Serial Correlations in Single-Subject fMRI with Sub-Second TR

When performing statistical analysis of single-subject fMRI data, serial correlations need to be taken into account to allow for valid inference. Otherwise, the variability in the parameter estimates might be under-estimated resulting in increased false-positive rates. Serial correlations in fMRI data are commonly characterized in terms of a first-order autoregressive (AR) process and then removed via pre-whitening. The required noise model for the pre-whitening depends on a number of parameters, particularly the repetition time (TR). Here we investigate how the sub-second temporal resolution provided by simultaneous multislice (SMS) imaging changes the noise structure in fMRI time series. We fit a higher-order AR model and then estimate the optimal AR model order for a sequence with a TR of less than 600 ms providing whole brain coverage. We show that physiological noise modelling successfully reduces the required AR model order, but remaining serial correlations necessitate an advanced noise model. We conclude that commonly used noise models, such as the AR(1) model, are inadequate for modelling serial correlations in fMRI using sub-second TRs. Rather, physiological noise modelling in combination with advanced pre-whitening schemes enable valid inference in single-subject analysis using fast fMRI sequences

Emittance measurements of Space Shuttle orbiter reinforced carbon-carbon

The spectral and total normal emittance of the Reinforced Carbon-Carbon (RCC) used on Space Shuttle nose cap and wing leading edges has been measured at room temperature and at surface temperatures of 1200 to 2100 K. These measurements were made on virgin and two flown RCC samples. Room temperature directional emittance data were also obtained and were used to determine the total hemispherical emittance of RCC as a function of temperature. Results of the total normal emittance for the virgin samples showed good agreement with the current RCC emittance design curve; however, the data from the flown samples showed an increase in the emittance at high temperature possibly due to exposure from flight environments

Online survey insight report: Involving children, young people, and families in our research

Insight report summarising the findings from an online public involvement survey to help shape child, young persons, and family research in North West London

The Social Work Online Team Training (SWOTT) toolkit: embedding team-based peer learning in continuous professional development

Continuous professional development (CPD) underpins safe, effec-tive practice by ensuring that social workers acquire and sustain up- to-date knowledge and skills. Additionally, CPD is critical to theoreti-cally rooted, evidence-informed decision-making and intervention. Despite the reported benefits, there are many barriers such as high caseloads and the time required to participate. This paper presents the findings from a proof-of-concept study which piloted a new model for CPD: the Social Work Online Team Training (SWOTT) toolkit. Each themed toolkit incorporates research evidence and/or new theoretical frameworks and is built upon a team-based, peer learning approach. Toolkits have two components: an online module and peer group supervision using a complex case study. The pilot and evaluation integrated two data collection workstreams: a pre- intervention survey and a post-intervention survey; and interviews. Participants reported that the CPD was relevant, accessible, enabling them to refresh knowledge of core theory and acquire new theore-tical and evidence-informed knowledge. The toolkit design facilitated deep learning as participants used the online training to critically discuss the complex case study using peer reflection. Overall, findings demonstrated the value of shared learning experiences through the combined modes of learning (online/in-person) resulting in evi-dence-informed CPD with real-world relevance to practice contexts

STK39 polymorphisms and blood pressure: an association study in British Caucasians and assessment of cis-acting influences on gene expression

