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The Developing Human Connectome Project (dHCP) aims to explore developmental patterns of the human brain during the perinatal period. An automated processing pipeline has been developed to extract high-quality cortical surfaces from structural brain magnetic resonance (MR) images for the dHCP neonatal dataset. However, the current implementation of the pipeline requires more than 6.5 h to process a single MRI scan, making it expensive for large-scale neuroimaging studies. In this paper, we propose a fast deep learning (DL) based pipeline for dHCP neonatal cortical surface reconstruction, incorporating DL-based brain extraction, cortical surface reconstruction and spherical projection, as well as GPU-accelerated cortical surface inflation and cortical feature estimation. We introduce a multiscale deformation network to learn diffeomorphic cortical surface reconstruction end-to-end from T2-weighted brain MRI. A fast unsupervised spherical mapping approach is integrated to minimize metric distortions between cortical surfaces and projected spheres. The entire workflow of our DL-based dHCP pipeline completes within only 24 s on a modern GPU, which is nearly 1000 times faster than the original dHCP pipeline. The qualitative assessment demonstrates that for 82.5% of the test samples, the cortical surfaces reconstructed by our DL-based pipeline achieve superior (54.2%) or equal (28.3%) surface quality compared to the original dHCP pipeline., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Background/objectives: The role of α-synuclein (α-syn) pathology in Parkinson's disease (PD) is well established; however, effective therapies remain elusive. Two mechanisms central to PD neurodegeneration are the intracellular aggregation of misfolded α-syn and the uptake of α-syn aggregates into neurons. Cationic arginine-rich peptides (CARPs) are an emerging class of molecule with multiple neuroprotective mechanisms of action, including protein stabilisation. This study characterised both intracellular α-syn aggregation and α-syn uptake in cortical neurons in vitro. Thereafter, this study examined the therapeutic potential of the neuroprotective CARP, R18D (18-mer of D-arginine), to prevent the aforementioned PD pathogenic processes through a cell-free thioflavin-T (ThT) assay and in cortical neurons., Methods: To induce intracellular α-syn aggregation, rat primary cortical neurons were exposed to α-syn seed (0.14 μM) for 2 h to allow uptake of the protein, followed by R18D treatment (0.0625, 0.125, 0.25, 0.5 μM), and a subsequent measurement of α-syn aggregates 48 h later using a homogenous time-resolved fluorescence (HTRF) assay. To assess neuronal uptake, α-syn seeds were covalently labelled with an Alexa-Fluor 488 fluorescent tag, pre-incubated with R18D (0.125, 0.25, 0.5 μM), and then exposed to cortical neurons for 24 h and assessed via confocal microscopy., Results: It was demonstrated that R18D significantly reduced both intracellular α-syn aggregation and α-syn seed uptake in neurons by 37.8% and 77.7%, respectively. Also, R18D reduced the aggregation of α-syn monomers in the cell-free assay., Conclusions: These findings highlight the therapeutic potential of R18D to inhibit key α-syn pathological processes and PD progression.

Although current studies support the use of prophylactic distal perfusion catheters (DPCs) to decrease limb ischemia in patients on venoarterial extracorporeal membrane oxygenation (VA ECMO), methods for monitoring limb ischemia differ between studies. We evaluated the safety of a selective rather than prophylactic DPC strategy at a single center with a well-established protocol for limb ischemia monitoring. Distal perfusion catheters were placed selectively if there was evidence of hypoperfusion at any point until decannulation. All patients were followed daily by vascular surgery with continuous regional saturation monitoring. Of 188 patients supported with VA ECMO, there were no significant differences in baseline characteristics between patients with upfront, delayed, and no DPC. Thirty day mortality was highest in patients with an upfront DPC (56% in the upfront DPC group, 19% in the delayed DPC group, and 22% in the no-DPC group, p < 0.001). The incidence of major bleeding, fasciotomy, and amputation in the entire cohort was 3.7%, 3.7%, and 0%, respectively. With strict adherence to a protocol for limb ischemia monitoring, a selective rather than prophylactic DPC strategy is safe and may obviate the risks of an additional arterial catheter., Competing Interests: Disclosure: P.M.E .: Consulting for Abbott, Ancora, Daxor, Medtronic. K.H.: Consultant for Abiomed. The other authors have no conflicts of interest to report., (Copyright © ASAIO 2024.)

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. Recent studies have revealed a remarkable molecular diversity across the prenatal cortex but little is known about how this diversity translates into the differential rates of cortical expansion observed during gestation. We present a digital resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal brain. Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions, quantified in utero using magnetic resonance imaging. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of neocortical expansion during gestation. We identify genes, upregulated from mid-gestation, that are highly expressed in rapidly expanding neocortex and implicated in genetic disorders with cognitive sequelae. The μBrain atlas provides a tool to comprehensively map early brain development across domains, model systems and resolution scales., (© 2024. The Author(s).)

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (n = 34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bimodal distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex, and complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (n = 228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes., Competing Interests: Declaration of interests E.T.B. has consulted for Novartis, GlaxoSmithKline, SR One, Sosei Heptares, Boehringer Ingelheim, and Monument Therapeutics. E.T.B. and J.S. are co-founders and stockholders of Centile Bio Inc., (Published by Elsevier Inc.)

