Data-driven model predictive control for continuous-time systems

We present some preliminary ideas on a data-driven Model Predictive Control framework for continuous-time systems. We use Chebyshev polynomial orthogonal bases to represent system trajectories and subsequently develop a data-driven continuous-time version of the classical Model Predictive Control algorithm. We investigate the effects of the parameters in our framework with two numerical examples and draw comparison to model-driven MPC schemes

Paternal prepubertal passive smoke exposure is related to impaired lung function trajectories from childhood to middle age in their offspring

Introduction: paternal prepubertal passive smoke exposure may increase the risk of childhood asthma. However, its association with impaired lung function trajectories at risk of chronic obstructive pulmonary disease in offspring was not investigated. We assessed the association between paternal prepubertal passive smoke exposure and lung function from childhood to middle age in their offspring. Methods: data were analysed from 890 father-offspring pairs from the Tasmanian Longitudinal Health Study. The offspring were probands in the original cohort who underwent spirometry at six time points from ages 7 to 53 years. Lung function (forced expiratory volume in 1 s (FEV 1), forced vital capacity (FVC) and FEV 1/FVC) trajectories were previously derived using group-based trajectory modelling. Fathers reported their own passive smoke exposure before age 15 years. Multinomial logistic regressions assessed associations between paternal prepubertal passive smoke exposure and lung function trajectories in offspring. Potential mediations and interactions were assessed for active paternal smoking, offspring passive smoke exposure and respiratory illnesses during childhood, and subsequent active smoking. Results: paternal prepubertal passive smoke exposure was associated with the below average FEV 1 (adjusted multinomial OR (aMOR) 1.56; 95% CI 1.05 to 2.31) and early low-rapid decline FEV 1/FVC trajectories (aMOR 2.30; 95% CI 1.07 to 4.94) in offspring. The association with the below average FEV 1 trajectory was augmented for offspring exposed to childhood passive smoke (aMOR 2.36; 95% CI 1.34 to 4.13; p-interaction=0.053). Observed associations partly mediated through smoking and respiratory illnesses in fathers and offspring (each contributing &lt;15%). Conclusions: paternal prepubertal passive smoke exposure was associated with impaired lung function trajectories in offspring, which highlights the adverse impact of smoking on multiple generations.</p

Navigating the narrative: Integrating traditional knowledge and embodied practice within computational models of ancient seafaring

Why do people go to sea? The relationship people have with land and sea, maritime space, boats and ships are entwined and complex, shaped and molded by the marine environment, identity and heritage. This paper explores the complexity of people’s relationship with the sea to question how we can understand and model seafaring in the past, and how this can be used to better understand maritime heritage today. To be meaningful, computational analysis of seafaring must be tied into relevant known seafaring and navigation practice. Without this firm basis our statistical and hypothetical models lose the ability to measure past actions. However, there are many ways to ‘go to sea’ and seafaring practices do not start and end on the water itself. This paper reflects upon the process of seafaring, as it relates to our understanding of navigational knowledge, mobility in practice, seafaring as social action and the influences behind people’s desire to set sail. There is much we can learn from applied practices of seafaring, conducted both by practitioners and through efforts of experimental or experiential archaeology; understanding the complexity and nuance of the social aspects of seafaring guides the research questions that shape our models and shapes how we use and understand the outcomes derived from quantitative computational approaches

Maternal age and parity influences on health outcomes: a multivariable regression analysis of mothers and infants

BackgroundAdverse pregnancy and birth outcomes remain significant public health challenges, particularly in low- and middle-income countries (LMICs). Maternal age and parity are recognised as key factors, yet their combined influence on maternal and infant outcomes is less understood, especially in LMICs.ObjectivesWe investigated the combined effects of maternal age and parity on maternal health risks, including body mass index (BMI), gestational diabetes mellitus (GDM), and hypertension, as well as infant birth outcomes, namely birth weight, length, and gestational age, in an urban South African cohort.MethodsThis study used data from 830 pregnant women (aged 18–44) enrolled in the Soweto First 1000 Days (S1000) longitudinal cohort. Group comparisons were conducted using ANOVA, chi-square, or Kruskal-Wallis tests. Multivariable Linear and logistic regression models assessed associations between age-parity and outcomes, adjusting for sociodemographic factors. Analyses were conducted in StataSE 18; p &lt; .05 was considered significant.ResultsMothers &gt; 23 years, ≥ 1 child had higher BMI (28.6 kg/m², p &lt; .001) and increased likelihood of hypertension (44.1%, p &lt; .001), and GDM (7.4%, p = .012). Nulliparous women showed greater gestational weight gain (0.39 kg/week, p &lt; .001) and an increased likelihood of having low birth weight (2960 g vs. 3185 g, p = .002), small for gestational age (SGA) (22.9%, p = .009), and shorter birth length infants (z = − 0.29, 95% CI: [− 0.57 to − 0.01], p = .04). Infants of mothers ≤ 23 years, ≥ 1 child had higher birth weight (β = 0.60, 95% CI: [0.32–0.88]; p &lt; .001) and length z-scores (95% CI: [0.01–0.97], p = .046). Hypertension (β = −0.99, 95% CI: [− 1.52 to − 0.45], p &lt; .001) and GDM (β = −0.57, 95% CI: [− 1.10 to − 0.04], p = .036) were associated with shorter gestational age.ConclusionMaternal age and parity were associated with distinct risks to maternal and infant health. These findings support the need for more targeted, risk-based antenatal strategies in LMICs

