folding ratio and performance tunability. To overcome these limitations, curved-crease origami is newly introduced as an active metamaterial design wherein folding is driven through panel bending. Folding kinematic analyses demonstrate that the elastic strain energy of the panels and creases is simultaneously minimized when circular arc creases are combined with orthogonal generators. Building on this geometric principle, a panel-driven actuation framework is established using high-modulus bimetallic strips. Further analysis confirms that this minimum-energy curved-crease origami configuration achieves a high conversion efficiency from actuation strain of material to active structural deformation strain. Circular sheets with curved zigzag patterns are then proposed that exhibit predictable thermally induced self-folding from a planar sheet into a compact wrapped cylindrical shape. By introducing Euler spiral creases, self-wrapping over multiple turns is realized with an area folding ratio of up to 19.1. Further extension to multilayer architectures yields active metamaterials that demonstrate three-dimensional shape transformations. The coupling of a soft mode dominated by crease folding and a stiff mode involving simultaneous crease folding and panel bending enables a stiffness tunability spanning three orders of magnitude, the widest range in active metamaterials to date. Therefore, this work broadens the design space of active metamaterials and offers new opportunities for applications in soft robotics, deployable structures, and medical devices.
Tacrolimus is a narrow therapeutic index drug with wide intrapatient and interpatient pharmacokinetic variability and cytochrome P450 3A5 (CYP3A5) genotype-guided dosing recommendations. This review aimed to evaluate population pharmacokinetic models and dosing algorithms across all treatment settings that analyzed the influence of CYP3A5 genotypic variation plus additional clinical covariates on tacrolimus pharmacokinetics. These effects were mathematically translated and summarized to provide a comparison between models. Changes in apparent clearance warranting tacrolimus dose adjustments were assessed and summarized by relative magnitude and direction. Sixty-eight tacrolimus population pharmacokinetic models were included in this review, including 55 developed for adults and 38 for kidney transplant recipients. The most frequently retained covariates on tacrolimus clearance were CYP3A5 genotype (88%), body size (29%), hematocrit (29%), and days since transplant (28%). The median fold increase in apparent clearance, across all treatments, was 1.64 for CYP3A5 normal and intermediate metabolizer patients compared to poor metabolizer patients. As days since transplant increased, median tacrolimus apparent clearance increased in liver (n = 6) and lung transplant (n = 2) models but decreased early post-transplant and then subsequently increased in kidney transplant models (n = 11). Concomitant administration of tacrolimus with -azole antifungals or Wuzhi capsules was associated with reduced tacrolimus apparent clearance (38% and 31%, respectively), while corticosteroids were associated with a 23% increase in apparent clearance. Based on our analysis, a substantial tacrolimus dose increase (≥ 75%) is required for CYP3A5 normal and intermediate metabolizer patients compared with poor metabolizer patients. Ultimately, these findings can be used to determine optimal personalized tacrolimus doses across a variety of disease states and treatment types.
Visual mental imagery is the process of reconstructing perceptual experience without sensory input. How the brain performs this process is poorly understood, particularly from the perspective of conventional linear EEG analysis. This study aims to evaluate if the two non-linear EEG complexity measures-Lempel-Ziv Complexity (LZC) and Higuchi Fractal Dimension (HFD)-can differentiate between perception and imagination and if they can be used as objective indices of neural separability of mental imagery. LZC and HFD were extracted from 62 scalp EEG channels in 46 healthy adults performing the PerceiveImagine paradigm (Li and Fan 2024), after wideband Picard ICA decomposition (1-200 Hz), which was used to make residual artefacts explicit rather than to remove components, with edge-channel EMG monitoring for artefact control. Statistical analyses included cluster-based permutation testing (Maris and Oostenveld 2007), Hotelling T², and leave-one-subject-out cross-validation (LOSO-CV). Broadband LZC topography differed between perception and imagination (cluster p = 0.005; Hotelling F = 3.08, p = 0.002, V = 0.28). LOSO-CV classification reached AUC = 0.811 (95% CI: [0.775, 0.847]). The classifier's AUC exceeded a label-permuted baseline by a wide margin (t(45) = 16.30, p < 0.001). The a priori low-gamma LZC hypothesis was not supported, with no significant difference at the occipital ROI (p = 1.0, d = - 0.13). At the scalp level, EEG complexity features are associated with a topographic redistribution rather than a global magnitude change: imagery shows a relative posterior-to-frontal shift in broadband LZC. Because these patterns are scalp-recorded, they characterise the spatial distribution of complexity rather than establishing the underlying cortical sources or the direction of information flow. Objective decoding-confidence labels provide a more usable training signal than the (invariant) self-report available in this dataset, indicating future potential for imagery-quality indexing rather than immediate translational readiness.