Surface meshes are a favoured domain for representing structural and functional information on the human cortex, but their complex topology and geometry pose significant challenges for deep learning analysis. While Transformers have excelled as domainagnostic architectures for sequence-to-sequence learning, the quadratic cost of the self-attention operation remains an obstacle for many dense prediction tasks. Inspired by some of the latest advances in hierarchical modelling with vision transformers, we introduce the Multiscale Surface Vision Transformer (MS-SiT) as a backbone architecture for surface deep learning. The self-attention mechanism is applied within local-mesh-windows to allow for high-resolution sampling of the underlying data, while a shifted-window strategy improves the sharing of information between windows. Neighbouring patches are successively merged, allowing the MS-SiT to learn hierarchical representations suitable for any prediction task. Results demonstrate that the MS-SiT outperforms existing surface deep learning methods for neonatal phenotyping prediction tasks using the Developing Human Connectome Project (dHCP) dataset. Furthermore, building the MS-SiT backbone into a U-shaped architecture for surface segmentation demonstrates competitive results on cortical parcellation using the UK Biobank (UKB) and manually-annotated MindBoggle datasets. Code and trained models are publicly available at https://github.com/metrics-lab/surface-vision-transformers.

Objective: This international survey investigated Evidence-Based Medicine (EBM) in spine surgery by measuring its acceptance among spine surgeons. It assessed their understanding of EBM and how they apply it in practice by analyzing responses to various clinical scenarios.., Materials and Methods: Following the CHERRIES guidelines, an e-survey was distributed to multiple social media forums for neurosurgeons and orthopedic surgeons on Facebook, LinkedIn, and Telegram and circulated further through email via the authors' network. Three hundred participants from Africa, Asia, Europe, North America, and Oceania completed the survey., Results: Our study revealed that 67.7% (n = 203) of respondents used EBM in their practice, and 97.3% (n = 292) believed training in research methodology and EBM was necessary for the practice of spine surgery. Despite this endorsement of using EBM in spine surgery, we observed varied responses to how EBM is applied in practice based on example scenarios. The responders who had additional training tended to obey EBM guidelines more than those who had no additional training. Most surgeons responded as always or sometimes prescribing methylprednisolone to patients with acute spinal cord injury. Other significant differences were identified between geographical regions, training, practice settings, and other factors., Conclusions: Most respondents used EBM in practice and believed training in research methodology and EBM is necessary for spine surgery; however, there were significant variations on how to use them per case. Thus, the appropriate application of EBM in clinical settings for spinal surgery must be further studied., (© 2024. The Author(s).)

The early life environment programmes cortical architecture and cognition across the life course. A measure of cortical organisation that integrates information from multimodal MRI and is unbound by arbitrary parcellations has proven elusive, which hampers efforts to uncover the perinatal origins of cortical health. Here, we use the Vogt-Bailey index to provide a fine-grained description of regional homogeneities and sharp variations in cortical microstructure based on feature gradients, and we investigate the impact of being born preterm on cortical development at term-equivalent age. Compared with term-born controls, preterm infants have a homogeneous microstructure in temporal and occipital lobes, and the medial parietal, cingulate, and frontal cortices, compared with term infants. These observations replicated across two independent datasets and were robust to differences that remain in the data after matching samples and alignment of processing and quality control strategies. We conclude that cortical microstructural architecture is altered in preterm infants in a spatially distributed rather than localised fashion., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

We developed a computational pipeline (now provided as a resource) for measuring morphological similarity between cortical surface sulci to construct a sulcal phenotype network (SPN) from each magnetic resonance imaging (MRI) scan in an adult cohort (N=34,725; 45-82 years). Networks estimated from pairwise similarities of 40 sulci on 5 morphological metrics comprised two clusters of sulci, represented also by the bipolar distribution of sulci on a linear-to-complex dimension. Linear sulci were more heritable and typically located in unimodal cortex; complex sulci were less heritable and typically located in heteromodal cortex. Aligning these results with an independent fetal brain MRI cohort (N=228; 21-36 gestational weeks), we found that linear sulci formed earlier, and the earliest and latest-forming sulci had the least between-adult variation. Using high-resolution maps of cortical gene expression, we found that linear sulcation is mechanistically underpinned by trans-sulcal gene expression gradients enriched for developmental processes., Competing Interests: Declaration of interests E.T.B. has consulted for GlaxoSmithKline, SR One, Sosei Heptares, Boehringer Ingelheim and Monument Therapeutics. E.T.B. and J.S. are co-founders and stockholders of Centile Bio Inc. All other authors declare no conflicts of interest.

In this systematic review, we address the status of intracortical brain-computer interfaces (iBCIs) applied to the motor cortex to improve function in patients with impaired motor ability. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Guidelines for Systematic Reviews. Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) and the Effective Public Health Practice Project (EPHPP) were used to assess bias and quality. Advances in iBCIs in the last two decades demonstrated the use of iBCI to activate limbs for functional tasks, achieve neural typing for communication, and other applications. However, the inconsistency of performance metrics employed by these studies suggests the need for standardization. Each study was a pilot clinical trial consisting of 1-4, majority male (64.28 %) participants, with most trials featuring participants treated for more than 12 months (55.55 %). The systems treated patients with various conditions: amyotrophic lateral sclerosis, stroke, spinocerebellar degeneration without cerebellar involvement, and spinal cord injury. All participants presented with tetraplegia at implantation and were implanted with microelectrode arrays via pneumatic insertion, with nearly all electrode locations solely at the precentral gyrus of the motor cortex (88.88 %). The development of iBCI devices using neural signals from the motor cortex to improve motor-impaired patients has enhanced the ability of these systems to return ability to their users. However, many milestones remain before these devices can prove their feasibility for recovery. This review summarizes the achievements and shortfalls of these systems and their respective trials., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

