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This article presents a collection of narrative examples on how a cohort of African graduates, who are beneficiaries of a scholarship from a global foundation, understand and practice giving back. The scholarship programme aims to cultivate and support a network of like-minded young leaders who are committed to giving back by providing training and mentorship that reinforces the core values of transformative leadership and a commitment to improving the lives of others. To investigate these ideas, the Human Sciences Research Council is tracking recent graduates of the scholarship programme using a longitudinal cohort study design consisting of a tracer study, annual qualitative interviews with scholarship alumni, and smaller collaborative enquiries. Beginning in 2019 and tracking alumni for a five-year period, the study involves alumni from seven study sites. Findings from the study show that alumni exhibit a strong sense of social consciousness including an alignment of their understanding and practices of give-back with deeply embedded African notions of give-back as a 'ripple effect', reciprocity and ubuntu. Alumni acknowledged that there was not only one way to give, indicating that they participated in give-back in relation to their capacity, usually beginning with contributions to the family. As they became more established in their careers, their sphere of give-back increased with their reach expanding to the broader community. A low proportion of alumni felt that they were making an impact on an institutional or systemic level. Findings also show the impactful position that university partners hold in fostering give-back engagement among students and their potential role in supporting alumni after graduation. The article argues that nurturing social consciousness in young people and an understanding of give-back as collective movement building can contribute to solving development and social justice problems in Africa.

The BASE (Barberton Archean Surface Environments) scientific drilling project aimed at recovering an unweathered continuous core from the Paleoarchean Moodies Group (ca. 3.2 Ga), central Barberton Greenstone Belt (BGB), South Africa. These strata comprise some of the oldest well-preserved sedimentary strata on Earth, deposited within only a few million years in alluvial, fluvial, coastal-deltaic, tidal, and prodeltaic settings. They represent a very-high-resolution record of Paleoarchean surface conditions and processes. Moodies Group strata consist of polymict conglomerates, widespread quartzose, lithic and arkosic sandstones, siltstones, shales, and rare banded-iron formations (BIFs) and jaspilites, interbedded with tuffs and several thin lavas. This report describes objectives, drilling, and data sets; it supplements the operational report. Eight inclined boreholes between 280 and 495 m length, drilled from November 2021 through July 2022, obtained a total of 2903 m of curated core of variable quality through steeply to subvertically dipping, in part overturned stratigraphic sections. All drilling objectives were reached. Boreholes encountered a variety of conglomerates, diverse and abundant, mostly tuffaceous sandstones, rhythmically laminated shale-siltstone and banded-iron formations, and several horizons of early-diagenetic silicified sulfate concretions. Oxidative weathering reached far deeper than expected. Fracturing was more intense, and BIFs and jaspilites were thicker than anticipated. Two ca. 1 km long mine adits and a water tunnel, traversing four thick stratigraphic sections within the upper Moodies Group in the central BGB, were also sampled. All boreholes were logged by downhole wireline geophysical instruments. The core was processed (oriented, slabbed, photographed, described, and archived) in a large, publicly accessible hall in downtown Barberton. A geological exhibition provided background explanations for visitors and related the drilling objectives to the recently established Barberton Makhonjwa Mountains World Heritage Site. A substantial education, outreach, and publicity program addressed the information needs of the local population and of local and regional stakeholders.

Abstract High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

Abstract During the Mesoproterozoic Era, 1600 to 1000 million years ago, global climate was warm with very little evidence of glaciation. Substantial greenhouse warming would have been required to sustain this ice-free state given 5-18% lower solar luminosity. Paleomagnetic data reported here place voluminous ca. 1.2 Ga shallow marine carbonate deposits from India at an unexpectedly high latitude of around 70° from the equator. Previous studies noted high latitudes, but their implication was never considered. Here, we evaluate the temporal-latitudinal distribution of neritic carbonate deposits across the Proterozoic and identify similar deposits from North China that together with those from India are seemingly unique to the late Mesoproterozoic. A uniformitarian interpretation implies that this is cold-water carbonate deposition, but facies similarity with low-latitude neritic deposits rather suggests a hotter climate and elevated polar ocean temperatures of 15–20° or higher. This interpretation represents a climate conundrum that would require much greater greenhouse warming than documented for the Mesoproterozoic.

