This collection gathers thirteen contributions by a number of historians, friends, colleagues and/or students of Jinty’s, who were asked to pick their favourite article by her and say a few words about it for an event held in her memory on 15 January 2025 at King’s College London. We offer this collection in print now for a wider audience not so much because it has any claim to be exhaustive or authoritative, but because taken all together these pieces seemed to add up to a useful retrospective on Jinty’s work, its wider context, and its impact on the field over the decades. We hope that, for those who know her work well already, this may be an opportunity to remember some of her classic (and a few less classic) articles, while at the same time serving as an accessible introduction to her research for anyone who knew her without necessarily knowing about her field, as well as for a new and younger generation of readers.

Aims: Safe and effective prescribing in people living with dementia (PLWD) is particularly challenging due to the increased risk of adverse events, polypharmacy and potentially inappropriate medications. Cognitive impairment and reliance on caregivers to report symptoms can further complicate the assessment of drug benefits. This case study demonstrates how novel contactless monitoring could address these challenges by enabling remote evaluation of drug effects in PLWD.

Methods: We present the case of a 77-year-old gentleman with late onset Alzheimer’s disease enrolled on the CR&T MINDER cohort study and continuously monitored using the Withing’s Sleep Analyzer. He visited his GP with complaints of insomnia and was subsequently prescribed 15 mg of mirtazapine. He reported immediate beneficial effects, although noted that the drug made him drowsy. We evaluated his sleep by comparing baseline sleep metrics (a 2-week average 1 month before drug administration) with average sleep metrics 2 weeks after starting mirtazapine. Statistical analysis was performed using a paired t-test and a rolling average to assess trends over time.

Results: Calculated rolling average showed reductions in time spent awake overnight and in light sleep, while deep sleep and total sleep time increased. These trends were confirmed by period comparisons. Baseline deep sleep duration (M = 1.19 hrs, SD = 1.02 hrs), and total sleep time (M = 7.16 hrs, SD = 1.03 hrs) significantly increased 2 weeks post mirtazapine (deep sleep: M = 2.63 hrs, SD = 1.03 hrs); total sleep time: M = 7.87 hrs, SD = 0.47 hrs), t(13) = −3.639, p = 0.003, and t(13) = −2.256, p = 0.042. There was also a significant reduction in time spent awake during the night from baseline (M = 1.17 hrs, SD = 0.51 hrs) to 2 weeks post mirtazapine (M = 0.65 hrs, SD = 0.43 hrs), t(13) = 2.616, p = 0.0214.

Conclusion: This case study shows that contactless remote monitoring could be used objectively to evaluate the effects of mirtazapine on sleep in PLWD. Our results demonstrate that improvements in sleep detected by monitoring align with the participants’ reported benefits. These findings suggests continuous remote monitoring could provide valuable, timely insights into drug effects in PLWD, improving clinical decision-making and personalising care.

We present the Evolutionary Map of the Universe (EMU) survey conducted with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU aims to deliver the touchstone radio atlas of the southern hemisphere. We introduce EMU and review its science drivers and key science goals, updated and tailored to the current ASKAP five-year survey plan. The development of the survey strategy and planned sky coverage is presented, along with the operational aspects of the survey and associated data analysis, together with a selection of diagnostics demonstrating the imaging quality and data characteristics. We give a general description of the value-added data pipeline and data products before concluding with a discussion of links to other surveys and projects and an outline of EMU’s legacy value.

Film offers untapped potential for making critical interventions in world politics, particularly in ways that harness people’s capacity to narrate stories that creatively empower their communities. Combining International Relations scholarship on visual politics with narrative theory and feminist scholarship on care, this paper presents film as a means of exploring and expressing narrative agency; that is, the power to tell stories that represent people’s experiences in ways that disrupt hegemonic narratives. Dialectics of care and narrative agency are explored in the context of military-to-civilian ‘transition’ in Britain. We argue that the landscape of transition for military veterans is dominated by a preoccupation with employment and economic productivity, resulting in a ‘care deficit’ for veterans leaving the military. Through the Stories in Transition project, which used co-created film to explore narrative agency in the context of three veterans’ charities, we argue that the act of making care visible constitutes a necessary intervention in this transitional landscape. Grounding this intervention within feminist care ethics and the related notion of care aesthetics, we highlight the potential for film to reveal in compelling audio-visual narratives an alternative project of transition which might better sustain life and hope in the aftermath of military service.