Background: Pregnancy following bariatric surgery requires tailored care. The current Australian care provision and its alignment with consensus guidelines is unclear., Methods: Antenatal care clinicians were invited to complete a web-based survey assessing multidisciplinary referral, gestational diabetes mellitus (GDM) and micronutrient management practices., Results: Respondents (n = 100) cared for pregnant women with a history of bariatric surgery at least monthly (63%) with most (54%) not using a specific guideline to direct care. GDM screening methods included one-week of home blood glucose monitoring (43%) or the oral glucose tolerance test (42%). Pregnancy multivitamin supplementation changes (59%) with bariatric surgery type were common. Half (54%) screened for micronutrient deficiencies every trimester and conducted additional growth ultrasounds (50%)., Conclusion: The care clinicians report providing may not align with current international consensus guidelines. Further studies with increased obstetric clinician response may aid increased understanding of current practices. The development of workplace management guidelines for pregnancy in women with a history of bariatric surgery may assist with providing consistent evidence-based care., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2022.)

Features of brain asymmetry have been implicated in a broad range of cognitive processes; however, their origins are still poorly understood. Here we investigated cortical asymmetries in 442 healthy term-born neonates using structural and functional magnetic resonance images from the Developing Human Connectome Project. Our results demonstrate that the neonatal cortex is markedly asymmetric in both structure and function. Cortical asymmetries observed in the term cohort were contextualized in two ways: by comparing them against cortical asymmetries observed in 103 preterm neonates scanned at term-equivalent age, and by comparing structural asymmetries against those observed in 1,110 healthy young adults from the Human Connectome Project. While associations with preterm birth and biological sex were minimal, significant differences exist between birth and adulthood., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Purpose: To evaluate the effect of iliac tortuosity on procedural metrics and outcomes of patients with complex aortic aneurysms (cAAs) undergoing repair with fenestrated/branched endografts (f/b-EVAR [endovascular aortic aneurysm repair])., Material and Methods: The study is a single-center, retrospective review of a prospectively maintained database of patients undergoing aneurysm repair using f/b-EVAR between the years 2013 and 2020 at our institution. Included patients had at least 1 preoperative computed tomography angiography (CTA) available for analysis. Iliac artery tortuosity index (TI) was calculated using centerline of flow imaging from a 3-dimensional work station based on the formula: (centerline iliac artery length / straight-line iliac artery length). The associations between iliac artery tortuosity and procedural metrics, including total operative time, fluoroscopy time, radiation dose, contrast volume, and estimated blood loss (EBL), were evaluated., Results: During this period, 219 patients with cAAs underwent f/b-EVAR at our institution. Ninety-one patients (74% men; mean age = 75.2±7.7 years) met criteria for inclusion into the study. In this group, there were 72 (79%) juxtarenal or paravisceral aneurysms and 18 (20%) thoracoabdominal aortic aneurysms and 5 patients (5.4%) with failed previous EVAR. The average aneurysm diameter was 60.1±0.74 mm. Overall, 270 vessels were targeted, and 267 (99%) were successfully incorporated, including 25 celiac arteries, 67 superior mesenteric arteries, and 175 renal arteries. The mean total operative time was 236±83 minutes, fluoroscopy time was 87±39 minutes, contrast volume was 81±47 mL, radiation dose 3246±2207 mGy, and EBL was 290±409 mL. The average left and right TIs for all patients were 1.5±0.3 and 1.4±0.3, respectively. On multivariable analysis, the interval estimates suggest positive association between TI and procedural metrics to a certain degree., Conclusions: In the current series, we found no definitive association between iliac artery TI and procedural metrics, including operative time, contrast used, EBL, fluoroscopy time, and dose in patients undergoing cAA repair using f/b-EVAR. However, there was a trend toward association between TI and all these metrics on multivariable analysis. This potential association needs to be evaluated in a larger series., Clinical Impact: Iliac artery tortuosity should not exclude patients with complex aortic aneurysms from being offered fenestrated or branched stent graft repair. However, special considerations should be taken to mitigate the impact of access tortuosity on alignment of fenestrations with target vessels, including use of extra stiff wires, through and through access and delivering the fenestrated/branched device into another (larger) sheath such as a Gore DrySeal in patients with arteries large enough to accommodate such sheaths.

Fetal MRI is widely used for quantitative brain volumetry studies. However, currently, there is a lack of universally accepted protocols for fetal brain parcellation and segmentation. Published clinical studies tend to use different segmentation approaches that also reportedly require significant amounts of time-consuming manual refinement. In this work, we propose to address this challenge by developing a new robust deep learning-based fetal brain segmentation pipeline for 3D T2w motion corrected brain images. At first, we defined a new refined brain tissue parcellation protocol with 19 regions-of-interest using the new fetal brain MRI atlas from the Developing Human Connectome Project. This protocol design was based on evidence from histological brain atlases, clear visibility of the structures in individual subject 3D T2w images and the clinical relevance to quantitative studies. It was then used as a basis for developing an automated deep learning brain tissue parcellation pipeline trained on 360 fetal MRI datasets with different acquisition parameters using semi-supervised approach with manually refined labels propagated from the atlas. The pipeline demonstrated robust performance for different acquisition protocols and GA ranges. Analysis of tissue volumetry for 390 normal participants (21-38 weeks gestational age range), scanned with three different acquisition protocols, did not reveal significant differences for major structures in the growth charts. Only minor errors were present in < 15% of cases thus significantly reducing the need for manual refinement. In addition, quantitative comparison between 65 fetuses with ventriculomegaly and 60 normal control cases were in agreement with the findings reported in our earlier work based on manual segmentations. These preliminary results support the feasibility of the proposed atlas-based deep learning approach for large-scale volumetric analysis. The created fetal brain volumetry centiles and a docker with the proposed pipeline are publicly available online at https://hub.docker.com/r/fetalsvrtk/segmentation (tag brain&#95;bounti&#95;tissue).