Power sector and energy systems models are widely used to explore the impacts of demographic, socio-economic or policy changes on the cost and emissions of electricity generation. Technology cost and performance data are essential inputs to such models. Despite the ubiquity and importance of these parameters, there is no standardised database which collates the variety of values from across the literature, so modellers must collect them independently each time they populate or update model inputs, leading to duplicated efforts and inconsistencies which can profoundly influence model results. Technology cost and performance varies between countries, regions and over time, meaning that data must be country- or region-specific and frequently updated. Values also vary widely between sources, so obtaining a broad consensus view is critical. Here, we present a database which collates historical, current, and future cost and performance data and assumptions for the six most prominent electricity generation technologies; coal, gas, hydroelectric, nuclear, solar photovoltaic (PV) and wind power, which together accounted for over 92 % of installed generation capacity in 2022. In addition, we provide the same data for utility-scale battery energy storage systems (BESS), regarded as critical to the integration of variable renewables such as wind and solar PV. The data are global in scope but with regional and national specificity, covers the years 2015 through to 2050, and span 5518 datapoints from 56 sources. The database enables modellers to select and justify model input data and provides a benchmark for comparing assumptions and projections to other sources across the literature to validate model inputs and outputs. It is designed to be easily updated with new sources of data, ensuring its utility, comprehensiveness, and broad applicability in future.

Objectives: To evaluate diagnostic yield and feasibility of integrating testing for TB and COVID-19 using molecular and radiological screening tools during community-based active case-finding (ACF). Methods: Community-based participants with presumed TB and/or COVID-19 were recruited using a mobile clinic. Participants underwent simultaneous point-of-care (POC) testing for TB (sputum; Xpert Ultra) and COVID-19 (nasopharyngeal swabs; Xpert SARS-CoV-2). Sputum culture and SARS-CoV-2 RT-PCR served as reference standards. Participants underwent ultra-portable POC chest radiography with computer-aided detection (CAD). TB infectiousness was evaluated using smear microscopy, cough aerosol sampling studies (CASS), and chest radiographic cavity detection. Feasibility of POC testing was evaluated via user-appraisals. Results: Six hundred and one participants were enrolled, with 144/601 (24.0%) reporting symptoms suggestive of TB and/or COVID-19. 16/144 (11.1%) participants tested positive for TB, while 10/144 (6.9%) tested positive for COVID-19 (2/144 [1.4%] had concurrent TB/COVID-19). Seven (7/16 [43.8%]) individuals with TB were probably infectious. Test-specific sensitivity and specificity (95% CI) were: Xpert Ultra 75.0% (42.8-94.5) and 96.9% (92.4-99.2); Xpert SARS-CoV-2 66.7% (22.3-95.7) and 97.1% (92.7-99.2). Area under the curve (AUC) for CAD4TB was 0.90 (0.82-0.97). User appraisals indicated POC Xpert to have ‘good’ user-friendliness. Conclusions: Integrating TB/COVID-19 screening during community-based ACF using POC molecular and radiological tools is feasible, has a high diagnostic yield, and can identity probably infectious persons.

In this opinion paper, the author reflects on a transformative experience attending an antimicrobial stewardship workshop that shifted their perception of the looming crisis of antimicrobial resistance. The author emphasises the critical need for greater awareness and education at all levels of society, from healthcare professionals to the general population, to truly comprehend the severity of this issue. Drawing parallels between antimicrobial resistance and more recognised threats such as cancer, the author advocates for a multidisciplinary approach and heightened emphasis on education to foster responsible antimicrobial use. They propose practical strategies, including integrating stewardship principles into medical education and advocating for preventive measures such as vaccination. Ultimately, this paper urges individuals to embrace their roles as stewards of antimicrobials and to seize the opportunity to effect change for the betterment of humanity. Contribution: This opinion paper emphasises the urgent need for greater awareness and education on antimicrobial stewardship. It underscores the importance of multidisciplinary collaboration and proposes practical strategies, particularly in healthcare education. These insights align with the journal’s scope of advancing healthcare education, policy, and addressing global health challenges regarding infectious diseases.

