Chemokine Receptor Redundancy and Specificity Are Context Dependent.

Currently, we lack an understanding of the individual and combinatorial roles for chemokine receptors in the inflammatory process. We report studies on mice with a compound deletion of Ccr1, Ccr2, Ccr3, and Ccr5, which together control monocytic and eosinophilic recruitment to resting and inflamed sites. Analysis of resting tissues from these mice, and mice deficient in each individual receptor, provides clear evidence for redundant use of these receptors in establishing tissue-resident monocytic cell populations. In contrast, analysis of cellular recruitment to inflamed sites provides evidence of specificity of receptor use for distinct leukocyte subtypes and no indication of comprehensive redundancy. We find no evidence of involvement of any of these receptors in the recruitment of neutrophils or lymphocytes to resting or acutely inflamed tissues. Our data shed important light on combinatorial inflammatory chemokine receptor function and highlight Ccr2 as the primary driver of myelomonocytic cell recruitment in acutely inflamed contexts.

International evaluation of an AI system for breast cancer screening.

Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful1. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives2. Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening.

Perioperative Brain Injury in Relation to Early Neurodevelopment Among Children with Severe Congenital Heart Disease: Results from a European Collaboration.

OBJECTIVE: To examine the relationship between perioperative brain injury and neurodevelopment during early childhood in patients with severe congenital heart disease (CHD). STUDY DESIGN: One hundred and seventy children with CHD and born at term who required cardiopulmonary bypass surgery in the first 6 weeks after birth were recruited from 3 European centers and underwent preoperative and postoperative brain MRIs. Uniform description of imaging findings was performed and an overall brain injury score was created, based on the sum of the worst preoperative or postoperative brain injury subscores. Motor and cognitive outcomes were assessed with the Bayley Scales of Infant and Toddler Development Third Edition at 12 to 30 months of age. The relationship between brain injury score and clinical outcome was assessed using multiple linear regression analysis, adjusting for CHD severity, length of hospital stay (LOS), socioeconomic status (SES), and age at follow-up. RESULTS: Neither the overall brain injury score nor any of the brain injury subscores correlated with motor or cognitive outcome. The number of preoperative white matter lesions was significantly associated with gross motor outcome after correction for multiple testing (P = .013, ß = -0.50). SES was independently associated with cognitive outcome (P < .001, ß = 0.26), and LOS with motor outcome (P < .001, ß = -0.35). CONCLUSION: Preoperative white matter lesions appear to be the most predictive MRI marker for adverse early childhood gross motor outcome in this large European cohort of infants with severe CHD. LOS as a marker of disease severity, and SES influence outcome and future intervention trials need to address these risk factors.

Development of Good Manufacturing Practice-Compatible Isolation and Culture Methods for Human Olfactory Mucosa-Derived Mesenchymal Stromal Cells.

Demyelination in the central nervous system (CNS) resulting from injury or disease can cause loss of nerve function and paralysis. Cell therapies intended to promote remyelination of axons are a promising avenue of treatment, with mesenchymal stromal cells (MSCs) a prominent candidate. We have previously demonstrated that MSCs derived from human olfactory mucosa (hOM-MSCs) promote myelination to a greater extent than bone marrow-derived MSCs (hBM-MSCs). However, hOM-MSCs were developed using methods and materials that were not good manufacturing practice (GMP)-compliant. Before considering these cells for clinical use, it is necessary to develop a method for their isolation and expansion that is readily adaptable to a GMP-compliant environment. We demonstrate here that hOM-MSCs can be derived without enzymatic tissue digestion or cell sorting and without culture antibiotics. They grow readily in GMP-compliant media and express typical MSC surface markers. They robustly produce CXCL12 (a key secretory factor in promoting myelination) and are pro-myelinating in in vitro rodent CNS cultures. GMP-compliant hOM-MSCs are comparable in this respect to those grown in non-GMP conditions. However, when assessed in an in vivo model of demyelinating disease (experimental autoimmune encephalitis, EAE), they do not significantly improve disease scores compared with controls, indicating further pre-clinical evaluation is necessary before their advancement to clinical trials.

Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence.