An important goal of medical imaging is to be able to precisely detect patterns of disease specific to individual scans; however, this is challenged in brain imaging by the degree of heterogeneity of shape and appearance. Traditional methods, based on image registration, historically fail to detect variable features of disease, as they utilise population-based analyses, suited primarily to studying group-average effects. In this paper we therefore take advantage of recent developments in generative deep learning to develop a method for simultaneous classification, or regression, and feature attribution (FA). Specifically, we explore the use of a VAE-GAN (variational autoencoder - general adversarial network) for translation called ICAM, to explicitly disentangle class relevant features, from background confounds, for improved interpretability and regression of neurological phenotypes. We validate our method on the tasks of Mini-Mental State Examination (MMSE) cognitive test score prediction for the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, as well as brain age prediction, for both neurodevelopment and neurodegeneration, using the developing Human Connectome Project (dHCP) and UK Biobank datasets. We show that the generated FA maps can be used to explain outlier predictions and demonstrate that the inclusion of a regression module improves the disentanglement of the latent space. Our code is freely available on GitHub https://github.com/CherBass/ICAM.

Telomeres form protective caps at the ends of chromosomes, and their attrition is a marker of biological aging. Short telomeres are associated with an increased risk of neurological and psychiatric disorders including dementia. The mechanism underlying this risk is unclear, and may involve brain structure and function. However, the relationship between telomere length and neuroimaging markers is poorly characterized. Here we show that leucocyte telomere length (LTL) is associated with multi-modal MRI phenotypes in 31,661 UK Biobank participants. Longer LTL is associated with: i) larger global and subcortical grey matter volumes including the hippocampus, ii) lower T1-weighted grey-white tissue contrast in sensory cortices, iii) white-matter microstructure measures in corpus callosum and association fibres, iv) lower volume of white matter hyperintensities, and v) lower basal ganglia iron. Longer LTL was protective against certain related clinical manifestations, namely all-cause dementia (HR 0.93, 95% CI: 0.91-0.96), but not stroke or Parkinson's disease. LTL is associated with multiple MRI endophenotypes of neurodegenerative disease, suggesting a pathway by which longer LTL may confer protective against dementia., Competing Interests: TN “Paid statistical consultancy, Perspectum”. The other authors declare no competing financial interests. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Topiwala et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

We present CortexODE, a deep learning framework for cortical surface reconstruction. CortexODE leverages neural ordinary differential equations (ODEs) to deform an input surface into a target shape by learning a diffeomorphic flow. The trajectories of the points on the surface are modeled as ODEs, where the derivatives of their coordinates are parameterized via a learnable Lipschitz-continuous deformation network. This provides theoretical guarantees for the prevention of self-intersections. CortexODE can be integrated to an automatic learning-based pipeline, which reconstructs cortical surfaces efficiently in less than 5 seconds. The pipeline utilizes a 3D U-Net to predict a white matter segmentation from brain Magnetic Resonance Imaging (MRI) scans, and further generates a signed distance function that represents an initial surface. Fast topology correction is introduced to guarantee homeomorphism to a sphere. Following the isosurface extraction step, two CortexODE models are trained to deform the initial surface to white matter and pial surfaces respectively. The proposed pipeline is evaluated on large-scale neuroimage datasets in various age groups including neonates (25-45 weeks), young adults (22-36 years) and elderly subjects (55-90 years). Our experiments demonstrate that the CortexODE-based pipeline can achieve less than 0.2mm average geometric error while being orders of magnitude faster compared to conventional processing pipelines.

Stenosis of left ventricular assist devices has traditionally required open operative management with device revision or replacement; however, endovascular therapy is emerging as an alternative to open surgery. Limited by the rarity of this approach, consensus is lacking regarding the optimal technique. In this publication, we present a case report of outflow graft stenosis managed with endovascular treatment and discuss technical considerations including preoperative planning, stent selection, and procedural adjuncts., (© 2022 Wiley Periodicals LLC.)

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Edwards, Rueckert, Smith, Abo Seada, Alansary, Almalbis, Allsop, Andersson, Arichi, Arulkumaran, Bastiani, Batalle, Baxter, Bozek, Braithwaite, Brandon, Carney, Chew, Christiaens, Chung, Colford, Cordero-Grande, Counsell, Cullen, Cupitt, Curtis, Davidson, Deprez, Dillon, Dimitrakopoulou, Dimitrova, Duff, Falconer, Farahibozorg, Fitzgibbon, Gao, Gaspar, Harper, Harrison, Hughes, Hutter, Jenkinson, Jbabdi, Jones, Karolis, Kyriakopoulou, Lenz, Makropoulos, Malik, Mason, Mortari, Nosarti, Nunes, O’Keeffe, O’Muircheartaigh, Patel, Passerat-Palmbach, Pietsch, Price, Robinson, Rutherford, Schuh, Sotiropoulos, Steinweg, Teixeira, Tenev, Tournier, Tusor, Uus, Vecchiato, Williams, Wright, Wurie and Hajnal.)