Splenic hydatid cysts are caused by the Echinococcus species and rarely occur in pregnancy. This case report describes the management of a 29-year-old pregnant woman with a large (11 × 8.7 × 10.5 cm) splenic hydatid cyst. The cyst had been identified before she became pregnant by her general practitioner with imaging investigations undertaken for her persistent left upper abdominal pain. The patient also had laboratory investigations which were positive for echinococcosis species.Hydatid splenic cysts are very rare and even more so in pregnancy. Risk of splenic cyst rupture exists, and rupture has significant risk of maternal and perinatal morbidity and mortality. Among the few case reports in the literature there is no clear consensus on conservative or surgical management during pregnancy and no clear guidelines for intrapartum care or delivery. The case report reviews the literature on splenic hydatid cyst disease in pregnancy and explores the management and outcome of this patient through her fourth pregnancy, which resulted in an uncomplicated vaginal birth.

Our subjective sense of time is intertwined with a plethora of perceptual, cognitive and motor functions, and likewise, the brain is equipped to expertly filter, weight and combine these signals for seamless interactions with a dynamic world. Until relatively recently, the literature on time perception has excluded the influence of simultaneous motor activity, yet it has been found that motor circuits in the brain are at the core of most timing functions. Several studies have now identified that concurrent movements exert robust effects on perceptual timing estimates, but critically have not assessed how humans consciously judge the duration of their own movements. This creates a gap in our understanding of the mechanisms driving movement-related effects on sensory timing. We sought to address this gap by administering a sensorimotor timing task in which we explicitly compared the timing of isolated auditory tones and arm movements, or both simultaneously. We contextualized our findings within a Bayesian cue combination framework, in which separate sources of temporal information are weighted by their reliability and integrated into a unitary time estimate that is more precise than either unisensory estimate. Our results revealed differences in accuracy between auditory, movement and combined trials, and (crucially) that combined trials were the most accurately timed. Under the Bayesian framework, we found that participants' combined estimates were more precise than isolated estimates, yet were sub-optimal when compared with the model's prediction, on average. These findings elucidate previously unknown qualities of conscious motor timing and propose computational mechanisms that can describe how movements combine with perceptual signals to create unified, multimodal experiences of time.

The aim of this study is to gain empirical knowledge about how the Bible functions in the context of Protestant Christian primary schools in the Netherlands. It presents the results of an empirical explorative and qualitative study on the perceptions of teachers and school administrators (directors and internal supervisors) on the goals of Bible use in Protestant primary education, as well as the roles of teachers and pupils, and how these can be understood in terms of religious pedagogical models and theories. Five small focus group interviews with teachers and six interviews with school administrators revealed a variety of goals teachers hold regarding Bible use in education and a variety of divisions of teacher-learner roles in this regard. The findings also show some particular characteristics when compared with secondary schools.

This contribution offers a reflection on the theme of religious educational leadership (REL) at a time when the coronavirus (COVID-19) pandemic is gripping society. The main question that guides the contribution is: How does one practice REL in theological education during COVID-19 and its accompanying measures? In answering this question, the author reflects on his own experiences as a rector on a theological faculty in Belgium and brings these experiences into conversation with the literature on the role of normativity in religious education (RE). This contribution presents a number of normative positions and discourses in leadership at the time of COVID-19 and invites the reader to reflect on the issue of normativity in their own practices of bridge-building leadership.

The COVID-19 pandemic emphasises the importance of care for our societies, yet underscores the inferiority of relational caring practices. During this time, we studied the participatory work of artists working with older adults using participant observations, in-depth interviews and visual ethnography. In this article, we present a case study of one arts initiative, a theatre company engaging seniors in the Netherlands, using ethics and aesthetics of care as sensitising concepts. The findings reveal that this work can promote relational forms of care. This study makes visible how different forms of care can be identified in a participatory art project.