The treatment recommendation based on a network meta-analysis (NMA) is usually the single treatment with the highest expected value (EV) on an evaluative function. We explore approaches that recommend multiple treatments and that penalise uncertainty, making them suitable for risk-averse decision-makers. We introduce loss-adjusted EV (LaEV) and compare it to GRADE and three probability-based rankings. We define properties of a valid ranking under uncertainty and other desirable properties of ranking systems. A two-stage process is proposed: the first identifies treatments superior to the reference treatment; the second identifies those that are also within a minimal clinically important difference (MCID) of the best treatment. Decision rules and ranking systems are compared on stylised examples and 10 NMAs used in NICE (National Institute of Health and Care Excellence) guidelines. Only LaEV reliably delivers valid rankings under uncertainty and has all the desirable properties. In 10 NMAs comparing between 5 and 41 treatments, an EV decision maker would recommend 4–14 treatments, and LaEV 0–3 (median 2) fewer. GRADE rules give rise to anomalies, and, like the probability-based rankings, the number of treatments recommended depends on arbitrary probability cutoffs. Among treatments that are superior to the reference, GRADE privileges the more uncertain ones, and in 3/10 cases, GRADE failed to recommend the treatment with the highest EV and LaEV. A two-stage approach based on MCID ensures that EV- and LaEV-based rules recommend a clinically appropriate number of treatments. For a risk-averse decision maker, LaEV is conservative, simple to implement, and has an independent theoretical foundation.

The Lyman alpha (Ly$\alpha$) forest in the spectra of $z\gt5$ quasars provides a powerful probe of the late stages of the epoch of reionisation (EoR). With the recent advent of exquisite datasets such as XQR-30, many models have struggled to reproduce the observed large-scale fluctuations in the Ly$\alpha$ opacity. Here we introduce a Bayesian analysis framework that forward-models large-scale lightcones of intergalactic medium (IGM) properties and accounts for unresolved sub-structure in the Ly$\alpha$ opacity by calibrating to higher-resolution hydrodynamic simulations. Our models directly connect physically intuitive galaxy properties with the corresponding IGM evolution, without having to tune ‘effective’ parameters or calibrate out the mean transmission. The forest data, in combination with UV luminosity functions and the CMB optical depth, are able to constrain global IGM properties at percent level precision in our fiducial model. Unlike many other works, we recover the forest observations without invoking a rapid drop in the ionising emissivity from $z\sim7$ to 5.5, which we attribute to our sub-grid model for recombinations. In this fiducial model, reionisation ends at $z=5.44\pm0.02$ and the EoR mid-point is at $z=7.7\pm0.1$. The ionising escape fraction increases towards faint galaxies, showing a mild redshift evolution at fixed UV magnitude, $M_\textrm{UV}$. Half of the ionising photons are provided by galaxies fainter than $M_\textrm{UV} \sim -12$, well below direct detection limits of optical/NIR instruments including $\textit{ JWST}$. We also show results from an alternative galaxy model that does not allow for a redshift evolution in the ionising escape fraction. Despite being decisively disfavoured by the Bayesian evidence, the posterior of this model is in qualitative agreement with that from our fiducial model. We caution, however, that our conclusions regarding the early stages of the EoR and which sources reionised the Universe are more model-dependent.

