Diet plays a critical role in development and progression of Crohn’s disease (CD). Dietary indices are important tools to evaluate diet quality and inflammatory potential, and we investigated their associations with pediatric CD in comparison to healthy children. A cross-sectional study including 144 children with CD (122 with clinically active and 22 with quiescent disease) and 57 healthy controls 6-18 years of age was conducted. Dietary intake was estimated using three 24-h dietary recalls. Diet quality was assessed using the Healthy Eating Index (HEI)-2015, alternate Mediterranean diet (aMed) score and dietary inflammatory potential using the modified Children-Dietary Inflammatory Index (mC-DII). Children with active CD had lower total HEI-2015 and aMed scores than healthy controls. A similar pro-inflammatory mC-DII score was found across the three groups. A higher mC-DII score in patients with CD was associated with higher intake of refined sugars, saturated fats and proteins, and lower intake of whole grains and dairy, highlighting dietary components contributing to pro-inflammatory potential. Similarly, healthy children in the highest mC-DII tertile consumed more added sugars and sodium and fewer whole grains, fruits, vegetables, and plant proteins. Fiber intake was significantly lower in children with active CD (median fiber %DRI: 37.0 IQR [22.6-48.3] vs 41.2 IQR [34.1-49.1] vs 45.8 IQR [35.7-62.0], P <0.001). Using three dietary indices to evaluate diet quality and dietary inflammatory potential, both children with CD and healthy children in this cohort consume a poor-quality, pro-inflammatory diet low in fiber, but the quality and fiber content are significantly lower in children with active CD. Future randomized controlled trials are required to evaluate the effect of dietary modification on the risk and progression of pediatric CD.

This study examined how the location of silent pausing (mid- vs. end-clause) may relate to neural processes during spontaneous L1 and L2 speech production. Twenty intermediate-level Japanese speakers of L2 English carried out eight monologic, oral decision-making tasks, four in English and four in Japanese. While completing the tasks, their brain activity was recorded through fMRI scanning. Participants’ speech was transcribed, and the resulting transcripts were annotated for mid- and end-clause silent pauses. Then, for the pauses identified, we conducted whole-brain analyses to identify relevant activation patterns, followed by region-of-interest analyses in language-related areas. We found that mid-clause pauses were linked to increased activation in language-related brain regions, with stronger effects for L2 speech. We also observed heightened activity in conceptualisation-related brain areas at end-clause positions in both L1 and L2 speech. In L2 English, participants also displayed greater activation in a concept-retrieval-related brain region in end-clause than in mid-clause position.

This study examines the interaction between regularity and complexity in the acquisition of morphology and morpho-syntax in Hebrew nominal inflection. Seventy-eight Hebrew-speaking children, ages 4–8, were tested, using sentence completion tasks, on nine structures from three linguistic systems: singular adjectival agreement, noun pluralization, and plural adjectival agreement. Regularity and complexity emerged as organizing factors across ages: regular structures precede irregular ones, and within each level of regularity, less complex structures were acquired before more complex ones. The findings are discussed within the Dual-Route Model pointing to the difference between rule-governed and memory-based knowledge, while suggesting that the advantage of regularity could be attributed to frequency as well as to the strength of regularity cues in language acquisition, as proposed by Usage-Based models. The advantage of less complex structures over more complex ones is accounted for by the greater cognitive and linguistic effort required to acquire the latter.

Judicial rulings on expert evidence determine which specialized knowledge enters the courtroom and, in doing so, shape the credibility of litigants and the legitimacy of their claims. This article examines how disparities in litigant status shape the judicial gatekeeping of expert evidence and how this process relates to the ideological context of the legal forum. Using data from a probability sample of 811 Daubert rulings from United States District Courts, our multinomial logistic regression models show that, overall, higher status litigants are more successful in excluding opposing evidence and in overcoming exclusionary motions. However, this aggregate relationship masks a pronounced ideological divide. Specifically, higher status litigants tend to be more successful in cases assigned to conservative judges while lower status litigants tend to be more successful in cases assigned to liberal judges. These findings illustrate how trial court decisions reflect broader institutional and ideological forces and suggest that ideological contexts can either amplify or temper structural inequalities in the courtroom.

In recent years, b-symplectic manifolds have emerged as important objects in symplectic geometry. These manifolds are Poisson manifolds that exhibit symplectic behaviour away from a distinguished hypersurface, where the symplectic form degenerates in a controlled manner. Inspired by this rich landscape, E-structures were introduced by Nest and Tsygan in [NT01] as a comprehensive framework for exploring generalizations of b-structures. This paper initiates a deeper investigation into their Poisson facets, building on foundational work by [MS21]. We also examine the closely related concept of almost regular Poisson manifolds, as studied in [AZ17], which reveals a natural Poisson groupoid associated with these structures.

In this article, we investigate the intricate relationship between E-structures and almost regular Poisson structures. Our comparative analysis not only scrutinizes their Poisson properties but also offers explicit formulae for the Poisson structure on the Poisson groupoid associated to the E-structures as both Poisson manifolds and singular foliations. In doing so, we reveal an interesting link between the existence of commutative frames and Darboux-Carathéodory-type expressions for the relevant structures.

The rise of Generative AI has accelerated the shift toward Industry 5.0, marking a critical transition from the technology-centric focus of Industry 4.0 to a human-centric, value-driven paradigm. While its predecessor prioritized automation and technology, Industry 5.0 integrates advanced human–machine collaboration with social imperatives to create resilience. This study advances current literature by presenting a novel systems-based framework, grounded in systems theory and legitimacy theory, which conceptualizes Industry 5.0 as an interconnected ecosystem rather than isolated pillars. We identify technological adaptation, specifically AI integration, and human-centricity as critical inputs that drive economic, environmental, and social sustainability as systemic outputs. By mapping these interdependencies, the model demonstrates how cohesive components collectively fuel organizational transformation. These findings offer actionable insights for aligning corporate strategies with Sustainable Development Goals, providing policymakers and practitioners with future-oriented pathways to navigate this complex, emerging industrial environment.

Proponents of modal knowledge accounts (safety and sensitivity) concur that one crucial advantage of their accounts is that they solve the so-called lottery problem—the problem of explaining why “lottery beliefs” based merely on statistical evidence do not constitute knowledge. Contra this claim, I argue that epistemic judgments about lottery beliefs do not consistently track what occurs in a specified set of nonactual possibilities. Thus, modal knowledge accounts cannot properly explain beliefs based merely on statistical evidence. Finally, I argue that these beliefs can be better accommodated by a rival theory of modal accounts—namely, explanationism.

We always treat fluent language as a marker of intelligence and trustworthiness, often independent of factual accuracy. Large language models (LLMs) exploit this bias by producing confident, human-like texts that are perceived as intelligent and trustworthy, even when they lack accurate contextual understanding or are factually incorrect. This creates particular risks in mental healthcare, where communication, trust and context are central, and where errors are difficult to detect but highly consequential. This article examines how linguistic fluency shapes judgement, how LLMs amplify these effects and why their use in mental healthcare poses ethical and clinical dangers. It argues for strict limits on deployment, restricting LLMs to supervised, assistive tasks rather than clinical judgement.