Neurons in the cerebral cortex receive thousands of synaptic inputs per second from thousands of presynaptic neurons. How the dendritic location of inputs, their timing, strength, and presynaptic origin, in conjunction with complex dendritic physiology, impact the transformation of synaptic input into action potential (AP) output remains generally unknown for in vivo conditions. Here, we introduce a computational approach to reveal which properties of the input causally underlie AP output, and how this neuronal input-output computation is influenced by the morphology and biophysical properties of the dendrites. We demonstrate that this approach allows dissecting of how different input populations drive in vivo observed APs. For this purpose, we focus on fast and broadly tuned responses that pyramidal tract neurons in layer 5 (L5PTs) of the rat barrel cortex elicit upon passive single whisker deflections. By reducing a multi-scale model that we reported previously, we show that three features are sufficient to predict with high accuracy the sensory responses and receptive fields of L5PTs under these specific in vivo conditions: the count of active excitatory versus inhibitory synapses preceding the response, their spatial distribution on the dendrites, and the AP history. Based on these three features, we derive an analytically tractable description of the input-output computation of L5PTs, which enabled us to dissect how synaptic input from thalamus and different cell types in barrel cortex contribute to these responses. We show that the input-output computation is preserved across L5PTs despite morphological and biophysical diversity of their dendrites. We found that trial-to-trial variability in L5PT responses, and cell-to-cell variability in their receptive fields, are sufficiently explained by variability in synaptic input from the network, whereas variability in biophysical and morphological properties have minor contributions. Our approach to derive analytically tractable models of input-output computations in L5PTs provides a roadmap to dissect network-neuron interactions underlying L5PT responses across different in vivo conditions and for other cell types.

Summary: Hippocampal pyramidal neuron activity underlies episodic memory and spatial navigation. Although extensively studied in rodents, extremely little is known about human hippocampal pyramidal neurons, even though the human hippocampus underwent strong evolutionary reorganization and shows lower theta rhythm frequencies. To test whether biophysical properties of human Cornu Amonis subfield 1 (CA1) pyramidal neurons can explain observed rhythms, we map the morpho-electric properties of individual CA1 pyramidal neurons in human, non-pathological hippocampal slices from neurosurgery. Human CA1 pyramidal neurons have much larger dendritic trees than mouse CA1 pyramidal neurons, have a large number of oblique dendrites, and resonate at 2.9 Hz, optimally tuned to human theta frequencies. Morphological and biophysical properties suggest cellular diversity along a multidimensional gradient rather than discrete clustering. Across the population, dendritic architecture and a large number of oblique dendrites consistently boost memory capacity in human CA1 pyramidal neurons by an order of magnitude compared to mouse CA1 pyramidal neurons.