<p>Abstract</p> <p>Background</p> <p>Blood pressure (BP) has significant heritability, but the genes responsible remain largely unknown. Single nucleotide polymorphisms (SNPs) at the <it>STK39 </it>locus were recently associated with hypertension by genome-wide association in an Amish population; <it>in vitro </it>data from transient transfection experiments using reporter constructs suggested that altered <it>STK39 </it>expression might mediate the effect. However, other large studies have not implicated <it>STK39 </it>in hypertension. We determined whether reported SNPs influenced <it>STK39 </it>expression <it>in vivo</it>, or were associated with BP in a large British Caucasian cohort.</p> <p>Methods</p> <p>1372 members of 247 Caucasian families ascertained through a hypertensive proband were genotyped for reported risk variants in <it>STK39 </it>(rs6749447, rs3754777, rs35929607) using Sequenom technology. MERLIN software was used for family-based association testing. <it>Cis</it>-acting influences on expression were assessed <it>in vivo </it>using allelic expression ratios in cDNA from peripheral blood cells in 35 South African individuals heterozygous for a transcribed SNP in <it>STK39 </it>(rs1061471) and quantified by mass spectrometry (Sequenom).</p> <p>Results</p> <p>No significant association was seen between the SNPs tested and systolic or diastolic BP in clinic or ambulatory measurements (all p > 0.05). The tested SNPs were all associated with allelic expression differences in peripheral blood cells (p < 0.05), with the most significant association for the intronic SNP rs6749447 (P = 9.9 × 10^-4). In individuals who were heterozygous for this SNP, on average the G allele showed 13% overexpression compared to the T allele.</p> <p>Conclusions</p> <p><it>STK39 </it>expression is modified by polymorphisms acting in <it>cis </it>and the typed SNPs are associated with allelic expression of this gene, but there is no evidence for an association with BP in a British Caucasian cohort.</p

Collateral donor artery physiology and the influence of a chronic total occlusion on fractional flow reserve

Background— The presence of a concomitant chronic total coronary occlusion (CTO) and a large collateral contribution might alter the fractional flow reserve (FFR) of an interrogated vessel, rendering the FFR unreliable at predicting ischemia should the CTO vessel be revascularized and potentially affecting the decision on optimal revascularization strategy. We tested the hypothesis that donor vessel FFR would significantly change after percutaneous coronary intervention of a concomitant CTO. Methods and Results— In consecutive patients undergoing percutaneous coronary intervention of a CTO, coronary pressure and flow velocity were measured at baseline and hyperemia in proximal and distal segments of both nontarget vessels, before and after percutaneous coronary intervention. Hemodynamics including FFR, absolute coronary flow, and the coronary flow velocity–pressure gradient relation were calculated. After successful percutaneous coronary intervention in 34 of 46 patients, FFR in the predominant donor vessel increased from 0.782 to 0.810 (difference, 0.028 [0.012 to 0.044]; P=0.001). Mean decrease in baseline donor vessel absolute flow adjusted for rate pressure product: 177.5 to 139.9 mL/min (difference −37.6 [−62.6 to −12.6]; P=0.005), mean decrease in hyperemic flow: 306.5 to 272.9 mL/min (difference, −33.5 [−58.7 to −8.3]; P=0.011). Change in predominant donor vessel FFR correlated with angiographic (%) diameter stenosis severity (r=0.44; P=0.009) and was strongly related to stenosis severity measured by the coronary flow velocity–pressure gradient relation (r=0.69; P&lt;0.001). Conclusions— Recanalization of a CTO results in a modest increase in the FFR of the predominant collateral donor vessel associated with a reduction in coronary flow. A larger increase in FFR is associated with greater coronary stenosis severity

Cognitive control mechanisms revealed by ERP and fMRI: Evidence from repeated task-switching

We investigated the extent to which a common neural mechanism is involved in task set-switching and response withholding, factors that are frequently confounded in task-switching and go/no-go paradigms. Subjects' brain activity was measured using event-related electrical potentials (ERPs) and event-related functional MRI (fMRI) neuroimaging in separate studies using the same cognitive paradigm. Subjects made compatible left/right keypress responses to left/right arrow stimuli of 1000 msec duration; they switched every two trials between responding at stimulus onset (GO task-green arrows) and stimulus offset (WAIT task-red arrows). Withholding an immediate response (WAIT vs. GO) elicited an enhancement of the frontal N2 ERP and lateral PFC activation of the right hemisphere, both previously associated with the "no-go" response, but only on switch trials. Task-switching (switch vs. nonswitch) was associated with frontal N2 amplification and right hemisphere ventrolateral PFC activation, but only for the WAIT task. The anterior cingulate cortex (ACC) was the only brain region to be activated for both types of task switch, but this activation was located more rostrally for the WAIT than for the GO switch trials. We conclude that the frontal N2 ERP and lateral PFC activation are not markers for withholding an immediate response or switching tasks per se, hut are associated with switching into a response-suppression mode. Different regions within the ACC may be involved in two processes integral to task-switching: processing response conflict (rostral ACC) and overcoming prior response suppression (caudal ACC)