Objectives/Goals: To investigate interventional clinical trial participation overall and by race, gender, and age. Methods/Study Population: We used Epic Cosmos, an aggregated, de-identified EHR platform including over 270 million patients, to examine overall clinical trial participation and the race, gender, and age composition of participants versus non-participants. Patients ≥5 years old with known race and gender and at least one healthcare encounter between 2021 and 2024 were included. Interventional trial enrollment was identified by a “research flag” indicating current or past participation in an interventional study within an Epic system contributing data to Cosmos. Race was categorized as American Indian, Asian, Black, Native Hawaiian, or White. Age-adjusted relative representation (RR) ratios were used to compare participation, with RR >1 indicating over-representation and RR Results/Anticipated Results: Of 130,455,189 patients meeting eligibility criteria, 0.52% (673,425) of patients were active or inactive in an interventional clinical trial. Results are shown in the figure below. The poorest representation was from Asian and NH/PI persons. Representation was most similar to the patient population for whites and AI/AN persons. Black males participated less and women, more than predicted by patient composition. Older patients participated more frequently than younger (age, mean (SD), y, 53 (22) vs. 46 (23); p Discussion/Significance of Impact: This is the first study we know of describing interventional trial participation in the USA across millions and millions of patients. Further research is needed to clarify whether these differences are due to the nature of the studies themselves (e.g., OB/GYN trials including only women, etc.) versus disparities in recruitment or otherwise.

Objectives/Goals: Opioid use disorder (OUD) at delivery increased between 1999 and 2014. Clinical guidelines include medication for OUD (MOUD) for pregnant women with OUD and is associated with better fetal outcomes. Few large studies have compared prenatal MOUD outcomes to no MOUD. We evaluated the association of documented MOUD prescription during pregnancy with maternal outcomes. Methods/Study Population: We utilized aggregated electronic health records using the TriNetX platform to conduct a retrospective cohort study of females, aged 1249 years with a childbirth CPT code and documented opioid use via ICD-10 codes in the nine months before delivery between 2014 and 2020, comparing patients with MOUD prescription of buprenorphine or methadone during the nine months before delivery to demographically matched patients without any documented MOUD, using hazard ratios and 95% CIs for outcomes occurring one week to one or three years after childbirth. Results/Anticipated Results: MOUD cohort (n = 6,945, 85.33% White; 82.77% Non-Hispanic or Latino) was associated with significantly higher subsequent documented MOUD prescription (HR, 9.26 [95% CI, 7.98–10.76]; 6.21 [95% CI, 5.60–6.88]) and new remission codes (HR, 2.79 [95% CI, 2.15–3.62]; 2.85 [95% CI, 2.38–3.40]) at one and three years, lower ED visits at one year (HR, 0.88 [95% CI, 0.81–0.96]), no significant association of ED visits at three years (0.95 [95% CI, 0.89–1.02]), higher outpatient visits (HR, 1.26 [95% CI, 1.20–1.32]; HR, 1.27 [95% CI, 1.21–1.33], and no significant association of inpatient visits at one and three years (HR, 0.93 [95% CI, 0.813–1.06]; 1.06 [95% CI, 0.96–1.18]) than the never-MOUD cohort (n = 4,708, 76.11% White; 75.68% non-Hispanic or Latino). Discussion/Significance of Impact: A documented prescription for MOUD during pregnancy is associated with newly documented remission of OUD, increased outpatient visits, decreased ED visits, and additional documented MOUD prescriptions suggestive of increased access to continuity care. Efforts to increase MOUD use in pregnancy may improve maternal outcomes.

The January 6th insurrection and its aftermath of obfuscation and denial were ostensibly racialized events. Under the guise of election fraud, white supremacists, white nationalists, and paramilitary groups attempted to overthrow established democratic procedures to retain a president who stoked racial antagonisms and racial divisions. African Americans, like many American citizens, watched in fear, anxiety, and foreboding as the groups most committed to their repression violently attacked and ransacked the Capitol.

We examine the extent to which the January 6th insurrection and its aftermath of denial and obfuscation influence African Americans’ racial resentment. Our results show how the racialized January 6th events were connected to heightened African American racial resentment. The most compelling result confirms that African Americans’ racial resentment stems from beliefs about justice and fairness.

“Improper linear models” (see Dawes, Am. Psychol. 34:571–582, 1979), such as equal weighting, have garnered interest as alternatives to standard regression models. We analyze the general circumstances under which these models perform well by recasting a class of “improper” linear models as “proper” statistical models with a single predictor. We derive the upper bound on the mean squared error of this estimator and demonstrate that it has less variance than ordinary least squares estimates. We examine common choices of the weighting vector used in the literature, e.g., single variable heuristics and equal weighting, and illustrate their performance in various test cases.