Background Artificial intelligence-derived software technologies have been developed that are intended to facilitate the review of computed tomography brain scans in patients with suspected stroke. Objectives To evaluate the clinical and cost-effectiveness of using artificial intelligence-derived software to support review of computed tomography brain scans in acute stroke in the National Health Service setting. Methods Twenty-five databases were searched to July 2021. The review process included measures to minimise error and bias. Results were summarised by research question, artificial intelligence-derived software technology and study type. The health economic analysis focused on the addition of artificial intelligence-derived software-assisted review of computed tomography angiography brain scans for guiding mechanical thrombectomy treatment decisions for people with an ischaemic stroke. The de novo model (developed in R Shiny, R Foundation for Statistical Computing, Vienna, Austria) consisted of a decision tree (short-term) and a state transition model (long-term) to calculate the mean expected costs and quality-adjusted life-years for people with ischaemic stroke and suspected large-vessel occlusion comparing artificial intelligence-derived software-assisted review to usual care. Results A total of 22 studies (30 publications) were included in the review; 18/22 studies concerned artificial intelligence-derived software for the interpretation of computed tomography angiography to detect large-vessel occlusion. No study evaluated an artificial intelligence-derived software technology used as specified in the inclusion criteria for this assessment. For artificial intelligence-derived software technology alone, sensitivity and specificity estimates for proximal anterior circulation large-vessel occlusion were 95.4% (95% confidence interval 92.7% to 97.1%) and 79.4% (95% confidence interval 75.8% to 82.6%) for Rapid (iSchemaView, Menlo Park, CA, USA) computed tomography angiography, 91.2% (95% confidence interval 77.0% to 97.0%) and 85.0 (95% confidence interval 64.0% to 94.8%) for Viz LVO (Viz.ai, Inc., San Fransisco, VA, USA) large-vessel occlusion, 83.8% (95% confidence interval 77.3% to 88.7%) and 95.7% (95% confidence interval 91.0% to 98.0%) for Brainomix (Brainomix Ltd, Oxford, UK) e-computed tomography angiography and 98.1% (95% confidence interval 94.5% to 99.3%) and 98.2% (95% confidence interval 95.5% to 99.3%) for Avicenna CINA (Avicenna AI, La Ciotat, France) large-vessel occlusion, based on one study each. These studies were not considered appropriate to inform cost-effectiveness modelling but formed the basis by which the accuracy of artificial intelligence plus human reader could be elicited by expert opinion. Probabilistic analyses based on the expert elicitation to inform the sensitivity of the diagnostic pathway indicated that the addition of artificial intelligence to detect large-vessel occlusion is potentially more effective (quality-adjusted life-year gain of 0.003), more costly (increased costs of £8.61) and cost-effective for willingness-to-pay thresholds of £3380 per quality-adjusted life-year and higher. Limitations and conclusions The available evidence is not suitable to determine the clinical effectiveness of using artificial intelligence-derived software to support the review of computed tomography brain scans in acute stroke. The economic analyses did not provide evidence to prefer the artificial intelligence-derived software strategy over current clinical practice. However, results indicated that if the addition of artificial intelligence-derived software-assisted review for guiding mechanical thrombectomy treatment decisions increased the sensitivity of the diagnostic pathway (i.e. reduced the proportion of undetected large-vessel occlusions), this may be considered cost-effective. Future work Large, preferably multicentre, studies are needed (for all artificial intelligence-derived software technologies) that evaluate these technologies as they would be implemented in clinical practice. Study registration This study is registered as PROSPERO CRD42021269609. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR133836) and is published in full in Health Technology Assessment; Vol. 28, No. 11. See the NIHR Funding and Awards website for further award information. Plain language summary Stroke is a serious life-threatening medical condition caused by a blood clot or haemorrhage in the brain. Quick and effective management, including a brain scan, of the patients with suspected stroke can make a big difference in their outcome. Artificial intelligence-derived computer programmes exist that are intended to help with the interpretation of computed tomography scans of the brain in stroke. We undertook a thorough review of the existing research into the effectiveness and value for money of using these programmes to help doctors and other specialists to interpret computed tomography brain scans. We found very little evidence to tell us how well artificial intelligence-derived computer programmes work in practice. Some studies have looked at artificial intelligence-derived computer programmes on their own (i.e. not taken together with a doctor’s judgement, as they were designed to be used). Other studies have looked at what happens to patients who are treated for stroke when artificial intelligence-derived computer programmes are used; these studies provide no information about whether using artificial intelligence-derived computer programmes may have led to patients who could have benefitted from treatment being missed. It is unclear how well artificial intelligence-derived software-assisted review works when added to current clinical practice. Scientific summary Background The primary population for this assessment was people presenting or attending secondary care with a suspected acute stroke who were last known to be well within the previous 24 hours. Stroke is a serious life-threatening medical condition defined by the World Health Organization (WHO) as a clinical syndrome consisting of ‘rapidly developing clinical signs of focal (at times global) disturbance of cerebral function, lasting more than 24 hours or leading to death with no apparent cause other than that of vascular origin’. Timely and