Predicting recovery following stroke: deep learning, multimodal data and feature selection using explainable AI

Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of the datasets available for learning, and how to effectively combine neuroimaging and tabular data (e.g. demographic information and clinical characteristics). This paper evaluates several solutions based on two strategies. The first is to use 2D images that summarise MRI scans. The second is to select key features that improve classification accuracy. Additionally, we introduce the novel approach of training a convolutional neural network (CNN) on images that combine regions-of-interest extracted from MRIs, with symbolic representations of tabular data. We evaluate a series of CNN architectures (both 2D and a 3D) that are trained on different representations of MRI and tabular data, to predict whether a composite measure of post-stroke spoken picture description ability is in the aphasic or non-aphasic range. MRI and tabular data were acquired from 758 English speaking stroke survivors who participated in the PLORAS study. The classification accuracy for a baseline logistic regression was 0.678 for lesion size alone, rising to 0.757 and 0.813 when initial symptom severity and recovery time were successively added. The highest classification accuracy 0.854 was observed when 8 regions-of-interest was extracted from each MRI scan and combined with lesion size, initial severity and recovery time in a 2D Residual Neural Network.Our findings demonstrate how imaging and tabular data can be combined for high post-stroke classification accuracy, even when the dataset is small in machine learning terms. We conclude by proposing how the current models could be improved to achieve even higher levels of accuracy using images from hospital scanners

Population Pharmacokinetics of Liposomal Amphotericin B in Immunocompromised Children

BACKGROUND Liposomal amphotericin B (LAmB) is widely used in the treatment of invasive fungal disease (IFD) in adults and children. There are relatively limited PK data to inform optimal dosing in children that achieves systemic drug exposures comparable to those of adults. OBJECTIVES To describe the pharmacokinetics of LAmB in children aged 1-17 years with suspected or documented IFD. METHODS Thirty-five children were treated with LAmB at dosages of 2.5-10 mg kg(-1) daily. Samples were taken at baseline and at 0.5-2.0 hourly intervals for twenty-four hours after receipt of the first dose (n=35 patients) and on the final day of therapy (n=25 patients). LAmB was measured using high performance liquid chromatography (HPLC). The relationship between drug exposure and development of toxicity was explored. RESULTS An evolution in PK was observed during the course of therapy resulting in a proportion of patients (n=13) having significantly higher maximum serum concentration (Cmax) and area under the concentration time curve (AUC0-24) later in the course of therapy, without evidence of drug accumulation (Cmin accumulation ratio, AR < 1.2). The fit of a 2-compartment model incorporating weight and an exponential decay function describing volume of distribution best described the data. There was a statistically significant relationship between mean AUC0-24 and probability of nephrotoxicity (OR 2.37; 95% CI 1.84-3.22, p=0.004). CONCLUSIONS LAmB exhibits nonlinear pharmacokinetics. A third of children appear to experience a time-dependent change in PK, which is not explained by weight, maturation or observed clinical factors

The impact of sample size on the reproducibility of voxel-based lesion-deficit mappings

This study investigated how sample size affects the reproducibility of findings from univariate voxel-based lesion-deficit analyses (e.g., voxel-based lesion-symptom mapping and voxel-based morphometry). Our effect of interest was the strength of the mapping between brain damage and speech articulation difficulties, as measured in terms of the proportion of variance explained. First, we identified a region of interest by searching on a voxel-by-voxel basis for brain areas where greater lesion load was associated with poorer speech articulation using a large sample of 360 right-handed English-speaking stroke survivors. We then randomly drew thousands of bootstrap samples from this data set that included either 30, 60, 90, 120, 180, or 360 patients. For each resample, we recorded effect size estimates and p values after conducting exactly the same lesion-deficit analysis within the previously identified region of interest and holding all procedures constant. The results show (1) how often small effect sizes in a heterogeneous population fail to be detected; (2) how effect size and its statistical significance varies with sample size; (3) how low-powered studies (due to small sample sizes) can greatly over-estimate as well as under-estimate effect sizes; and (4) how large sample sizes (N ≥ 90) can yield highly significant p values even when effect sizes are so small that they become trivial in practical terms. The implications of these findings for interpreting the results from univariate voxel-based lesion-deficit analyses are discussed.</p

The Role of Compensatory Beliefs in Rationalizing Environmentally Detrimental Behaviors