Microglial mechanisms drive amyloid-β clearance in immunized patients with Alzheimer’s disease

Alzheimer’s disease (AD) therapies utilizing amyloid-β (Aβ) immunization have shown potential in clinical trials. Yet, the underlying mechanisms driving Aβ clearance in the immunized AD brain remain unclear. Here, we employ spatial transcriptomics (ST) to explore the effects of both active and passive Aβ immunization on the AD brain. Comparing actively immunized AD patients with non-immunized AD subjects and neurologically healthy controls, we identify distinct microglial states associated with Aβ clearance. Using high-resolution ST alongside single-cell RNA sequencing (scRNA-seq), we delve deeper into the transcriptional pathways involved in Aβ removal following treatment with lecanemab, uncovering spatially distinct microglial responses that vary by brain region. Our analysis reveals upregulation of Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) and Apolipoprotein E (APOE) in microglia across both active and passive immunization approaches, which correlate positively with Aβ clearance. These findings provide novel insights into the transcriptional mechanisms orchestrating Aβ clearance and shed light on the role of microglia in immune-mediated clearance. Importantly, our work uncovers potential molecular targets that could enhance Aβ-targeted immunotherapies, offering new avenues for developing more effective therapeutic strategies to combat AD. This study paves the way for future research into microglial modulation and its therapeutic potential in AD

Nasim: revealing the low surface brightness Universe from legacy VISTA data

Near-infrared imaging is a powerful technique in observational astronomy, but the bright background – primarily from the Earth’s atmosphere – makes the detection of faint features particularly challenging. To recover low surface brightness (LSB) structures in such data, we present NASIM (Near-infrared Automated low Surface brightness reduction In Maneage), a fully automated and reproducible data reduction pipeline optimised for VISTA/VIRCAM observations. NASIM builds on advanced techniques from the GNU Astronomy Utilities (Gnuastro) to effectively remove large-scale instrumental artefacts and detector patterns while preserving faint, diffuse emission crucial for LSB science. As a key science application, we focus on the deep K s-band observations of the Euclid Deep Field South (KEDFS), one of the deepest VISTA/VIRCAM datasets and a high-priority field for synergy with current and future facilities, including Euclid, JWST, LSST, Roman, Spitzer, and ALMA. Situated near the South Ecliptic Pole, KEDFS offers favourable conditions for deep extragalactic observations due to minimal Galactic foreground contamination. With VIRCAM no longer operational, it now stands as a unique and irreplaceable legacy dataset for near-infrared astronomy. We release selected tiles from the KEDFS survey and highlight representative science cases – including galaxy outskirts, LSB galaxies, and intracluster light – that demonstrate NASIM’s ability to recover diffuse structures. Our reduction reaches a surface brightness limit of ∼27.7 mag arcsec −2 (3σ over 100 arcsec 2) in the K s band, approximately 67 times deeper than 2MASS and 11 times deeper than VISTA Hemisphere Survey (VHS). A direct comparison with conventional VISTA data reduction pipelines demonstrates the advantages of NASIM in preserving diffuse emission without compromising compact source detection. All quantitative results presented in this paper are fully reproducible with Maneage (commit a02b40dd).</p

Long-Term glycemic control and the risk of liver stiffness progression and liver-related events in MASLD

