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This study compared health status and developmental skill acquisition of children aged 3–5 years with and without CHD and identified predictors of special education or early intervention plan.
Materials and methods:
Data were analysed from the 2022 National Survey of Children’s Health using complex weighted survey data procedures. Chi-square tests compared health status and developmental skill acquisition of children aged 3–5 years with and without CHD. Multivariate logistic regression identified predictors of the need for special education or early intervention plan.
Results:
11,097 National Survey of Children’s Health responses pertained to children aged 3–5 years. Children aged 3–5 years with CHD were more likely than heart-healthy peers to be born prematurely, have special healthcare needs, have parent-reported health as “fair” or “poor,” be diagnosed with anxiety, depression, or a developmental disorder, and receive special education or an early intervention plan. Children aged 3–5 years with CHD were less likely to have acquired communication, fine motor, personal social, and problem-solving skills than comparators at the time of the survey, even after adjustment for special healthcare needs. Having public plus private insurance, special healthcare needs designation, and a developmental disorder predicted children aged 3–5 years needing special education or an early intervention plan.
Conclusion:
Children with predictors of receiving special education or an early intervention plan may benefit from early identification and support. Further research should investigate the impact of systemic disparities on developmental skill acquisition in children with CHD.
The politics of knowledge production is a long-standing debate at the heart of the discipline of international relations (IR). The importance of the IR classroom as a site of the politics of knowledge production in the discipline has long been emphasized by critical and feminist IR scholars and has recently received renewed interest. In this article we contribute to this debate through an analysis of the ways in which learner-generated films contribute to address knowledge production politics. Inspired by the distinction between knowledge production and knowledge cultivation, we propose that the practice of knowledge cultivation through filmmaking in the IR classroom can serve as a compass and generates openings to ‘stay with the trouble’ of creating knowledge. We draw on insights from our experience with learner-generated films and from a dialogue with the literature on the politics of knowledge production in IR; visual and arts-based theorizing in IR; and the interdisciplinary literature on filmmaking. The article addresses three key dimensions of the politics of knowledge production: the ethics and politics of filmmaking; affect and embodiment of creating knowledge through films; and non-textual theorizing through filmmaking.
Schizophrenia (SCZ) shows marked biological heterogeneity, with negative symptoms linked to poor outcomes and hypothesized immune dysregulation. This study examined whether a peripheral cytokine–long non-coding RNA (lncRNA) panel could distinguish patients with SCZ and Brief Negative Symptom Scale (BNSS)-defined subgroups from healthy controls (HC).
Methods:
Forty-one hospitalized patients with SCZ completed the BNSS and the Positive and Negative Syndrome Scale (PANSS). Twenty HCs, frequency-matched for age and sex, served as comparison samples. Severe negative-symptom subgroups were defined using two BNSS criteria: a broader (SNS1) and a more restrictive (SNS2) threshold. Serum cytokines—interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), interleukin-10 (IL-10)—and leukocyte lncRNAs (MALAT1, NEAT1, MEG3) were quantified by enzyme-linked immunosorbent assay and quantitative RT-PCR. Covariate-adjusted logistic and multinomial models (adjusting for age, sex, body mass index, and smoking) assessed discrimination using area under the receiver-operating-characteristic curve (AUC) and interquartile-range odds ratios (OR_IQR).
Results:
IL-6 correlated with PANSS Total (ρ = .48, p = .001) and Negative (ρ = .34, p = .032) scores and was higher in SCZ than HC (p = .033), with further increases in SNS subgroups. NEAT1 was significantly reduced only within BNSS-defined subgroups (p ≤ .025). The dual-marker pattern (IL-6 ↑, NEAT1 ↓) showed the strongest discrimination for SNS1 versus HC (AUC = 0.85) and the steepest multinomial contrasts for SNS2 (IL-6 OR_IQR = 4.98; NEAT1 OR_IQR = 0.11).
Conclusions:
Elevated IL-6 and decreased NEAT1 define a peripheral signature linked to negative-symptom severity in SCZ and may support biologically informed stratification and longitudinal research.