Compensatory green beliefs (CGBs) reflect the idea that a pro-environmental behavior (e.g., recycling) can off-set the negative effects of an environmentally detrimental behavior (e.g., driving). It is thought that CGBs might help explain why people act in ways that appear to contradict their pro-environmental intentions, and inconsistently engage in pro-environmental behaviors. The present study sought to investigate the nature and use of CGBs. A series of interviews suggested that participants endorsed CGBs to: (a) reduce feelings of guilt with respect to (the assumed or actual) negative environmental impact of their actions, and (b) to defend their green credentials in social situations. Participants also justified detrimental behaviors on the basis of higher loyalties (e.g., family’s needs), or the perceived difficulty of performing more pro-environmental actions. In addition to shedding light on how, when, and why people might hold and use CGBs, the research also provides new insight into how CGBs should be assessed

Predicting online behavioural responses to transcranial direct current stimulation in stroke patients with anomia

Anomia, or difficulty naming common objects, is the most common, acquired impairment of language. Effective therapeutic interventions for anomia typically involve massed practice at high doses. This requires significant investment from patients and therapists. Aphasia researchers have increasingly looked to neurostimulation to accelerate these treatment effects, but the evidence behind this intervention is sparse and inconsistent. Here, we hypothesised that group-level neurostimulation effects might belie a more systematic structure at the individual level. We sought to test the hypothesis by attempting to predict the immediate (online), individual-level behavioural effects of anodal and sham neurostimulation in 36 chronic patients with anomia, performing naming and size judgement tasks. Using clinical, (pre-stimulation) behavioural and MRI data, as well as Partial Least Squares regression, we attempted to predict neurostimulation effects on accuracies and reaction times of both tasks. Model performance was assessed via cross-validation. Predictive performances were compared to that of a null model, which predicted the mean neurostimulation effects for all patients. Models derived from pre-stimulation data consistently outperformed the null model when predicting neurostimulation effects on both tasks’ performance. Notably, we could predict behavioural declines just as well as improvements. In conclusion, inter-patient variation in online responses to neurostimulation is, to some extent, systematic and predictable. Since declines in performance were just as predictable as improvements, the behavioural effects of neurostimulation in patients with anomia are unlikely to be driven by placebo effects. However, the online effect of the intervention appears to be as likely to interfere with task performance as to improve it

Rac1 Dynamics in the Human Opportunistic Fungal Pathogen Candida albicans

The small Rho G-protein Rac1 is highly conserved from fungi to humans, with approximately 65% overall sequence identity in Candida albicans. As observed with human Rac1, we show that C. albicans Rac1 can accumulate in the nucleus, and fluorescence recovery after photobleaching (FRAP) together with fluorescence loss in photobleaching (FLIP) studies indicate that this Rho G-protein undergoes nucleo-cytoplasmic shuttling. Analyses of different chimeras revealed that nuclear accumulation of C. albicans Rac1 requires the NLS-motifs at its carboxyl-terminus, which are blocked by prenylation of the adjacent cysteine residue. Furthermore, we show that C. albicans Rac1 dynamics, both at the plasma membrane and in the nucleus, are dependent on its activation state and in particular that the inactive form accumulates faster in the nucleus. Heterologous expression of human Rac1 in C. albicans also results in nuclear accumulation, yet accumulation is more rapid than that of C. albicans Rac1. Taken together our results indicate that Rac1 nuclear accumulation is an inherent property of this G-protein and suggest that the requirements for its nucleo-cytoplasmic shuttling are conserved from fungi to humans

Quantum superchemistry: Role of trapping profile and quantum statistics

The process of Raman photoassociation of a trapped atomic condensate to form condensed molecules has been labeled superchemistry because it can occur at 0 K and experiences coherent bosonic stimulation. We show here that the differences from ordinary chemical processes go even deeper, with the conversion rates depending on the quantum state of the reactants, as expressed by the Wigner function. We consider different initial quantum states of the trapped atomic condensate and different forms of the confining potentials, demonstrating the importance of the quantum statistics and the extra degrees of freedom which massive particles and trapping potentials make available over the analogous optical process of second-harmonic generation. We show that both mean-field analyses and quantum calculations using an inappropriate initial condition can make inaccurate predictions for a given system. This is possible whether using a spatially dependent analysis or a zero-dimensional approach as commonly used in quantum optics