effective management of the patients with suspected stroke substantially impacts patients’ outcomes. A number of software products with artificial intelligence (AI)-derived software technologies have been developed, which are intended to facilitate the review of computed tomography (CT) images of the brain in patients with suspected stroke. These products are not intended to provide a diagnosis but to support review and reporting healthcare professionals. Objectives This assessment aimed to evaluate the clinical and cost-effectiveness of using AI-derived software to support the review of CT brain scans in acute stroke, in the NHSs setting. Three research questions were considered. (1) Does AI-derived software-assisted review of non-enhanced CT brain scans for guiding thrombolysis treatment decisions for people with suspected acute stroke represent a clinically and cost-effective use of NHS resources? (2a) Does AI-derived software-assisted review of CT angiography (CTA) brain scans for guiding mechanical thrombectomy treatment decisions for people with an ischaemic stroke represent a clinically and cost-effective use of NHS resources? (2b) Does AI-derived software-assisted review of CT perfusion brain scans for guiding mechanical thrombectomy treatment decisions for people with an ischaemic stroke after a CTA brain scan represent a clinically and cost-effective use of NHS resources? Methods Assessment of clinical effectiveness Twenty-five databases, including MEDLINE and Embase, research registers, conference proceedings and a preprint resource, were searched for relevant studies from inception to July 2021; update searches were conducted in October 2021. Search results were screened for relevance independently by two reviewers. Full-text inclusion assessment, data extraction and quality assessment were conducted by one reviewer and checked by a second. The methodological quality of included diagnostic test accuracy studies was assessed using QUADAS-2 (Bristol Medical School, University of Bristol, Bristol, UK). The methodological quality of observational ‘before and after’ studies was assessed using a checklist, devised by the authors, for this review. The hierarchical summary receiver operating characteristic (HSROC) model was used to estimate summary sensitivity and specificity with 95% confidence intervals (CIs) and prediction regions around the summary points, and to derive HSROC curves for meta-analyses of diagnostic test accuracy, where four or more studies evaluated the same intervention for a given research question. All other results, including those of ‘before and after’ studies, were summarised in a narrative synthesis, grouped by research question addressed, AI-derived software evaluated and study type. Assessment of cost-effectiveness The health economic analysis focused on research question 2a: (2a) Does AI-derived software-assisted review of CT angiography brain scans for guiding mechanical thrombectomy treatment decisions for people with an ischaemic stroke represent a clinically and cost-effective use of NHS resources? All diagnostic accuracy studies identified by the systematic review conducted for this assessment assessed the accuracy of AI-derived software technologies as stand-alone interventions. As a result, information about how AI-derived software technologies would perform when used as an adjunct/aid to human readers (i.e. as recommended by the manufacturers, as specified for this assessment and as they would be used in clinical practice) is lacking. This is because the accuracy of the device by itself tells us nothing about how, or indeed whether, it might improve the accuracy of a human reader. It would not make sense to infer that any of the variation in sensitivity observed between stand-alone AIs can tell us something about precisely the variation in a hypothetical, small improvement in sensitivity of the human reader. To perform cost-effectiveness analysis (CEA), we elicited expert opinion to estimate the diagnostic accuracy of AI as adjunct to human reader. Experts were provided with the evidence on AI alone and human reader alone. Because it was considered too difficult for experts to differentiate between different AI-derived software-assisted review technologies, AI-derived software-assisted review in general (not specified by manufacturer or specific technology) is considered. The de novo model (developed in R Shiny, R Foundation for Statistical Computing, Vienna, Austria) consisted of a decision tree (short-term) and a state transition model (long-term) to calculate the mean expected costs and quality-adjusted life-years (QALYs) for people with ischaemic stroke and suspected large-vessel occlusion (LVO). The decision tree was used to estimate short-term costs and consequences (first 90 days). Subsequently, patients with LVO were classified as either eligible for thrombectomy or not eligible. Those with both LVO and eligibility for thrombectomy were further classified, based on the sensitivity of the diagnostic strategy, into whether a LVO was detected (and thus thrombectomy received) or not. Based on the classification in the decision tree, patients were subdivided into health states according to the modified Rankin Scale (mRS). Notably, patients without LVO were subdivided based on the specificity of the diagnostic strategy into whether a LVO was incorrectly detected or not. If a LVO was incorrectly detected (i.e. false positive), this had cost consequences only (e.g. due to potential unnecessary transfer to experienced stroke centre qualified to perform thrombectomy). The long-term consequences in terms of costs and QALYs were estimated using a state transition cohort model with a lifetime time horizon (annual cycle length) and health states defined as per mRS states. Probabilistic sensitivity analyses, deterministic sensitivity analyses and scenario analyses were performed. Results Assessment of clinical effectiveness A total of 22 studies (30 publications) were included in the review; for 9 of the 13 manufacturers of AI-derived software included in the scope, no studies were identified. All included studies concerned AI-derived software produced by Avicenna, Brainomix, iSchemaView or Viz. The majority (18/22 studies) reported data concerning research question 2a (i.e. evaluated AI-derived