We investigate positivity and probabilistic properties arising from the Young–Fibonacci lattice $\mathbb {YF}$, a 1-differential poset on words composed of 1’s and 2’s (Fibonacci words) and graded by the sum of the digits. Building on Okada’s theory of clone Schur functions, we introduce clone coherent measures on $\mathbb {YF}$ which give rise to random Fibonacci words of increasing length. Unlike coherent systems associated to classical Schur functions on the Young lattice of integer partitions, clone coherent measures are generally not extremal on $\mathbb {YF}$. Our first main result is a complete characterization of Fibonacci positive specializations – parameter sequences which yield positive clone Schur functions on $\mathbb {YF}$. Second, we establish a broad array of correspondences that connect Fibonacci positivity with: (i) the total positivity of tridiagonal matrices; (ii) Stieltjes moment sequences; (iii) the combinatorics of set partitions; and (iv) families of univariate orthogonal polynomials from the (q-)Askey scheme. We further link the moment sequences of broad classes of orthogonal polynomials to combinatorial structures on Fibonacci words, a connection that may be of independent interest. Our third family of results concerns the asymptotic behavior of random Fibonacci words derived from various Fibonacci positive specializations. We analyze several limiting regimes for specific examples, revealing stick-breaking-like processes (connected to GEM distributions), dependent stick-breaking processes of a new type, or limits supported on the discrete component of the Martin boundary of the Young–Fibonacci lattice. Our stick-breaking-like scaling limits significantly extend the result of Gnedin–Kerov on asymptotics of the Plancherel measure on $\mathbb {YF}$. We also establish Cauchy-like identities for clone Schur functions whose right-hand side is presented as a quadridiagonal determinant rather than a product, as in the case of classical Schur functions. We construct and analyze models of random permutations and involutions based on Fibonacci positive specializations along with a version of the Robinson–Schensted correspondence for $\mathbb {YF}$.
We study bond and site Bernoulli percolation models on $\mathbb{Z}^d$ for $d \geq 3$ with parameter p, in both the oriented and non-oriented versions. The main macroscopic quantity of interest is the probability of long-range order, and the existence of a non-trivial threshold is well established. Precise numerical results for the threshold values are available in the literature, but mathematically rigorous bounds are mostly restricted to two-dimensional lattices. Utilizing dynamical coupling techniques, we introduce a comprehensive set of new rigorous upper bounds that corroborate existing numerical values.
Scanning electron microscopy (SEM) methods are widely used in the geosciences to determine grain shape and surface characteristics using SEM–secondary electron and backscatter imagery (SEM-SE/BSE) and elemental composition of minerals using SEM–energy dispersive X-ray spectroscopy (SEM-EDS). We discuss applications and best practices for utilizing widely available SEM methods for luminescence dating, including (1) checking sample purity following mineral separation, (2) imaging grain shape and surface characteristics related to weathering and transport, (3) quantifying feldspar-mineral phases in feldspar separates, and (4) determining internal potassium concentration (wt% K) in feldspars for use in estimating internal beta contribution to the dose rate for a sample.
Quartz and feldspar purification checks of mineral separates require the least sample preparation and instrument time. These methods utilize the “environmental” or “low-vacuum” conditions of SEM. These conditions are less conducive to acquiring high-quality compositional data but can be used to quickly determine sample purity.
Conversely, to acquire higher-quality compositional data, SEM working conditions require high vacuum and accelerating voltages. The resulting semiquantitative SEM-EDS results can be used to determine the phase composition of feldspar separates and more accurately determine the internal potassium content for dose-rate and age calculations.
Post-Dobbs v. Jackson, abortion regulation is left entirely to the states. Laws that restrict access to abortion generally allow for exceptions when determined necessary for the life or safety of the pregnant patient. Some states, e.g., Ohio, use a “subjective” legal standard when determining whether an abortion is medically necessary. Other states, e.g., Texas, rely on an “objective” legal standard, whereby the necessity of an abortion is not determined by any particular physician’s judgments, but rather by the judgment of a hypothetical “reasonable physician.” Though objective legal standards are widespread in American jurisprudence, they are a poor fit for clinical judgments about the medical necessity of abortion. On the contemporary model of clinical decision-making, medical judgment is irremediably subjective. In addition to being responsive to patient values and medical evidence, medical judgment is, and should be, informed by physician values. Because Texas abortion regulations rely on an objective standard of judgment that fails to correspond to a medically meaningful category, they fail to provide adequate guidance to physicians regarding the circumstances under which abortion is legally protected.
Examining religion and state arrangements in the United States, this study investigates under what conditions religious law, rooted in state establishment, declines in democracies. We argue that when (1) state founders or political elites intentionally refrain from embedding religious arrangements within state institutions, (2) the state apparatus enforces a constitutionalized and explicit prohibition against government-sanctioned religion, and (3) legal justifications shift from religious to secular rationale to maintain their justifiable constitutionality, then reliance on religious law within the state diminishes. However, due to institutional path dependence, laws initially rooted in religious arrangements/traditions may persist but are increasingly framed in secular terms, aligning with the broader secularization of modern Western societies, regardless of the extent of separation between religion and state. Hence, the religious influence and objectives of these laws endure despite the secular disguise.