BACKGROUND: The rhetoric surrounding clinical artificial intelligence (AI) often exaggerates its effect on real-world care. Limited understanding of the factors that influence its implementation can perpetuate this. OBJECTIVE: In this qualitative systematic review, we aimed to identify key stakeholders, consolidate their perspectives on clinical AI implementation, and characterize the evidence gaps that future qualitative research should target. METHODS: Ovid-MEDLINE, EBSCO-CINAHL, ACM Digital Library, Science Citation Index-Web of Science, and Scopus were searched for primary qualitative studies on individuals' perspectives on any application of clinical AI worldwide (January 2014-April 2021). The definition of clinical AI includes both rule-based and machine learning-enabled or non-rule-based decision support tools. The language of the reports was not an exclusion criterion. Two independent reviewers performed title, abstract, and full-text screening with a third arbiter of disagreement. Two reviewers assigned the Joanna Briggs Institute 10-point checklist for qualitative research scores for each study. A single reviewer extracted free-text data relevant to clinical AI implementation, noting the stakeholders contributing to each excerpt. The best-fit framework synthesis used the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. To validate the data and improve accessibility, coauthors representing each emergent stakeholder group codeveloped summaries of the factors most relevant to their respective groups. RESULTS: The initial search yielded 4437 deduplicated articles, with 111 (2.5%) eligible for inclusion (median Joanna Briggs Institute 10-point checklist for qualitative research score, 8/10). Five distinct stakeholder groups emerged from the data: health care professionals (HCPs), patients, carers and other members of the public, developers, health care managers and leaders, and regulators or policy makers, contributing 1204 (70%), 196 (11.4%), 133 (7.7%), 129 (7.5%), and 59 (3.4%) of 1721 eligible excerpts, respectively. All stakeholder groups independently identified a breadth of implementation factors, with each producing data that were mapped between 17 and 24 of the 27 adapted Nonadoption, Abandonment, Scale-up, Spread, and Sustainability subdomains. Most of the factors that stakeholders found influential in the implementation of rule-based clinical AI also applied to non-rule-based clinical AI, with the exception of intellectual property, regulation, and sociocultural attitudes. CONCLUSIONS: Clinical AI implementation is influenced by many interdependent factors, which are in turn influenced by at least 5 distinct stakeholder groups. This implies that effective research and practice of clinical AI implementation should consider multiple stakeholder perspectives. The current underrepresentation of perspectives from stakeholders other than HCPs in the literature may limit the anticipation and management of the factors that influence successful clinical AI implementation. Future research should not only widen the representation of tools and contexts in qualitative research but also specifically investigate the perspectives of all stakeholder HCPs and emerging aspects of non-rule-based clinical AI implementation. TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews) CRD42021256005; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=256005. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/33145.

Risk Factors for Perioperative Brain Lesions in Infants With Congenital Heart Disease: A European Collaboration.

BACKGROUND: Infants with congenital heart disease are at risk of brain injury and impaired neurodevelopment. The aim was to investigate risk factors for perioperative brain lesions in infants with congenital heart disease. METHODS: Infants with transposition of the great arteries, single ventricle physiology, and left ventricular outflow tract and/or aortic arch obstruction undergoing cardiac surgery <6 weeks after birth from 3 European cohorts (Utrecht, Zurich, and London) were combined. Brain lesions were scored on preoperative (transposition of the great arteries N=104; single ventricle physiology N=35; and left ventricular outflow tract and/or aortic arch obstruction N=41) and postoperative (transposition of the great arteries N=88; single ventricle physiology N=28; and left ventricular outflow tract and/or aortic arch obstruction N=30) magnetic resonance imaging for risk factor analysis of arterial ischemic stroke, cerebral sinus venous thrombosis, and white matter injury. RESULTS: Preoperatively, induced vaginal delivery (odds ratio [OR], 2.23 [95% CI, 1.06-4.70]) was associated with white matter injury and balloon atrial septostomy increased the risk of white matter injury (OR, 2.51 [95% CI, 1.23-5.20]) and arterial ischemic stroke (OR, 4.49 [95% CI, 1.20-21.49]). Postoperatively, younger postnatal age at surgery (OR, 1.18 [95% CI, 1.05-1.33]) and selective cerebral perfusion, particularly at ≤20 °C (OR, 13.46 [95% CI, 3.58-67.10]), were associated with new arterial ischemic stroke. Single ventricle physiology was associated with new white matter injury (OR, 2.88 [95% CI, 1.20-6.95]) and transposition of the great arteries with new cerebral sinus venous thrombosis (OR, 13.47 [95% CI, 2.28-95.66]). Delayed sternal closure (OR, 3.47 [95% CI, 1.08-13.06]) and lower intraoperative temperatures (OR, 1.22 [95% CI, 1.07-1.36]) also increased the risk of new cerebral sinus venous thrombosis. CONCLUSIONS: Delivery planning and surgery timing may be modifiable risk factors that allow personalized treatment to minimize the risk of perioperative brain injury in severe congenital heart disease. Further research is needed to optimize cerebral perfusion techniques for neonatal surgery and to confirm the relationship between cerebral sinus venous thrombosis and perioperative risk factors.