software for the interpretation of CTA). All included studies either assessed the diagnostic accuracy of AI-derived software alone (i.e. not as it would be used in clinical practice, as recommended by the manufacturers and as specified in the inclusion criteria for this assessment) or were ‘before and after’ observational studies reporting information about the effects of implementing AI-derived software in treated patients. Eleven studies provided information about the accuracy of various AI-derived software technologies for the detection of LVO on CTA scans in patients with acute ischaemic stroke. Where the target condition included occlusions of internal carotid artery, carotid terminus or the M1 or M2 segments of the middle cerebral artery (MCA), the sensitivity and specificity estimates were 95.4% (95% CI 92.7% to 97.1%) and 79.4% (95% CI 75.8% to 82.6%) for Rapid CTA (iSchemaView, Menlo Park, CA, USA), 91.2% (95% CI 77.0% to 97.0%) and 85.0 (95% CI 64.0% to 94.8%) for Viz LVO, 83.8% (95% CI 77.3% to 88.7%) and 95.7% (95% CI 91.0% to 98.0%) for Brainomix e-CTA, and 98.1% (95% CI 94.5% to 99.3%) and 98.2% (95% CI 95.5% to 99.3%) for Avicenna CINA LVO, based on one study each. There was some evidence to indicate that, where studies included more distal (e.g. M3 segment of the MCA) elements of the anterior circulation or included posterior circulation in their definition of the target condition, sensitivity was reduced. All four studies that provided information about the effects of implementing Viz LVO and one study that provided information about the effects of implementing Rapid CTA reported that implementation was associated with reductions in time to treatment for thrombectomy patients and, where reported, with no significant change in clinical outcomes (mRS). However, it should be noted that two of the studies of Viz LVO and the study of Rapid CTA evaluated implementation in the context of providing an automated alert system (i.e. not as specified in the scope for this assessment); it is plausible that reductions in time to intervention, observed in these studies, may be driven by this ‘early alert’ step. The information provided by studies of this type is also limited in that it concerns only treated (i.e. test positive) patients; no information is provided about test negative patients and hence there is no information about the extent to which AI-derived software, as implemented, may miss patients with LVO. There is no evidence about the accuracy of AI-derived software when used as an aid to human interpretation; all evidence concerns only stand-alone AI. This might imply that a CEA is not feasible for any of the three research questions. However, we conducted a CEA in relation to the research question 2a, where there is most evidence about the performance of AI-derived software technologies alone and one study comparing an AI-derived software technology alone with human reader alone. These studies were not considered appropriate to inform cost-effectiveness modelling but formed the basis by which the accuracy of AI plus human reader could be elicited by expert opinion. Assessment of cost-effectiveness Base-case analysis The probabilistic results indicated that the addition of AI to detect LVO is potentially more effective (QALY gain of 0.003), more costly (increased costs of £8.61) and cost-effective for willingness-to-pay thresholds of £3380 per QALY and higher. The cost-effectiveness plane illustrated the negative correlation between incremental costs and incremental QALYs; that is if a technology is more effective it also tends to be less costly. The cost-effectiveness acceptability curve indicated that at willingness-to-pay values of £20,000 and £30,000 per QALY gained the probabilities of current practice with AI being cost-effective are 54% and 56%, respectively. The expected risks per patient associated with adding AI at willingness-to-pay values of £20,000 and £30,000 per QALY gained are £80 and £95, respectively (these were £122 and £163 respectively without adding AI; see expected loss curves). At a population level (assuming 87,635 patients imaged, per year, in the UK), the estimated annual risks associated with adding AI are £7.0 million and £8.4 million, at willingness-to-pay values of £20,000 and £30,000 per QALY gained, respectively. Secondary analysis sensitivity and scenario analyses Sensitivity analyses indicated that the sensitivity of both technologies (i.e. with and without the addition of AI-derived software-assisted review) was the most important input parameter. In addition, the proportion of patients with LVO that are eligible for mechanical thrombectomy is important to determine the most optimal strategy in terms of costs and QALYs. For the estimated costs (specificity), the additional costs of the AI technology, costs related to mRS 4 and mRS 5 were input parameters (in addition to those mentioned above), which can change the strategy that is most expensive. Consistently, the most influential scenario analyses were related to the sensitivity (for both strategies), the proportion of patients with LVO eligible for mechanical thrombectomy with AI, removing the general population mortality cap and the additional costs of the AI technology. Conclusions The available evidence is not suitable to determine the clinical effectiveness of using AI-derived software to support the review of CT brain scans in acute stroke. The economic analyses did not provide evidence to prefer the AI-derived software strategy over current clinical practice. However, results indicated that if the addition of AI-derived software-assisted review for guiding mechanical thrombectomy treatment decisions increased the sensitivity of the diagnostic pathway (i.e. reduced the proportion of undetected LVOs) this may be considered cost-effective. Nevertheless, the sensitivity of AI-derived software-assisted review when added to current clinical practice is largely uncertain and probably depends on the implementation of AI-derived software-assisted review. Study registration This study is registered as PROSPERO CRD42021269609. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR133836) and is published in full in Health Technology Assessment; Vol. 28, No. 11. See the NIHR Funding and Awards website for further award information.