Ultrafiltration for acute decompensated cardiac failure: A systematic review and meta-analysis

Background Ultrafiltration is a method used to achieve diuresis in acute decompensated heart failure (ADHF) when there is diuretic resistance, but its efficacy in other settings is unclear. We therefore conducted a systematic review and meta-analysis to evaluate the use of ultrafiltration in ADHF. Methods We searched MEDLINE and EMBASE for studies that evaluated outcomes following filtration compared to diuretic therapy in ADHF. The outcomes of interest were body weight change, change in renal function, length of stay, frequency of rehospitalization, mortality and dependence on dialysis. We performed random effects meta-analyses to pool studies that evaluated the desired outcomes and assessed statistical heterogeneity using the I2 statistic. Results A total of 10 trials with 857 participants (mean age 68 years, 71% male) compared filtration to usual diuretic care in ADHF. Nine studies evaluated weight change following filtration and the pooled results suggest a decline in mean body weight − 1.8; 95% CI, − 4.68 to 0.97 kg. Pooled results showed no difference between the filtration and diuretic group in change in creatinine or estimated glomerular filtration rate. The pooled results suggest longer hospital stay with filtration (mean difference, 3.70; 95% CI, − 3.39 to 10.80 days) and a reduction in heart failure hospitalization (RR, 0.71; 95% CI, 0.51–1.00) and all-cause rehospitalization (RR, 0.89; 95% CI, 0.43–1.86) compared to the diuretic group. Filtration was associated with a non-significant greater risk of death compared to diuretic use (RR, 1.08; 95% CI, 0.77–1.52)

FFNSL: feed-forward neural-symbolic learner

Logic-based machine learning aims to learn general, interpretable knowledge in a data-efficient manner. However, labelled data must be specified in a structured logical form. To address this limitation, we propose a neural-symbolic learning framework, called Feed-Forward Neural-Symbolic Learner (FFNSL), that integrates a logic-based machine learning system capable of learning from noisy examples, with neural networks, in order to learn interpretable knowledge from labelled unstructured data. We demonstrate the generality of FFNSL on four neural-symbolic classification problems, where different pre-trained neural network models and logic-based machine learning systems are integrated to learn interpretable knowledge from sequences of images. We evaluate the robustness of our framework by using images subject to distributional shifts, for which the pre-trained neural networks may predict incorrectly and with high confidence. We analyse the impact that these shifts have on the accuracy of the learned knowledge and run-time performance, comparing FFNSL to tree-based and pure neural approaches. Our experimental results show that FFNSL outperforms the baselines by learning more accurate and interpretable knowledge with fewer examples

Measurements of the diffuse Galactic synchrotron spectral index and curvature from MeerKLASS pilot data

21cm intensity mapping experiments are bringing an influx of high spectral resolution observational data in the $\sim100$ MHz $- 1$ GHz regime. We use pilot $971-1075$ MHz data from MeerKAT in single-dish mode, recently used to test the calibration and data reduction scheme of the upcoming MeerKLASS survey, to probe the spectral index of diffuse synchrotron emission below 1 GHz within $145^{\circ} < \alpha < 180^{\circ}$, $-1^{\circ} < \delta < 8^{\circ}$. Through comparisons with data from the OVRO Long Wavelength Array and the Maipu and MU surveys, we find an average spectral index of $-2.75 < \beta < -2.71$ between 45 and 1055 MHz. By fitting for spectral curvature with a spectral index of the form $\beta + c \, {\rm{ln}}(\nu / 73~{\rm MHz})$, we measure $\beta = -2.55 \pm 0.13$ and $c = -0.12 \pm 0.05$ within our target field. Our results are in good agreement (within $1\sigma$) with existing measurements from experiments such as ARCADE2 and EDGES. These results show the calibration accuracy of current data and demonstrate that MeerKLASS will also be capable of achieving a secondary science goal of probing the interstellar medium.Comment: 17 pages, 13 figures, accepted for publication in MNRAS. Updated to match published paper (additional references and acknowledgements