Quantitative Analysis of OCT for Neovascular Age-Related Macular Degeneration Using Deep Learning.

PURPOSE: To apply a deep learning algorithm for automated, objective, and comprehensive quantification of OCT scans to a large real-world dataset of eyes with neovascular age-related macular degeneration (AMD) and make the raw segmentation output data openly available for further research. DESIGN: Retrospective analysis of OCT images from the Moorfields Eye Hospital AMD Database. PARTICIPANTS: A total of 2473 first-treated eyes and 493 second-treated eyes that commenced therapy for neovascular AMD between June 2012 and June 2017. METHODS: A deep learning algorithm was used to segment all baseline OCT scans. Volumes were calculated for segmented features such as neurosensory retina (NSR), drusen, intraretinal fluid (IRF), subretinal fluid (SRF), subretinal hyperreflective material (SHRM), retinal pigment epithelium (RPE), hyperreflective foci (HRF), fibrovascular pigment epithelium detachment (fvPED), and serous PED (sPED). Analyses included comparisons between first- and second-treated eyes by visual acuity (VA) and race/ethnicity and correlations between volumes. MAIN OUTCOME MEASURES: Volumes of segmented features (mm3) and central subfield thickness (CST) (µm). RESULTS: In first-treated eyes, the majority had both IRF and SRF (54.7%). First-treated eyes had greater volumes for all segmented tissues, with the exception of drusen, which was greater in second-treated eyes. In first-treated eyes, older age was associated with lower volumes for RPE, SRF, NSR, and sPED; in second-treated eyes, older age was associated with lower volumes of NSR, RPE, sPED, fvPED, and SRF. Eyes from Black individuals had higher SRF, RPE, and serous PED volumes compared with other ethnic groups. Greater volumes of the majority of features were associated with worse VA. CONCLUSIONS: We report the results of large-scale automated quantification of a novel range of baseline features in neovascular AMD. Major differences between first- and second-treated eyes, with increasing age, and between ethnicities are highlighted. In the coming years, enhanced, automated OCT segmentation may assist personalization of real-world care and the detection of novel structure-function correlations. These data will be made publicly available for replication and future investigation by the AMD research community.

Cognitive function in toddlers with congenital heart disease: The impact of a stimulating home environment.

Infants born with congenital heart disease (CHD) are at increased risk of neurodevelopmental difficulties in childhood. The extent to which perioperative factors, cardiac physiology, brain injury severity, socioeconomic status, and home environment influence early neurodevelopment is not clear. Sixty-nine newborns with CHD were recruited from St Thomas' Hospital. Infants underwent presurgical magnetic resonance imaging on a 3-Tesla scanner situated on the neonatal unit. At 22 months, children completed the Bayley Scales of Infant and Toddler Development-3rd edition and parents completed the cognitively stimulating parenting scale to assess cognitive stimulation at home. Level of maternal education and total annual household income were also collected. Hospital records were reviewed to calculate days on the intensive care unit post-surgery, time on bypass during surgery, and days to corrective or definitive palliative surgical intervention. In the final analysis of 56 infants, higher scores on the cognitively stimulating parenting scale were associated with higher cognitive scores at age 22 months, correcting for gestational age at birth, sex, and maternal education. There were no relationships between outcome scores and clinical factors; socioeconomic status; or brain injury severity. Supporting parents to provide a stimulating home environment for children may promote cognitive development in this high-risk population.

