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Background Cerebral small vessel disease (SVD) leads to reduced quality of life (QOL), but the mechanisms underlying this relationship remain unknown. This study investigated multivariate relationships between radiological markers of SVD and domain‐specific QOL deficits, as well as potential mediators, in patients with SVD. Methods Clinical and neuroimaging measures were obtained from a pooled sample of 174 SVD patients from the St. George's Cognition and Neuroimaging in Stroke and PRESsure in established cERebral small VEssel disease studies. Lacunes, white matter hyperintensities, and microbleeds were defined as radiological markers of SVD and delineated using MRI. QOL was assessed using the Stroke‐Specific Quality of Life Scale. Multivariate linear regression was used to determine whether SVD markers were associated with domain‐specific QOL deficits. Significant associations were further investigated using mediation analysis to examine whether functional disability or cognition was potential mediators. Results Multivariate regression analyses revealed that lacunes were associated with total QOL score (β = −8.22, p = .02), as well as reductions in mobility (β = −1.41, p = .008) and language‐related subdomains (β = −0.69, p = .033). White matter hyperintensities and microbleeds showed univariate correlations with QOL, but these became nonsignificant during multivariate analyses. Mediation analyses revealed that functional disability, defined as reduced activities of daily living, and executive function, partially mediated the relationship between lacunes and total QOL, as well as mobility‐related QOL, but not language‐related QOL. Conclusions Lacunar infarcts have the most detrimental effect on QOL in SVD patients, particularly in the mobility and language‐related subdomains. These effects may be partially explained by a reduction in activities of daily living. These results may inform targeted interventions to improve QOL in patients with SVD. Fernando et al. investigate associations between radiological markers of cerebral small vessel disease (SVD) and subdomains of quality of life (QOL). In a pooled sample of SVD patients, they find that lacunes lead to reductions in total QOL, as well as mobility and language‐related QOL, and explore potential mediating variables. These results suggest the possibility of targeted interventions to improve QOL in SVD patients.

The perch landing maneuver of a wing-deforming unmanned aerial vehicle (UAV) was investigated through a framework that uses the free, open-source OpenFOAM with 6 degrees of freedom (6DOF) simulations. The framework uses a moving grid to follow the trajectory of the UAV, reducing computational resources. Together with the ability to allow internal grid deformation, sliding mesh, and algorithm addition, it can accurately mimic the entire landing process. Different wing deformation speeds, additional elevator rotation and emulated propeller lift were added to the 6DOF simulations to investigate their effects on the landing maneuver. The results showed that the wing deformation retraction speed has a considerable effect on the trajectory and velocity of the UAV. The wing deformation reduced the forward velocity of the UAV by 32%, from 13.89 to 9 m/s. With the elevator control, the velocity was reduced to 5 m/s. Lastly, and an activation time of 1 s for the emulated propeller lift can further decrease the velocity to around 4.2 m/s. A better algorithm for the emulated propeller lift may be able to give a superior performance. This framework allows us to understand the underlying perch landing maneuver aerodynamics. It can also be used on problems like fast-turning agile and flapping wing flight.

Peptide nanotechnology has experienced a long and enduring development since its inception. Many different applications have been conceptualized, which depends on the functional groups present on the peptide and the physical shape/size of the peptide nanostructures. One of the most prominent nanostructures formed by peptides are nanoparticles. Until recently, however, it has been challenging to engineer peptide nanoparticles with low dispersity. An emerging and promising technique involves the utility of microfluidics to produce a solution of peptide nanoparticles with narrow dispersity. In this process, two or more streams of liquid are focused together to create conditions that are conducive towards the formation of narrowly dispersed samples of peptide nanoparticles. This makes it possible to harness peptide nanoparticles for the myriad of applications that are dependent on nanoparticle size and uniformity. In this focus review, we aim to show how microfluidics may be utilized to (1) study peptide self-assembly, which is critical to controlling nanostructure shape and size, and peptide-interface interactions, and (2) generate self-assembling peptide-based microgels for miniaturized cell cultures. These examples will illustrate how the emerging microfluidic approach promises to revolutionize the production and application of peptide nanoparticles in ever more diverse fields than before.

BackgroundObesity is a risk factor for both cardiovascular disease and dementia, but the mechanisms underlying this association are not fully understood. We examined associations between obesity, including estimates of central obesity using different modalities, with brain gray matter (GM) volume in the UK Biobank, a large population-based cohort study.MethodsTo determine relationships between obesity and the brain we used brain MRI, abdominal MRI, dual-energy X-ray absorptiometry (DXA), and bioelectric whole-body impedance. We determined whether obesity was associated with any change in brain gray matter (GM) and white matter (WM) volumes, and brain network efficiency derived from the structural connectome (wiring of the brain) as determined from diffusion-tensor MRI tractography. Using Waist-Hip Ratio (WHR), abdominal MRI and DXA we determined whether any associations were primarily with central rather than peripheral obesity, and whether associations were mediated by known cardiovascular risk factors. We analyzed brain MRI data from 15,634.ResultsWe found that central obesity, was associated with decreased GM volume (anthropometric data: p = 6.7 × 10−16, DXA: p = 8.3 × 10−81, abdominal MRI: p = 0.0006). Regional associations were found between central obesity and with specific GM subcortical nuclei (thalamus, caudate, pallidum, nucleus accumbens). In contrast, no associations were found with WM volume or structure, or brain network efficiency. The effects of central obesity on GM volume were not mediated by C-reactive protein or blood pressure, glucose, lipids.ConclusionsCentral body-fat distribution rather than the overall body-fat percentage is associated with gray matter changes in people with obesity. Further work is required to identify the factors that mediate the association between central obesity and GM atrophy.