Developmental delays in infanthood often persist, turning into life-long difficulties, and coming at great cost for the individual and community. By examining the developing brain and its relation to developmental outcomes we can start to elucidate how the emergence of brain circuits is manifested in variability of infant motor, cognitive and behavioural capacities. In this study, we examined if cortical structural covariance at birth, indexing coordinated development, is related to later infant behaviour. We included 193 healthy term-born infants from the Developing Human Connectome Project (dHCP). An individual cortical connectivity matrix derived from morphological and microstructural features was computed for each subject (morphometric similarity networks, MSNs) and was used as input for the prediction of behavioural scores at 18 months using Connectome-Based Predictive Modeling (CPM). Neonatal MSNs successfully predicted social-emotional performance. Predictive edges were distributed between and within known functional cortical divisions with a specific important role for primary and posterior cortical regions. These results reveal that multi-modal neonatal cortical profiles showing coordinated maturation are related to developmental outcomes and that network organization at birth provides an early infrastructure for future functional skills., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Peripheral arterial disease (PAD) represents a major health issue that significantly impacts patient's survival and quality of life. In addition to limb-related events, patients with PAD have an increased risk of myocardial infarction, stroke, and death. However, compared with coronary and cerebrovascular disease, studies addressing optimal risk reduction modalities including antithrombotic therapies in patients with PAD have been underrepresented in the literature. This publication serves as a narrative review of existing evidence on the effectiveness of antithrombotic therapy in patients with PAD. In patients with chronic stable PAD or post-revascularization, antithrombotic therapies including single or dual antiplatelet agents, anticoagulation, or a combination of these treatments have been shown to reduce cardiovascular and limb events. This narrative review provides a summary of the available literature on the management of patients with PAD, categorized into treatment strategies for chronic, post-endovascular treatment, and post-open surgical revascularization and to discuss the antithrombotic protocol utilized at our institution while providing a rational for our treatment algorithm.

Introduction: The dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors., Methods: We sought to first map typical cortical micro- and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n = 259). Then we offer a comprehensive characterization of the cortical consequences of preterm birth in 76 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months., Results: In the term-born neonatal brain, we observed heterogeneous and regionally specific associations between age at scan and measures of cortical morphology and microstructure, including rapid surface expansion, greater cortical thickness, lower cortical anisotropy and higher neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months., Conclusion: We showed that preterm birth alters cortical micro- and macrostructural maturation near the time of full-term birth. Deviations from normative development were highly variable between individual preterm infants., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Few challenges of the COVID-19 pandemic strike at the very core of our humanity as the inability of family to sit at the bedside of their loved ones when battling for their lives in the ICU. Virtual visiting is one tool to help deal with this challenge. When introducing virtual visiting into our ICU, we identified 5 criteria for a sustainable system that aligned with patient-family-centered care: virtual visiting needed to (1) simulate open and flexible visiting; (2) be able to accommodate differences in family size, dynamics, and cultural practices; (3) utilize a video conferencing platform that is private and secure; (4) be easy to use and not require special teams to facilitate meetings; and (5) not increase the workload of ICU staff. There is a growing body of literature demonstrating a global movement toward virtual visiting in ICU, however there are no publications that describe a system which meet all 5 of our criteria. Importantly, there are no papers describing systems of virtual visiting which mimic open and flexible family presence at the bedside. We were unable to find any off-the-shelf video conferencing platforms that met all our criteria. To come up with a solution, a multidisciplinary team of ICU staff partnered with healthcare technology adoption consultants and two technology companies to develop an innovative system called HowRU. HowRU uses the video conferencing platform Webex with the integration of some newly designed software that automates many of the laborious and complex processes. HowRU is a cloud based, supported, and simplified system that closely simulates open and flexible visiting while ensuring patient and family privacy, dignity, and security. We have demonstrated the transferability of HowRU by implanting it into a second ICU. HowRU is now commercially available internationally. We hope HowRU will improve patient-family-centered care in ICU.

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain., (© The Author(s) 2021. Published by Oxford University Press.)

Fully automatic deep learning has become the state-of-the-art technique for many tasks including image acquisition, analysis and interpretation, and for the extraction of clinically useful information for computer-aided detection, diagnosis, treatment planning, intervention and therapy. However, the unique challenges posed by medical image analysis suggest that retaining a human end-user in any deep learning enabled system will be beneficial. In this review we investigate the role that humans might play in the development and deployment of deep learning enabled diagnostic applications and focus on techniques that will retain a significant input from a human end user. Human-in-the-Loop computing is an area that we see as increasingly important in future research due to the safety-critical nature of working in the medical domain. We evaluate four key areas that we consider vital for deep learning in the clinical practice: (1) Active Learning to choose the best data to annotate for optimal model performance; (2) Interaction with model outputs - using iterative feedback to steer models to optima for a given prediction and offering meaningful ways to interpret and respond to predictions; (3) Practical considerations - developing full scale applications and the key considerations that need to be made before deployment; (4) Future Prospective and Unanswered Questions - knowledge gaps and related research fields that will benefit human-in-the-loop computing as they evolve. We offer our opinions on the most promising directions of research and how various aspects of each area might be unified towards common goals., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

An aneurysm of the inferior mesenteric artery is a rarely described clinical presentation. We have presented the case of a ruptured aneurysm originating from a branch of the inferior mesenteric artery that might represent an aneurysm of the left colic artery or the arc of Riolan. Aneurysms of this anatomic location can develop secondary to mesenteric occlusive disease, alterations in mesenteric blood flow from previous operations, or connective tissue disease. In the present case, a patient with a ruptured inferior mesenteric artery branch aneurysm had presented with intra-abdominal hemorrhage, which was successfully treated with endovascular embolization., (© 2021 The Authors.)