Emerging evidence suggests that metabolic and hormonal disturbances in polycystic ovary syndrome (PCOS) may increase vulnerability to neurodegenerative disorders. However, the link between PCOS and Alzheimer’s disease (AD)-related pathology remains unclear.
Methods:
In this cross-sectional study, plasma levels of β-amyloid (Aβ40, Aβ42), phosphorylated tau (p-tau181), neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) were quantified in women with PCOS and age-matched controls. Homeostasis model assessment of insulin resistance (HOMA-IR), inflammatory cytokines (IL-6, TNF-α) and hormonal parameters were assessed. Mediation and moderation analyses were conducted to explore metabolic and hormonal pathways underlying biomarker alterations.
Results:
Among 400 women (200 PCOS, 200 controls), age and BMI were comparable (P > 0.05). Compared with controls, PCOS participants had increased Aβ40, p-tau181, NfL and GFAP, a slightly higher Aβ42, and a lower Aβ42/40 ratio (all P < 0.05). p-tau181 correlated positively with HOMA-IR (r = 0.41) and IL-6 (r = 0.36), while Aβ42/40 ratio correlated negatively with HOMA-IR (r = –0.27). In multivariable analysis, p-tau181 (aOR = 1.34, 95% CI 1.05–1.71), IL-6 (aOR = 1.19) and TNF-α (aOR = 1.14) were independent predictors of insulin resistance. Mediation analysis indicated that HOMA-IR, IL-6 and TNF-α jointly mediated ∼ 71% of the PCOS–p-tau181 association, suggesting a metabolic–inflammatory pathway linking PCOS to AD-related tau pathology.
Conclusions:
PCOS is linked to peripheral markers of early Alzheimer’s pathology, largely mediated by insulin resistance and inflammation. PCOS may provide a clinical context to explore metabolic–inflammatory contributors to early neurodegenerative changes.
How should resource-constrained manufacturers renew operations under mounting innovation pressure? We theorize and test a contingent model in which market pressure affects operational innovation indirectly through two pathways, technology investment (exploitation) and human-capital utilization (exploration), and in which firm size conditions both pathways. Using Eurobarometer 433 data on 2,213 European manufacturing firms, we estimate a conditional process model combining ordinary least squares and logistic regressions. We find a negative direct effect of pressure on operational innovation, but positive mediated effects via technology and human capital; the technology pathway is substantively stronger. Size matters: larger firms more effectively translate pressure into technology investment, whereas smaller firms rely relatively more on human capital, implying performance parity for sequential strategies when resources are tight. We contribute boundary conditions to ambidexterity theory and offer actionable guidance: small and medium-sized enterprises should sequence renewal by first mobilising human capabilities, then adding technologies; large firms can pursue ambidextrous investments.
Treatment-resistant depression (TRD) poses a significant clinical challenge, with limited evidence guiding long-term pharmacological strategies. Esketamine, a glutamatergic modulator, has demonstrated short-term efficacy in TRD, but data on its extended use in real-world settings remains scarce.
Aims
This study aimed to evaluate the long-term effectiveness and side-effects of intranasal esketamine in adults with TRD over more than 100 treatment sessions.
Method
We conducted a retrospective, single-arm, pre–post study of 20 patients with TRD at a psychiatric out-patient clinic in the United Arab Emirates. All participants received ≥100 sessions of intranasal esketamine alongside oral antidepressants. Depression and anxiety symptoms were assessed with the Patient Health Questionnaire-9 (PHQ-9) and Generalised Anxiety Disorder-7 (GAD-7) scales. Side-effects were monitored through blood pressure, sedation, dissociation, urinary symptoms and psychiatric symptoms.
Results
After an average of 129 esketamine sessions (mean duration 2.5 years), PHQ-9 and GAD-7 scores significantly decreased (P < 0.001). A total of 85% of patients improved in depressive severity, with 25% achieving remission; 65% improved in anxiety severity, and 20% reached remission. Esketamine was generally well tolerated; side-effects were mild and transient, with no serious adverse events. However, urinary symptoms suggestive of cystitis occurred in 20% of patients, highlighting the need for ongoing monitoring in long-term treatment.
Conclusions
Intranasal esketamine demonstrated sustained effectiveness and an acceptable side-effect profile in a real-world TRD cohort with extensive psychiatric comorbidity. These findings support its long-term use in complex clinical populations, and underscore the need for further prospective, multi-site studies.
The bidirectional Glenn surgery is an important staging procedure for patients with single ventricle physiology. Approximately 1000 children are born each year in the United States with this subset of CHD. There is limited data regarding optimal post-operative management for these children. We surveyed paediatric cardiac intensive care providers surrounding their management strategies after the bidirectional Glenn surgery.