ObjectiveTo determine whether apathy or depression predicts all-cause dementia in small vessel disease (SVD) patients.MethodsAnalyses used two prospective cohort studies of SVD: St. George’s Cognition and Neuroimaging in Stroke (SCANS; n=121) and Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC; n=352). Multivariate Cox regressions were used to predict dementia using baseline apathy and depression scores in both datasets. Change in apathy and depression was used to predict dementia in a subset of 104 participants with longitudinal data from SCANS. All models were controlled for age, education and cognitive function.ResultsBaseline apathy scores predicted dementia in SCANS (HR 1.49, 95% CI 1.05 to 2.11, p=0.024) and RUN DMC (HR 1.05, 95% CI 1.01 to 1.09, p=0.007). Increasing apathy was associated with dementia in SCANS (HR 1.53, 95% CI 1.08 to 2.17, p=0.017). In contrast, baseline depression and change in depression did not predict dementia in either dataset. Including apathy in predictive models of dementia improved model fit.ConclusionsApathy, but not depression, may be a prodromal symptom of dementia in SVD, and may be useful in identifying at-risk individuals.

There has been much interest in how the hippocampus codes time in support of episodic memory. Notably, while rodent hippocampal neurons, including populations in subfield CA1, have been shown to represent the passage of time in the order of seconds between events, there is limited support for a similar mechanism in humans. Specifically, there is no clear evidence that human hippocampal activity during long-term memory processing is sensitive to temporal duration information that spans seconds. To address this gap, we asked participants to first learn short event sequences that varied in image content and interval durations. During fMRI, participants then completed a recognition memory task, as well as a recall phase in which they were required to mentally replay each sequence in as much detail as possible. We found that individual sequences could be classified using activity patterns in the anterior hippocampus during recognition memory. Critically, successful classification was dependent on the conjunction of event content and temporal structure information (with unsuccessful classification of image content or interval duration alone), and further analyses suggested that the most informative voxels resided in the anterior CA1. Additionally, a classifier trained on anterior CA1 recognition data could successfully identify individual sequences from the mental replay data, suggesting that similar activity patterns supported participants’ recognition and recall memory. Our findings complement recent rodent hippocampal research, and provide evidence that long-term sequence memory representations in the human hippocampus can reflect duration information in the order of seconds.

ObjectivesTo investigate whether longitudinal structural network efficiency is associated with cognitive decline and whether baseline network efficiency predicts mortality in cerebral small vessel disease (SVD).MethodsA prospective, single-centre cohort consisting of 277 non-demented individuals with SVD was conducted. In 2011 and 2015, all participants were scanned with MRI and underwent neuropsychological assessment. We computed network properties using graph theory from probabilistic tractography and calculated changes in psychomotor speed and overall cognitive index. Multiple linear regressions were performed, while adjusting for potential confounders. We divided the group into mild-to-moderate white matter hyperintensities (WMH) and severe WMH group based on median split on WMH volume.ResultsThe decline in global efficiency was significantly associated with a decline in psychomotor speed in the group with severe WMH (β=0.18, p=0.03) and a trend with change in cognitive index (β=0.14, p=0.068), which diminished after adjusting for imaging markers for SVD. Baseline global efficiency was associated with all-cause mortality (HR per decrease of 1 SD 0.43, 95% CI 0.23 to 0.80, p=0.008, C-statistic 0.76).ConclusionDisruption of the network efficiency, a metric assessing the efficiency of network information transfer, plays an important role in explaining cognitive decline in SVD, which was however not independent of imaging markers of SVD. Furthermore, baseline network efficiency predicts risk of mortality in SVD that may reflect the global health status of the brain in SVD. This emphasises the importance of structural network analysis in the context of SVD research and the use of network measures as surrogate markers in research setting.