The developing Human Connectome Project (dHCP) aims to create a detailed 4-dimensional connectome of early life spanning 20-45 weeks post-menstrual age. This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines. In this paper we present an automated and robust pipeline to minimally pre-process highly confounded neonatal resting-state fMRI data, robustly, with low failure rates and high quality-assurance. The pipeline has been designed to specifically address the challenges that neonatal data presents including low and variable contrast and high levels of head motion. We provide a detailed description and evaluation of the pipeline which includes integrated slice-to-volume motion correction and dynamic susceptibility distortion correction, a robust multimodal registration approach, bespoke ICA-based denoising, and an automated QC framework. We assess these components on a large cohort of dHCP subjects and demonstrate that processing refinements integrated into the pipeline provide substantial reduction in movement related distortions, resulting in significant improvements in SNR, and detection of high quality RSNs from neonates., Competing Interests: Declaration of Competing Interest MJ, SS, and JA receive royalties from the commercial licensing of FSL (it is free for non-commercial use). The authors report no other conflicts of interest., (Copyright © 2020. Published by Elsevier Inc.)

Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal magnetic resonance imaging (MRI) in n = 292 healthy newborn infants (mean age at birth = 39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n = 156 samples from 16 brains, aged 12 to 37 postconceptional weeks [pcw]). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n = 64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis (PCA) of 6 measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated with estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons, and engaged in stem cell differentiation, neuron migration, and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder., Competing Interests: The authors have declared that no competing interests exist.

Mapping connections in the neonatal brain can provide insight into the crucial early stages of neurodevelopment that shape brain organisation and lay the foundations for cognition and behaviour. Diffusion MRI and tractography provide unique opportunities for such explorations, through estimation of white matter bundles and brain connectivity. Atlas-based tractography protocols, i.e. a priori defined sets of masks and logical operations in a template space, have been commonly used in the adult brain to drive such explorations. However, rapid growth and maturation of the brain during early development make it challenging to ensure correspondence and validity of such atlas-based tractography approaches in the developing brain. An alternative can be provided by data-driven methods, which do not depend on predefined regions of interest. Here, we develop a novel data-driven framework to extract white matter bundles and their associated grey matter networks from neonatal tractography data, based on non-negative matrix factorisation that is inherently suited to the non-negative nature of structural connectivity data. We also develop a non-negative dual regression framework to map group-level components to individual subjects. Using in-silico simulations, we evaluate the accuracy of our approach in extracting connectivity components and compare with an alternative data-driven method, independent component analysis. We apply non-negative matrix factorisation to whole-brain connectivity obtained from publicly available datasets from the Developing Human Connectome Project, yielding grey matter components and their corresponding white matter bundles. We assess the validity and interpretability of these components against traditional tractography results and grey matter networks obtained from resting-state fMRI in the same subjects. We subsequently use them to generate a parcellation of the neonatal cortex using data from 323 new-born babies and we assess the robustness and reproducibility of this connectivity-driven parcellation., (Copyright © 2020. Published by Elsevier Inc.)

Interruptions to neurodevelopment during the perinatal period may have long-lasting consequences. However, to be able to investigate deviations in the foundation of proper connectivity and functional circuits, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a cohort of 241 term-born infants, we used magnetic resonance imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37-44 weeks postmenstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (morphometric similarity networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory-motor, limbic, and association regions, and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior regions became more morphometrically similar with increasing age, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with age: Within-network similarity increased over age suggesting emerging network distinction. These changes in cortical network architecture over an 8-week period are consistent with, and likely underpin, the highly dynamic processes occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development., (© The Author(s) 2020. Published by Oxford University Press.)

Evolutionary adaptations of temporo-parietal cortex are considered to be a critical specialization of the human brain. Cortical adaptations, however, can affect different aspects of brain architecture, including local expansion of the cortical sheet or changes in connectivity between cortical areas. We distinguish different types of changes in brain architecture using a computational neuroanatomy approach. We investigate the extent to which between-species alignment, based on cortical myelin, can predict changes in connectivity patterns across macaque, chimpanzee, and human. We show that expansion and relocation of brain areas can predict terminations of several white matter tracts in temporo-parietal cortex, including the middle and superior longitudinal fasciculus, but not the arcuate fasciculus. This demonstrates that the arcuate fasciculus underwent additional evolutionary modifications affecting the temporal lobe connectivity pattern. This approach can flexibly be extended to include other features of cortical organization and other species, allowing direct tests of comparative hypotheses of brain organization., Competing Interests: NE, ER, KB, SJ, MJ, LL, KW, RM No competing interests declared, KK Reviewing editor, eLife, (© 2020, Eichert et al.)