Pancreas-derived mesenchymal stromal cells share immune response-modulating and angiogenic potential with bone marrow mesenchymal stromal cells and can be grown to therapeutic scale under Good Manufacturing Practice conditions.

BACKGROUND AIMS: Mesenchymal stromal cells (MSCs) isolated from various tissues are under investigation as cellular therapeutics in a wide range of diseases. It is appreciated that the basic biological functions of MSCs vary depending on tissue source. However, in-depth comparative analyses between MSCs isolated from different tissue sources under Good Manufacturing Practice (GMP) conditions are lacking. Human clinical-grade low-purity islet (LPI) fractions are generated as a byproduct of islet isolation for transplantation. MSC isolates were derived from LPI fractions with the aim of performing a systematic, standardized comparative analysis of these cells with clinically relevant bone marrow-derived MSCs (BM MSCs). METHODS: MSC isolates were derived from LPI fractions and expanded in platelet lysate-supplemented medium or in commercially available xenogeneic-free medium. Doubling rate, phenotype, differentiation potential, gene expression, protein production and immunomodulatory capacity of LPIs were compared with those of BM MSCs. RESULTS: MSCs can be readily derived in vitro from non-transplanted fractions resulting from islet cell processing (i.e., LPI MSCs). LPI MSCs grow stably in serum-free or platelet lysate-supplemented media and demonstrate in vitro self-renewal, as measured by colony-forming unit assay. LPI MSCs express patterns of chemokines and pro-regenerative factors similar to those of BM MSCs and, importantly, are equally able to attract immune cells in vitro and in vivo and suppress T-cell proliferation in vitro. Additionally, LPI MSCs can be expanded to therapeutically relevant doses at low passage under GMP conditions. CONCLUSIONS: LPI MSCs represent an alternative source of GMP MSCs with functions comparable to BM MSCs.

Different patterns of cortical maturation before and after 38 weeks gestational age demonstrated by diffusion MRI in vivo.

Human cortical development during the third trimester is characterised by macro- and microstructural changes which are reflected in alterations in diffusion MRI (dMRI) measures, with significant decreases in cortical mean diffusivity (MD) and fractional anisotropy (FA). This has been interpreted as reflecting increased cellular density and dendritic arborisation. However, the fall in FA stops abruptly at 38 weeks post-menstrual age (PMA), and then tends to plateau, while MD continues to fall, suggesting a more complex picture and raising the hypothesis that after this age development is dominated by continuing increase in neural and organelle density rather than alterations in the geometry of dendritic trees. To test this, we used neurite orientation dispersion and density imaging (NODDI), acquiring multi-shell, high angular resolution dMRI and measures of cortical volume and mean curvature in 99 preterm infants scanned between 25 and 47 weeks PMA. We predicted that increased neurite and organelle density would be reflected in increases in neurite density index (NDI), while a relatively unchanging geometrical structure would be associated with constant orientation dispersion index (ODI). As dendritic arborisation is likely to be one of the drivers of gyrification, we also predicted that measures of cortical volume and curvature would correlate with ODI and show slower growth after 38 weeks. We observed a decrease of MD throughout the period, while cortical FA decreased from 25 to 38 weeks PMA and then increased. ODI increased up to 38 weeks and then plateaued, while NDI rose after 38 weeks. The evolution of ODI correlated with cortical volume and curvature. Regional analysis of cortical microstructure revealed a heterogenous pattern with increases in FA and NDI after 38 weeks confined to primary motor and sensory regions. These results support the interpretation that cortical development between 25 and 38 weeks PMA shows a predominant increase in dendritic arborisation and neurite growth, while between 38 and 47 weeks PMA it is dominated by increasing cellular and organelle density.

Key challenges for delivering clinical impact with artificial intelligence.