Background &amp; Aims: the long-term impact of type 2 diabetes (T2D) status and long-term glycemic control on disease progression and clinical outcomes in metabolic dysfunction–associated steatotic liver disease (MASLD) remains unclear. The study sought to assess the association of diabetes status and long-term glycemic control with liver stiffness progression or regression, and liver-related events (LREs) in MASLD.Methods: we analyzed patients with MASLD from the VCTE-Prognosis cohort who underwent serial vibration-controlled transient elastography (VCTE) assessments and hemoglobin A1c (HbA1c) measurements. Long-term glycemic control was evaluated using the time-weighted average (TWA) HbA1c, which reflects both the magnitude and duration of glycemia. Patients were categorized as non-T2D, well-controlled T2D (TWA HbA1c&lt;7%), or poorly controlled T2D (TWA HbA1c ≥7%). Liver stiffness progression, regression, and LREs were examined using Kaplan-Meier analyses and Cox proportional hazards models.Results: of 7543 patients with MASLD, 4090 had T2D (2045 well controlled, 2045 poorly controlled) and 3453 did not have T2D. Over a median follow-up of 4.1 years, patients with T2D had a higher risk of liver stiffness progression (hazard ratio [HR], 1.501, 95% confidence interval [CI]. 1.148–1.962; P = .003) and LREs (HR, 2.030; 95% CI, 1.241–3.320; P = .005), but not liver stiffness regression, compared with non-T2D patients. Among patients with T2D, poor glycemic control was associated with a higher risk of liver stiffness progression compared with good glycemic control (HR, 1.524; 95% CI, 1.182–1.965; P = .001). No differences were observed for liver stiffness regression (P = .957) or LREs (P = .625) with glycemic control. Findings were consistent across sensitivity analyses.Conclusions: T2D was independently associated with a higher risk of liver stiffness progression and LREs in MASLD. Good glycemic control was associated with slower liver stiffness progression, but not regression or LREs. <br/

Investigating the inflammatory response to cerebral amyloid angiopathy (CAA-ri)

Background: amyloid (A)-β immunotherapy has been approved as treatment for Alzheimer's patients in some countries. However, clinical trials have highlighted side effects interpreted as brain oedema and microhaemorrhages, named amyloid-related imaging abnormalities (ARIA), for which tissue is unavailable to understand the underlying pathophysiomechanisms. Cerebral amyloid angiopathy–related inflammation (CAA-ri) is a condition presenting similarities with ARIA and is seen in a proportion of neurosurgical biopsies, thus presenting an opportunity to study ARIA.Method: eight biopsies of CAA-ri and 11 CAA without inflammation, sourced from BRAIN UK, were immunolabelled for T lymphocytes (CD4 and CD8) and microglia/macrophages (CD68) and the staining quantified.Results: preliminary results show increased intramural and perivascular CD8+ lymphocytes in CAA-ri vs. CAA (p &lt; 0.001 and p = 0.004, respectively). There were also more perivascular CD4+ lymphocytes in CAA-ri (p = 0.006). In CAA-ri, a higher proportion of vessels were associated with CD8+ lymphocytes vs. CD4+ lymphocytes, both intramural and perivascular (p = 0.004 and p = 0.009, respectively). In CAA, more vessels were associated with perivascular CD8+ lymphocytes (p = 0.014), which co-localised with acute haemorrhage on H&amp;E.Conclusion: CAA-ri comprises both CD4 and CD8 lymphocytes, with the latter appearing to be a more prominent component. CD4 and CD8 lymphocytes both were detected in cerebral haemorrhage associated with CAA, which may skew the assessment. CD68 quantification to investigate a microglial/macrophage component is in process and additional biopsies are currently obtained to increase the power of the study. A better comprehension of CAA-ri may aid in understanding ARIA occurring in Alzheimer's patients treated with A-β immunotherapy

Cognitive authority theory: reframing health inequity, disadvantage and privilege in palliative and end-of-life care

Background: there persist disparities in access to quality palliative and end-of-life care, often based on avoidable injustice. Research and theory to explain this health inequity focuses on structural or individual-based factors, overlooking important relational factors between health professionals, patients and families.Aim: to apply Cognitive Authority Theory in palliative and end-of-life care to explain neglected relational drivers of inequity in access and experience.Methods: cognitive Authority Theory, a middle-range theory of power relations between individuals and authority over knowledge, was developed from empirical and review data. This paper demonstrates its utility in explaining an overlooked component of inequity in palliative care: interactions between health professionals and patients/caregivers.Results: using examples from the palliative care literature, we characterise how people who are socially disadvantaged have fewer resources to exploit during consultations with health professionals which makes it difficult for them to have their voices heard, their choices prioritised by others, and to express their expertise. We examine the implications of health professionals’ judgements of expertise for care access, experience, involvement and appropriateness. We offer a fresh perspective on the mechanisms by which stereotypes, bias and power imbalances between health professionals and patients reinforce existing health inequities, drawing on the role of social privilege in shaping inequity in palliative care.Conclusion: this paper provides a new language to articulate relational drivers of inequity in palliative care. It explains how to use Cognitive Authority Theory to design and interpret research to determine how healthcare interactions reinforce both social privilege and social disadvantage at end-of-life