Abstract Proton therapy is of great interest to pediatric cancer patients because of its optimal depth dose distribution. In view of healthy tissue damage and the increased risk of secondary cancers, we investigated DNA damage induction and repair of radiosensitive hematopoietic stem and progenitor cells (HSPCs) exposed to therapeutic proton and photon irradiation due to their role in radiation-induced leukemia. Human CD34+ HSPCs were exposed to 6 MV X-rays, mid- and distal spread-out Bragg peak (SOBP) protons at doses ranging from 0.5 to 2 Gy. Persistent chromosomal damage was assessed with the micronucleus assay, while DNA damage induction and repair were analyzed with the γ-H2AX foci assay. No differences were found in induction and disappearance of γ-H2AX foci between 6 MV X-rays, mid- and distal SOBP protons at 1 Gy. A significantly higher number of micronuclei was found for distal SOBP protons compared to 6 MV X-rays and mid- SOBP protons at 0.5 and 1 Gy, while no significant differences in micronuclei were found at 2 Gy. In HSPCs, mid-SOBP protons are as damaging as conventional X-rays. Distal SOBP protons showed a higher number of micronuclei in HSPCs depending on the radiation dose, indicating possible changes of the in vivo biological response.

Background: AT-MSCs display great immunoregulatory features, making them potential candidates for cell-based therapy. This study aimed to evaluate the “RBC lysis buffer” isolation protocol and immunological profiling of the so-obtained AT-MSCs. Methods: We established an immune-comparative screening of AT-MSCs throughout in vitro cell expansion (PM, P1, P2, P3, P4) and inflammatory priming regarding the expression of 28 cell-surface markers, 6 cytokines/chemokines, and 10 TLR patterns. Findings: AT-MSCs were highly expandable and sensitive to microenvironment challenges, hereby showing plasticity in distinct expression profiles. Both cell expansion and inflammation differentially modulated the expression profile of CD34, HLA-DR, CD40, CD62L, CD200 and CD155, CD252, CD54, CD58, CD106, CD274 and CD112. Inflammation resulted in a significant increase in the expression of the cytokines IL-6, IL-8, IL-1β, IL-1Ra, CCL5, and TNFα. Depending on the culture conditions, the expression of the TLR pattern was distinctively altered with TLR1–4, TLR7, and TLR10 being increased, whereas TLR6 was downregulated. Protein network and functional enrichment analysis showed that several trophic and immune responses are likely linked to these immunological changes. Conclusions: AT-MSCs may sense and actively respond to tissue challenges by modulating distinct and specific pathways to create an appropriate immuno-reparative environment. These mechanisms need to be further characterized to identify and assess a molecular target that can enhance or impede the therapeutic ability of AT-MSCs, which therefore will help improve the quality, safety, and efficacy of the therapeutic strategy.