BACKGROUND: Artificial intelligence (AI) research in healthcare is accelerating rapidly, with potential applications being demonstrated across various domains of medicine. However, there are currently limited examples of such techniques being successfully deployed into clinical practice. This article explores the main challenges and limitations of AI in healthcare, and considers the steps required to translate these potentially transformative technologies from research to clinical practice. MAIN BODY: Key challenges for the translation of AI systems in healthcare include those intrinsic to the science of machine learning, logistical difficulties in implementation, and consideration of the barriers to adoption as well as of the necessary sociocultural or pathway changes. Robust peer-reviewed clinical evaluation as part of randomised controlled trials should be viewed as the gold standard for evidence generation, but conducting these in practice may not always be appropriate or feasible. Performance metrics should aim to capture real clinical applicability and be understandable to intended users. Regulation that balances the pace of innovation with the potential for harm, alongside thoughtful post-market surveillance, is required to ensure that patients are not exposed to dangerous interventions nor deprived of access to beneficial innovations. Mechanisms to enable direct comparisons of AI systems must be developed, including the use of independent, local and representative test sets. Developers of AI algorithms must be vigilant to potential dangers, including dataset shift, accidental fitting of confounders, unintended discriminatory bias, the challenges of generalisation to new populations, and the unintended negative consequences of new algorithms on health outcomes. CONCLUSION: The safe and timely translation of AI research into clinically validated and appropriately regulated systems that can benefit everyone is challenging. Robust clinical evaluation, using metrics that are intuitive to clinicians and ideally go beyond measures of technical accuracy to include quality of care and patient outcomes, is essential. Further work is required (1) to identify themes of algorithmic bias and unfairness while developing mitigations to address these, (2) to reduce brittleness and improve generalisability, and (3) to develop methods for improved interpretability of machine learning predictions. If these goals can be achieved, the benefits for patients are likely to be transformational.

Neuroimaging, cardiovascular physiology, and functional outcomes in infants with congenital heart disease.

This review integrates data on brain dysmaturation and acquired brain injury using fetal and neonatal magnetic resonance imaging (MRI), including the contribution of cardiovascular physiology to differences in brain development, and the relationship between brain abnormalities and subsequent neurological impairments in infants with congenital heart disease (CHD). The antenatal and neonatal period are critical for optimal brain development; the developing brain is particularly vulnerable to haemodynamic disturbances during this time. Altered cerebral perfusion and decreased cerebral oxygen delivery in the antenatal period can affect functional and structural brain development, while postnatal haemodynamic fluctuations may cause additional injury. In critical CHD, brain dysmaturation and acquired brain injury result from a combination of underlying cardiovascular pathology and surgery performed in the neonatal period. MRI findings in infants with CHD can be used to evaluate potential clinical risk factors for brain abnormalities, and aid prediction of functional outcomes at an early stage. In addition, information on timing of brain dysmaturation and acquired brain injury in CHD has the potential to be used when developing strategies to optimize neurodevelopment.

Perioperative pulmonary aspiration is infrequent and low risk in pediatric anesthetic practice.

Recent studies have reported perioperative pulmonary aspiration in pediatric practice to be an uncommon problem associated with low morbidity and mortality. This paper examines the recent publications in both the adult and pediatric literature and looks at some of the potential risk factors involved, both patient and anesthetic, in the development of aspiration of gastric contents. We also look at the risk of severe morbidity following pulmonary aspiration and speculate on possible reasons behind the assertion that pulmonary aspiration in pediatric anesthetic practice is rare and a low-risk event.

Analysis of protected species observer data: Strengths, weaknesses, and application in the assessment of marine mammal responses to seismic surveys in the northern Gulf of Mexico 2002-2015.

Visual observation data collected by protected species observers (PSOs) is required per regulations stipulated in Notices to Lessees (NTLs) and geophysical survey Permits (Form BOEM-0328) issued to seismic operators in the Gulf of Mexico (GOM). Here, data collected by certified and trained PSOs during seismic surveys conducted between 2002-2015 were compiled and analyzed to assess utility in assessing marine mammal responses to seismic noise and effectiveness of required mitigation measures. A total of 3,886 agency-required bi-weekly PSO Effort and Sightings reports were analyzed comprising 598,319 hours of PSO visual effort and 15,117 visual sighting records of marine mammals. The observed closest point of approach (CPA) distance was statistically compared across five species groupings for four airgun activity levels (full, minimum source, ramp up, silent). Whale and dolphin detections were significantly farther from airgun array locations during full power operations versus silence, indicating some avoidance response to full-power operations. Dolphin CPA distances were also significantly farther from airguns operating at minimum source than silence. Blackfish were observed significantly farther from the airgun array during ramp up versus both full and minimum source activities. Blackfish were observed significantly closer to the airgun array during silent activities versus at full, minimum source, and ramp up activities. Beaked whales had the largest mean CPA for detection distance compared to all other species groups. Detection distances for beaked whales were not significantly differences between full and silent operations; however, the sample size was very low. Overall results are consistent with other studies indicating that marine mammals may avoid exposure to airgun sounds based on observed distance from the seismic source during specified source activities. There was geographic variability in sighting rates associated with specific areas of interest within the GOM. This study demonstrates that agency required PSO reports provide a robust and useful data set applicable to impact assessments; management, policy and regulatory decision making; and qualitative input for regional scientific, stock assessment and abundance studies. However, several improvements in content and consistency would facilitate finer-scale analysis of some topics (e.g., effort associated with specific activities, observer biases, sound field estimation) and support statistical comparisons that could provide further insight into marine mammal responses and mitigation efficacy.