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Direct-to-implant breast reconstruction offers the intuitive advantages of shortening the reconstructive process and reducing costs. In the authors' practice, direct-to-implant breast reconstruction has evolved from dual-plane to prepectoral implant placement. The authors sought to understand postoperative complications and aesthetic outcomes and identify differences in the dual-plane and prepectoral direct-to-implant subcohorts., Methods: A retrospective review of a prospectively maintained database was conducted from November of 2014 to March of 2018. Postoperative complication data, reoperation, and aesthetic outcomes were reviewed. Aesthetic outcomes were evaluated by a blinded panel of practitioners using standardized photographs., Results: One hundred thirty-four direct-to-implant reconstructions were performed in 81 women: 42.5 percent were dual-plane (n = 57) and 57.5 percent were prepectoral (n = 77). Statistical analysis was limited to patients with at least 1 year of follow-up. Total complications were low overall (8 percent), although the incidence of prepectoral complications [n = 1 (2 percent)] was lower than the incidence of dual-plane complications [n = 7 (12 percent)], with the difference approaching statistical significance (p = 0.07). Panel evaluation for aesthetic outcomes favored prepectoral reconstruction. Pectoralis animation deformity was completely eliminated in the prepectoral cohort., Conclusions: The authors present the largest comparative direct-to-implant series using acellular dermal matrix to date. Transition to prepectoral direct-to-implant reconstruction has not resulted in increased complications, degradation of aesthetic results, or an increase in revision procedures. Prepectoral reconstruction is a viable reconstructive option with elimination of animation deformity and potential for enhanced aesthetic results., Clinical Question/level of Evidence: Therapeutic, III.

Background: Prepectoral direct-to-implant breast reconstruction has historically been fraught with complications, including flap necrosis, implant extrusion, and capsular contracture, along with high rates of operative revisions. This may result from a number of factors, including the lack of an algorithmic approach, failure to predict postoperative migration of the implant, use of improper implants, and unsuitable patient selection. Over the past 5 years, the authors have gained significant experience in prepectoral breast reconstruction as they have transitioned their direct-to-implant technique., Methods: Using video, technical aspects for achieving superior results are demonstrated, including suture technique, application of acellular dermal matrix, creation of the implant pocket, implant selection and placement, and postoperative dressings. Video is used to highlight technical aspects to yield consistent, predictable results using the anterior tenting technique., Results: A systematic review of prepectoral direct-to-implant breast reconstruction was conducted to amalgamate the experience of the authors and others with regard to technique, material, and outcomes., Conclusions: Prepectoral direct-to-implant breast reconstruction represents a significant paradigm shift in postmastectomy breast reconstruction and warrants reconsideration. Prepectoral direct-to-implant breast reconstruction provides the potential benefits of a single-stage operation, elimination of dynamic deformity, enhanced aesthetic outcomes, and increased patient satisfaction. Although early evidence suggests an increased incidence of complications, our experience and that of others demonstrate favorable outcomes with version 2.0 of prepectoral direct-to-implant breast reconstruction. As the body of literature encompassing a modern approach to prepectoral direct-to-implant breast reconstruction grows, greater appreciation for operative technique, candidate selection, and implant choice may accelerate its adoption and mitigate past concerns.

The Human Connectome Projects in Development (HCP-D) and Aging (HCP-A) are two large-scale brain imaging studies that will extend the recently completed HCP Young-Adult (HCP-YA) project to nearly the full lifespan, collecting structural, resting-state fMRI, task-fMRI, diffusion, and perfusion MRI in participants from 5 to 100+ years of age. HCP-D is enrolling 1300+ healthy children, adolescents, and young adults (ages 5-21), and HCP-A is enrolling 1200+ healthy adults (ages 36-100+), with each study collecting longitudinal data in a subset of individuals at particular age ranges. The imaging protocols of the HCP-D and HCP-A studies are very similar, differing primarily in the selection of different task-fMRI paradigms. We strove to harmonize the imaging protocol to the greatest extent feasible with the completed HCP-YA (1200+ participants, aged 22-35), but some imaging-related changes were motivated or necessitated by hardware changes, the need to reduce the total amount of scanning per participant, and/or the additional challenges of working with young and elderly populations. Here, we provide an overview of the common HCP-D/A imaging protocol including data and rationales for protocol decisions and changes relative to HCP-YA. The result will be a large, rich, multi-modal, and freely available set of consistently acquired data for use by the scientific community to investigate and define normative developmental and aging related changes in the healthy human brain., (Copyright © 2018 Elsevier Inc. All rights reserved.)

We propose a method for constructing a spatio-temporal cortical surface atlas of neonatal brains aged between 36 and 44 weeks of post-menstrual age (PMA) at the time of scan. The data were acquired as part of the Developing Human Connectome Project (dHCP), and the constructed surface atlases are publicly available. The method is based on a spherical registration approach: Multimodal Surface Matching (MSM), using cortical folding for driving the alignment. Templates have been generated for the anatomical cortical surface and for the cortical feature maps: sulcal depth, curvature, thickness, T1w/T2w myelin maps and cortical regions. To achieve this, cortical surfaces from 270 infants were first projected onto the sphere. Templates were then generated in two stages: first, a reference space was initialised via affine alignment to a group average adult template. Following this, templates were iteratively refined through repeated alignment of individuals to the template space until the variability of the average feature sets converged. Finally, bias towards the adult reference was removed by applying the inverse of the average affine transformations on the template and de-drifting the template. We used temporal adaptive kernel regression to produce age-dependant atlases for 9 weeks (36-44 weeks PMA). The generated templates capture expected patterns of cortical development including an increase in gyrification as well as an increase in thickness and T1w/T2w myelination with increasing age., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The macro-connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity-driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity-driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting-state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject-level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously., (Copyright © 2017 Elsevier Inc. All rights reserved.)