Design:
An anonymous survey was distributed via email to paediatric cardiac intensive care providers. The survey included anonymised demographic data and focused on post-operative physiologic targets for patients recovering after the bidirectional Glenn surgery.
Subjects:
Thirty-five paediatric cardiac intensive care providers responded to an anonymous 12-question survey. Subjects were mostly comprised of paediatric cardiac intensive care attendings (80%), with an average of 7.86 years of training. The respondents primarily practised in settings with medical trainees, and all practised in settings with extracorporeal membrane oxygenation capabilities.
Intervention:
Respondents were asked to complete a web-based survey. Five of the survey questions were devoted to background demographic data, and seven questions were aimed at identifying physiologic targets. Two of the seven questions were in relation to a provided clinical vignette.
Measurements and main results:
This survey demonstrated that there is a lack of consensus in the management of patients after the bidirectional Glenn surgery. Specifically, granular SpO2, mean arterial pressure, and pH Goals were all less than 75% consensus. This survey highlights the variable practice patterns in providers taking care of patients after the bidirectional Glenn surgery, and further demonstrates the need for physiologic and outcome-driven targets to optimise the post-operative care.
Efforts to curb online hate speech depend on our ability to reliably detect it at scale. Previous studies have highlighted the strong zero-shot classification performance of large language models (LLMs), offering a potential tool to efficiently identify harmful content. Yet for complex and ambivalent tasks like hate speech detection, pre-trained LLMs can be insufficient and carry systemic biases. Domain-specific models fine-tuned for the given task and empirical context could help address these issues, but, as we demonstrate, the quality of data used for fine-tuning decisively matters. In this study, we fine-tuned GPT-4o-mini using a unique corpus of online comments annotated by diverse groups of coders with varying annotation quality: research assistants, activists, two kinds of crowd workers, and citizen scientists. We find that only annotations from those groups of annotators that are better than zero-shot GPT-4o-mini in recognizing hate speech improve the classification performance of the fine-tuned LLM. Specifically, fine-tuning using the highest-quality annotator group – trained research assistants – boosts classification performance by increasing the model’s precision without notably sacrificing the good recall of zero-shot GPT-4o-mini. In contrast, lower-quality annotations do not improve and may even decrease the ability to identify hate speech. By examining tasks reliant on human judgment and context, we offer insights that go beyond hate speech detection.
Surveillance activities are emerging as exemplar use cases for large language models (LLMs) in health care. The aim of this study was to evaluate the potential for LLMs to support the expansion of surveillance activities to include cardiovascular implantable electronic device (CIED) procedures.
Methods:
A validated machine learning-based infection flagging tool was applied to a cohort of VA CIED procedures from 7/1/2021 to 9/30/2023; cases with ≥10% probability of CIED infection underwent manual review. Then, a weighted random sample of 50 infected and 50 uninfected cases was reviewed with generative artificial intelligence (GenAI) assistance. GenAI prompts were iteratively refined to extract and classify all components of infection-related variables from clinical notes. Data extracted by GenAI were compared with manual chart reviews to assess infection status and extraction consistency.
Results:
Among 12,927 CIED procedures, 334 (2.58%) had ≥10% probability of CIED infection. Among 100 sampled cases, 50 of 50 uninfected cases were correctly categorized. Among 50 infection cases, GenAI identified all CIED infections, but the timing of events and the attribution to a preceding procedure were incorrect in 7 of 50 cases. The overall specificity of the GenAI-assisted process was 100% and the sensitivity for accurately classifying timing and attribution of CIED infection events was 82%. Errors in timing improved with iterative prompt updates. Manual chart reviews averaged 25 minutes per chart; the GenAI-assisted process averaged 5–7 minutes per chart.
Conclusions:
LLMs can help streamline the review process for healthcare-associated infection surveillance, but manual adjudication of output is needed to ensure the correct timeline of events and attribution.
How did Soviet Jews rebuild their lives after the Holocaust? How did they navigate Stalinist rule, reclaim their place in society, and seek retribution against those responsible for wartime atrocities? This study uncovers the resilience and adaptability of Soviet Jews in postwar Moldavia, a borderland where identities were fluid, loyalties were tested, and survival demanded ingenuity. Using newly accessed archives and oral histories, Diana Dumitru reveals how Jews pursued professional success, resisted discrimination, and sought vengeance on their wrongdoers. Far from passive subjects of repression, they carved out spaces for agency in an era of contradictions – between social mobility and state-imposed limitations, between the Soviet promise of equality and the rising anti-Jewish drive of the early 1950s, and between ideological control and personal ambition. In doing so, this study offers a fresh perspective on a complex, understudied chapter of 20th-century history.