Quantitative analysis of chromatin compaction in living cells using FLIM-FRET

FRET analysis of cell lines expressing fluorescently tagged histones on separate nucleosomes demonstrates that variations in chromosome compaction occur during mitosis

Targeting nuclear transporters in cancer: Diagnostic, prognostic and therapeutic potential

The Karyopherin superfamily is a major class of soluble transport receptors consisting of both import and export proteins. The trafficking of proteins involved in transcription, cell signalling and cell cycle regulation among other functions across the nuclear membrane is essential for normal cellular functioning. However, in cancer cells, the altered expression or localization of nuclear transporters as well as the disruption of endogenous nuclear transport inhibitors are some ways in which the Karyopherin proteins are dysregulated. The value of nuclear transporters in the diagnosis, prognosis and treatment of cancer is currently being elucidated with recent studies highlighting their potential as biomarkers and therapeutic targets

Health Economic Considerations for the Implementation of Artificial Intelligence‐Enabled Diabetic Retinopathy Screening: A Review

Artificial intelligence (AI) has comparable accuracy to ophthalmologists for diabetic retinopathy (DR) screening, yet its cost‐effectiveness is crucial for implementation. Our review of 18 health economic analyses of AI versus manual grading for DR found significant methodological variation, with cost‐utility analysis and Markov modelling being the commonest evaluation and modelling approaches, respectively. We identified three key considerations when appraising health economic analyses of AI‐enabled DR screening: the importance of contextualised parameters including subgroup analysis, real‐world data on adherence to ophthalmology follow‐up, and the trade‐off between diagnostic accuracy and cost‐effectiveness. 39% of studies followed standardised reporting guidelines, and most did not consider improved follow‐up after AI screening, potentially underestimating its economic value. Future evaluations should incorporate contextualised parameters, including adherence and regional data, and recognise that the most accurate diagnostic screening may not reflect the most cost‐effective. Studies should follow updated reporting guidelines such as CHEERS‐AI or PICOTS‐ComTeC to improve methodological transparency

Torn between war and peace: critiquing the use of war to mobilize peaceful climate action

Notable studies have suggested the potentiality of the WWII wartime mobilization as a model for climate change adaptation and/or mitigation. The argument being that we need a similar rapid and total shift in our industrial social and economic environment to prevent or at least address the pending impacts of climate change. This argument and these studies have inspired us to think with them on what it means to use the WWII war analogy as a security claim in energy and climate change debates. Here, we would like to use this opportunity to draw attention to some of the implicit dangers of a call to war in such discussions. Among others we observe, first, the absence of any attention to the actual mobilization policies, in terms of garnishing public support. Second, based on the insights from Critical Security Studies, we question the historical incongruence of the case study especially by comparing the perceived enemy in both cases. Lastly, building on that same security literature, we point to some undesirable and perhaps unintended consequences of the use of war analogies in climate change debates

A meta-analysis of social skills training and related interventions for psychosis

Objective Evidence suggests that social skills training (SST) is an efficacious intervention for negative symptoms in psychosis, whereas evidence of efficacy in other psychosis symptom domains is limited. The current article reports a comprehensive meta-analytic review of the evidence for SST across relevant outcome measures, control comparisons, and follow-up assessments. The secondary aim of this study was to identify and investigate the efficacy of SST subtypes. Methods A systematic literature search identified 27 randomized controlled trials including N = 1437 participants. Trials assessing SST against active controls, treatment-as-usual (TAU), and waiting list control were included. Risk of bias was assessed using the Cochrane risk of bias assessment tool. A series of 70 meta-analytic comparisons provided effect sizes in Hedges’ g. Heterogeneity and publication bias were assessed. Results SST demonstrated superiority over TAU (g = 0.3), active controls (g = 0.2–0.3), and comparators pooled (g = 0.2–0.3) for negative symptoms, and over TAU (g = 0.4) and comparators pooled (g = 0.3) for general psychopathology. Superiority was indicated in a proportion of comparisons for all symptoms pooled and social outcome measures. SST subtype comparisons were underpowered, although social-cognitive approaches demonstrated superiority vs comparators pooled. SST treatment effects were maintained at proportion of follow-up comparisons. Conclusions SST demonstrates a magnitude of effect for negative symptoms similar to those commonly reported for cognitive-behavioral therapy (CBT) for positive symptoms, although unlike CBT, SST is not routinely recommended in treatment guidelines for psychological intervention. SST may have potential for wider implementation. Further stringent effectiveness research alongside wider pilot implementation of SST in community mental health teams is warranted

Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians

BACKGROUND/AIMS: Deep learning systems (DLSs) for diabetic retinopathy (DR) detection show promising results but can underperform in racial and ethnic minority groups, therefore external validation within these populations is critical for health equity. This study evaluates the performance of a DLS for DR detection among Indigenous Australians, an understudied ethnic group who suffer disproportionately from DR-related blindness. METHODS: We performed a retrospective external validation study comparing the performance of a DLS against a retinal specialist for the detection of more-than-mild DR (mtmDR), vision-threatening DR (vtDR) and all-cause referable DR. The validation set consisted of 1682 consecutive, single-field, macula-centred retinal photographs from 864 patients with diabetes (mean age 54.9 years, 52.4% women) at an Indigenous primary care service in Perth, Australia. Three-person adjudication by a panel of specialists served as the reference standard. RESULTS: For mtmDR detection, sensitivity of the DLS was superior to the retina specialist (98.0% (95% CI, 96.5 to 99.4) vs 87.1% (95% CI, 83.6 to 90.6), McNemar's test p<0.001) with a small reduction in specificity (95.1% (95% CI, 93.6 to 96.4) vs 97.0% (95% CI, 95.9 to 98.0), p=0.006). For vtDR, the DLS's sensitivity was again superior to the human grader (96.2% (95% CI, 93.4 to 98.6) vs 84.4% (95% CI, 79.7 to 89.2), p<0.001) with a slight drop in specificity (95.8% (95% CI, 94.6 to 96.9) vs 97.8% (95% CI, 96.9 to 98.6), p=0.002). For all-cause referable DR, there was a substantial increase in sensitivity (93.7% (95% CI, 91.8 to 95.5) vs 74.4% (95% CI, 71.1 to 77.5), p<0.001) and a smaller reduction in specificity (91.7% (95% CI, 90.0 to 93.3) vs 96.3% (95% CI, 95.2 to 97.4), p<0.001). CONCLUSION: The DLS showed improved sensitivity and similar specificity compared with a retina specialist for DR detection. This demonstrates its potential to support DR screening among Indigenous Australians, an underserved population with a high burden of diabetic eye disease

Operational analysis of school-based delivery models to vaccinate children against influenza.

Large-scale immunisation programmes against seasonal influenza are characterised by logistical challenges related to the need for vaccinating large cohorts of people in a short amount of time. Careful operational planning of resources is essential for a successful implementation of such programmes. We focused on the process of child vaccination in schools and analysed the staffing and workflow aspects of a school-aged children vaccination programme in England. Our objectives were to document vaccination processes and analyse times and costs associated with different models deployed across England. We collected data through direct non-participatory observations. Statistical data analysis enabled us to identify potential factors influencing vaccine delivery time and informed the development of a tool to simulate vaccination sessions. Using this tool, we carried out scenario analyses and explored trade-offs between session times and costs in different settings. Our work ultimately supported the local implementation of school-based vaccination

Predicting post one-year durability of glucose-lowering monotherapies in patients with newly-diagnosed type 2 diabetes mellitus – A MASTERMIND precision medicine approach (UKPDS 87)

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record Aims: Predicting likely durability of glucose-lowering therapies for people with type 2 diabetes (T2D) could help inform individualised therapeutic choices. Methods: We used data from UKPDS patients with newly-diagnosed T2D randomised to first-line glucose-lowering monotherapy with chlorpropamide–glibenclamide–basal insulin or metformin. In 2339 participants who achieved one-year HbA1c values <7.5% (<59 mmol/mol)–we assessed relationships between one-year characteristics and time to monotherapy-failure (HbA1c ≥ 7.5% or requiring second-line therapy). Model validation was performed using bootstrap sampling. Results: Follow-up was median (IQR) 11.0 (8.0–14.0) years. Monotherapy-failure occurred in 72%–82%–75% and 79% for those randomised to chlorpropamide–glibenclamide–basal insulin or metformin respectively–after median 4.5 (3.0–6.6)–3.7 (2.6–5.6)–4.2 (2.7–6.5) and 3.8 (2.6– 5.2) years. Time-to-monotherapy-failure was predicted primarily by HbA1c and BMI values–with other risk factors varying by type of monotherapy–with predictions to within ±2.5 years for 55%–60%–56% and 57% of the chlorpropamide–glibenclamide–basal insulin and metformin monotherapy cohorts respectively. Conclusions: Post one-year glycaemic durability can be predicted robustly in individuals with newly-diagnosed T2D who achieve HbA1c values < 7.5% one year after commencing traditional monotherapies. Such information could be used to help guide glycaemic management for individual patients.Medical Research Council (MRC