During the third trimester of human brain development, the cerebral cortex undergoes dramatic surface expansion and folding. Physical models suggest that relatively rapid growth of the cortical gray matter helps drive this folding, and structural data suggest that growth may vary in both space (by region on the cortical surface) and time. In this study, we propose a unique method to estimate local growth from sequential cortical reconstructions. Using anatomically constrained multimodal surface matching (aMSM), we obtain accurate, physically guided point correspondence between younger and older cortical reconstructions of the same individual. From each pair of surfaces, we calculate continuous, smooth maps of cortical expansion with unprecedented precision. By considering 30 preterm infants scanned two to four times during the period of rapid cortical expansion (28-38 wk postmenstrual age), we observe significant regional differences in growth across the cortical surface that are consistent with the emergence of new folds. Furthermore, these growth patterns shift over the course of development, with noninjured subjects following a highly consistent trajectory. This information provides a detailed picture of dynamic changes in cortical growth, connecting what is known about patterns of development at the microscopic (cellular) and macroscopic (folding) scales. Since our method provides specific growth maps for individual brains, we are also able to detect alterations due to injury. This fully automated surface analysis, based on tools freely available to the brain-mapping community, may also serve as a useful approach for future studies of abnormal growth due to genetic disorders, injury, or other environmental variables., Competing Interests: The authors declare no conflict of interest.

Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behaviour. For example, studies have used 'functional connectivity fingerprints' to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits., Competing Interests: JB, MW, MG, ER, CB, SH, SS No competing interests declared, DV Reviewing editor, eLife, (© 2018, Bijsterbosch et al.)

In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical sensitivity and spatial localisation of group studies, and cortical surface-based alignment has generally been accepted to be superior to volume-based approaches at aligning cortical areas. However, human subjects have considerable variation in cortical folding, and in the location of functional areas relative to these folds. This makes alignment of cortical areas a challenging problem. The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. Using MSM, we have previously shown that driving cross-subject surface alignment, using areal features, such as resting state-networks and myelin maps, improves group task fMRI statistics and map sharpness. However, the initial implementation of MSM's regularisation function did not penalize all forms of surface distortion evenly. In some cases, this allowed peak distortions to exceed neurobiologically plausible limits, unless regularisation strength was increased to a level which prevented the algorithm from fully maximizing surface alignment. Here we propose and implement a new regularisation penalty, derived from physically relevant equations of strain (deformation) energy, and demonstrate that its use leads to improved and more robust alignment of multimodal imaging data. In addition, since spherical warps incorporate projection distortions that are unavoidable when mapping from a convoluted cortical surface to the sphere, we also propose constraints that enforce smooth deformation of cortical anatomies. We test the impact of this approach for longitudinal modelling of cortical development for neonates (born between 31 and 43 weeks of post-menstrual age) and demonstrate that the proposed method increases the biological interpretability of the distortion fields and improves the statistical significance of population-based analysis relative to other spherical methods., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Rectal foreign bodies are commonly encountered in the emergency department (ED). Three techniques are well described in literature, including using a Foley catheter, "scooping" the object out, or grasping the object directly with ring forceps. We present a novel extraction method for an inflatable foreign body., Case Report: A 27-year-old man presented to the ED 13 h after inserting a rubber inflatable child's ball into his rectum. After well-described extraction techniques failed to remove the ball, an 18-gauge needle at the end of a syringe was inserted into the rectum to puncture the ball and partially deflate it. The ball was then able to be removed easily. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Although recent published literature has pushed for early consultation of surgical specialties in lieu of emergency physician bedside extraction, this case report highlights the ability of emergency physicians to modify known extraction techniques to safely remove rectal foreign bodies in well-appearing patients at the bedside using appropriate analgesia, positioning, and readily available equipment., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Competing Interests: Disclosure The authors report no conflicts of interest in this work.

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI).

Macrophages are essential to maintaining lung homoeostasis and recent work has demonstrated that influenza-infected lung macrophages downregulate their expression of the scavenger receptor CD36. This receptor has also been shown to be involved in phagocytosis of Streptococcus pneumoniae, a primary agent associated with pneumonia secondary to viral infection. The aim of this study was to investigate the role of CD36 in the effects of viral infection on macrophage phagocytic function. Human monocyte-derived macrophages (MDM) were exposed to H3N2 X31 influenza virus, M37 respiratory syncytial virus (RSV) or UV-irradiated virus. No infection of MDM was seen upon exposure to UV-irradiated virus but incubation with live X31 or M37 resulted in significant levels of viral detection by flow cytometry or RT-PCR respectively. Infection resulted in significantly diminished uptake of S. pneumoniae by MDM and significantly decreased expression of CD36 at both the cell surface and mRNA level. Concurrently, there was a significant increase in IFNβ gene expression in response to infection and we observed a significant decrease in bacterial phagocytosis (p = 0.031) and CD36 gene expression (p = 0.031) by MDM cultured for 24 h in 50IU/ml IFNβ. Knockdown of CD36 by siRNA resulted in decreased phagocytosis, but this was mimicked by transfection reagent alone. When MDM were incubated with CD36 blocking antibodies no effect on phagocytic ability was observed. These data indicate that autologous IFNβ production by virally-infected cells can inhibit bacterial phagocytosis, but that decreased CD36 expression by these cells does not play a major role in this functional deficiency., Competing Interests: RD is a co-founder and holds shares in Synairgen Plc. These interests do not alter our adherence to PLOS ONE policies on sharing data and materials. The remaining authors declare no conflict of interest.