Cerebral small vessel disease (SVD) is a cerebrovascular pathology that affects the small vessels of the brain, resulting in heterogeneous brain tissue changes. These can lead to neuropsychiatric symptoms such as apathy, a loss of motivation, and depression, which is characterised by low mood and a loss of pleasure. Apathy and depression are both prevalent symptoms in SVD, but an understanding of the relationship between underlying disease processes and the expression of these neuropsychiatric symptoms remains poor. This thesis uses magnetic resonance imaging techniques to examine the neurobiological basis of apathy and depression in SVD. We show that apathy is related to focal grey matter damage and distributed white matter microstructural change. These microstructural changes underlie large-scale white matter network disruption, which is related to apathy, but not depression. We then show that depression, as a construct, can be dissociated into distinct symptoms which are associated with overlapping and distinct areas of cortical atrophy over time. This suggests that depression as a general syndrome may be characterised by atrophy in core structures, while different symptoms are associated with atrophy in more specialised areas. Consistent with these patterns of overarching tissue damage, we find that apathy, but not depression, predicts conversion to dementia in patients with SVD. Our findings suggest that different types of SVD-related pathology lead to apathy and depression. Diffuse white matter damage may lead to widespread network disruption, resulting in apathy and cognitive impairment. In contrast, depressive symptoms are associated with focal patterns of grey matter atrophy over time. This highlights the importance of differentiating neuropsychiatric symptoms, and paves the way for targeted treatment approaches.

Objective This report investigated the impact of radiation therapy among stage II/III rectal cancer patients who were resected for cure and then developed second primary cancer. Methods The analysis included patients diagnosed with rectal cancer from 1992 to 2010 and who were registered in the National Cancer Institute’s Surveillance, Epidemiology and End Results database. Standardized incidence ratios assessed the location of second primary cancers by the receipt and sequence of radiation therapy. A Cox proportional hazards model examined the predictors for patients who developed second primary cancers. Results The hazard ratio for developing any type of second primary was 12 % higher in patients receiving preoperative radiotherapy, Hazard Ratio and 95 % confidence interval, HR 95 % CI 1.12 (1.0, 1.2), and 33 % lower for patients receiving postoperative radiotherapy, HR 95 % CI 0.75 (0.7, 0.8), relative to patients who did not receive radiation therapy. The location of the second cancer varied by both the receipt and sequence of radiation therapy. Secondary rectal cancers were reduced 170 % after postoperative radiation and 103 % after preoperative radiation, compared to the non-receipt of radiation therapy. The impact of radiation therapy on secondary colon cancers was not as marked. Rectal cancer patients undergoing radiation therapy are at a higher risk of thyroid cancers and leukemia, but males have a lower risk of prostate cancer. Conclusions While preoperative radiation therapy is advantageous for reducing rectal cancer recurrence, this study identifies advantages of postoperative radiation for reducing second primary cancers. This research will help improve recommendations for postdiagnosis surveillance in patients with rectal cancer.

The present study investigates the effect that an array of dimples has on turbulent drag reduction. Although dimples have shown drag reduction in some cases, this drag reduction is usually of the order of a few percent, making quantifying the drag reduction accurately a challenging task. For this purpose, a channel flow is used to allow accurate control of the flow over an array of dimples. A novel method involving the use of measuring relative changes in the mean streamwise pressure gradients within the different sections of the channel was developed to obtain the accuracy required to quantify the effect that the dimples have on drag. Arrays of shallow axisymmetric circular dimples with depth to diameter ratios of 1.5% and 5% are studied in a turbulent channel flow at Reynolds numbers between 3,300 and 37,000. Pressure measurements show that drag reduction of up to 3% is possible at a Reynolds number of 37,000. Single element hot-wire velocimetry is also carried out to measure the streamwise velocity of the flow over the dimple array. Investigation of the flow was further carried out using Detached Eddy Simulation (DES) of the same dimple geometry as the experiments. This allowed the DES and the experiments to compliment as well as validate each other’s findings. The most significant finding of the study is that the mechanism of skin friction drag reduction with dimples is the same as that observed using active methods such as spanwise wall motions or transverse wall jets over flat plates. The three dimensional dimples introduce streamwise vorticity into the flow which results in spanwise flow components near the wall. The DES shows that although the streamwise vorticity introduced is weak, it is concentrated near the dimple surface, and generates significant spanwise flow components near the dimple surface. The result is that the normal energy cascade to the smaller scales is suppressed, which leads to a reduction in turbulent skin friction drag because of the stabilized flow. This suppression is supported by the spectral analysis of the hot-wire velocimetry as well as the turbulent budget and Reynolds stress analysis of the DES. Peaks in the spectral distribution are observed to shift towards the lower frequencies, and reductions in the peaks of the various energy budget terms and Reynolds stress terms are observed with drag reduction. Increasing the dimple depth from 1.5% to 5% of its diameter increases the streamwise vorticity introduced, which leads to a greater reduction in skin friction. However, increasing the dimple depth also results in flow separation which increases pressure or form drag. The DES shows that flow separation is dependent on both the dimple depth and flow Reynolds number. The net effect to the total drag depends on the relative dominance between the drag reducing streamwise vorticity and the drag increasing flow separation. The region of flow separation can shrink with increasing Reynolds number, so that at sufficiently high Reynolds numbers, the flow separation region can shrink and may disappear completely, consequently leading to a larger drag reduction.