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines.

The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77-94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines.

Individual Assessment of Perioperative Brain Growth Trajectories in Infants With Congenital Heart Disease: Correlation With Clinical and Surgical Risk Factors.

Background Infants with congenital heart disease (CHD) are at risk of neurodevelopmental impairments, which may be associated with impaired brain growth. We characterized how perioperative brain growth in infants with CHD deviates from typical trajectories and assessed the relationship between individualized perioperative brain growth and clinical risk factors. Methods and Results A total of 36 infants with CHD underwent preoperative and postoperative brain magnetic resonance imaging. Regional brain volumes were extracted. Normative volumetric development curves were generated using data from 219 healthy infants. Z-scores, representing the degree of positive or negative deviation from the normative mean for age and sex, were calculated for regional brain volumes from each infant with CHD before and after surgery. The degree of Z-score change was correlated with clinical risk factors. Perioperative growth was impaired across the brain, and it was associated with longer postoperative intensive care stay (false discovery rate P<0.05). Higher preoperative creatinine levels were associated with impaired brainstem, caudate nuclei, and right thalamus growth (all false discovery rate P=0.033). Older postnatal age at surgery was associated with impaired brainstem and right lentiform growth (both false discovery rate P=0.042). Longer cardiopulmonary bypass duration was associated with impaired brainstem and right caudate growth (false discovery rate P<0.027). Conclusions Infants with CHD can have impaired brain growth in the immediate postoperative period, the degree of which associates with postoperative intensive care duration. Brainstem growth appears particularly vulnerable to perioperative clinical course, whereas impaired deep gray matter growth was associated with multiple clinical risk factors, possibly reflecting vulnerability of these regions to short- and long-term hypoxic injury.

Diseases of oysters Crassostrea ariakensis and C. virginica reared in ambient waters from the Choptank River, Maryland and the Indian River Lagoon, Florida.

To assess potential benefits and liabilities from a proposed introduction of Asian Suminoe oysters, susceptibilities of exotic Crassostrea ariakensis and native C. virginica oysters were compared during exposures to pathogens endemic in temperate, mesohaline waters of Chesapeake Bay and sub-tropical, polyhaline Atlantic waters of southern Florida, USA. Cohorts of diploid, sibling oysters of both species were periodically tested for diseases while reared in mesocosms receiving ambient waters from the Choptank River, Maryland (>3 yr) or the Indian River Lagoon, Florida (10 to 11 mo). Haplosporidium sp. infections (e.g. MSX disease) were not detected in oysters from either site. Perkinsus sp. infections (dermo disease) occurred among members of both oyster species at both sites, but infections were generally of low or moderate intensities. A Bonamia sp. was detected by PCR of DNAs from tissues of both oyster species following exposure to Florida waters, with maximum PCR prevalences of 44 and 15% among C. ariakensis and C. virginica oysters respectively during June 2007. Among C. ariakensis oysters sampled during April to July 2007, a Bonamia sp. was detected in 31% of oysters by PCR (range 11 to 35%) and confirmed histologically in 10% (range 0 to 15%). Among simultaneously sampled C. virginica oysters, a Bonamia sp. was detected in 7% by PCR (range 0 to 15%), but histological lesions were absent. Although this is the first report of a Bonamia sp. from Florida waters, sequences of small subunit (SSU) rDNA and in situ hybridization (ISH) assays both identified the Florida pathogen as Bonamia exitiosa, which also infects oysters in the proximate waters of North Carolina, USA.