Predictors of Radiotherapy Induced Bone Injury (RIBI) after stereotactic lung radiotherapy

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to identify clinical and dosimetric factors associated with radiotherapy induced bone injury (RIBI) following stereotactic lung radiotherapy.</p> <p>Methods</p> <p>Inoperable patients with early stage non-small cell lung cancer, treated with SBRT, who received 54 or 60 Gy in 3 fractions, and had a minimum of 6 months follow up were reviewed. Archived treatment plans were retrieved, ribs delineated individually and treatment plans re-computed using heterogeneity correction. Clinical and dosimetric factors were evaluated for their association with rib fracture using logistic regression analysis; a dose-event curve and nomogram were created.</p> <p>Results</p> <p>46 consecutive patients treated between Oct 2004 and Dec 2008 with median follow-up 25 months (m) (range 6 – 51 m) were eligible. 41 fractured ribs were detected in 17 patients; median time to fracture was 21 m (range 7 – 40 m). The mean maximum point dose in non-fractured ribs (n = 1054) was 10.5 Gy ± 10.2 Gy, this was higher in fractured ribs (n = 41) 48.5 Gy ± 24.3 Gy (p < 0.0001). On univariate analysis, age, dose to 0.5 cc of the ribs (D_0.5), and the volume of the rib receiving at least 25 Gy (V₂₅), were significantly associated with RIBI. As D_0.5 and V₂₅ were cross-correlated (Spearman correlation coefficient: 0.57, p < 0.001), we selected D_0.5 as a representative dose parameter. On multivariate analysis, age (odds ratio: 1.121, 95% CI: 1.04 – 1.21, p = 0.003), female gender (odds ratio: 4.43, 95% CI: 1.68 – 11.68, p = 0.003), and rib D_0.5 (odds ratio: 1.0009, 95% CI: 1.0007 – 1.001, p < 0.0001) were significantly associated with rib fracture.</p> <p>Using D_0.5, a dose-event curve was constructed estimating risk of fracture from dose at the median follow up of 25 months after treatment. In our cohort, a 50% risk of rib fracture was associated with a D_0.5 of 60 Gy.</p> <p>Conclusions</p> <p>Dosimetric and clinical factors contribute to risk of RIBI and both should be included when modeling risk of toxicity. A nomogram is presented using D_0.5, age, and female gender to estimate risk of RIBI following SBRT. This requires validation.</p

PPARα and PPARγ activation is associated with pleural mesothelioma invasion but therapeutic inhibition is ineffective

Mesothelioma is a cancer that typically originates in the pleura of the lungs. It rapidly invades the surrounding tissues, causing pain and shortness of breath. We compared cell lines injected either subcutaneously or intrapleurally and found that only the latter resulted in invasive and rapid growth. Pleural tumors displayed a transcriptional signature consistent with increased activity of nuclear receptors PPARα and PPARγ and with an increased abundance of endogenous PPAR-activating ligands. We found that chemical probe GW6471 is a potent, dual PPARα/γ antagonist with anti-invasive and anti-proliferative activity in vitro. However, administration of GW6471 at doses that provided sustained plasma exposure levels sufficient for inhibition of PPARα/γ transcriptional activity did not result in significant anti-mesothelioma activity in mice. Lastly, we demonstrate that the in vitro anti-tumor effect of GW6471 is off-target. We conclude that dual PPARα/γ antagonism alone is not a viable treatment modality for mesothelioma

Mead-halls of the Oiscingas: a new Kentish perspective on the Anglo-Saxon great hall complex phenomenon

Widely cited as a metaphor for the emergence of kingship in early medieval England, the great hall complex represents one of the most distinctive and evocative expressions of the Anglo-Saxon settlement record, yet interpretation of these sites remains underdeveloped and heavily weighted towards Yeavering. Inspired by the results of recent excavations at Lyminge, this paper undertakes a detailed comparative interrogation of three great hall complexes in Kent and exploits this new regional perspective to advance understanding of the agency and embodied meanings of these settlements as ‘theatres of power’. Explored through the thematic prisms of place, social memory and monumental hybridity, this examination leads to a new appreciation of the involvement of great hall sites in the genealogical strategies of 7th-century royal dynasties and a fresh perspective on how this remarkable yet short-lived monumental idiom was adapted to harness the symbolic capital of Romanitas