Characterizing cerebral metabolite profiles in anorexia and bulimia nervosa and their associations with habitual behavior.

Anorexia nervosa (AN) and bulimia nervosa (BN) are associated with altered brain structure and function, as well as increased habitual behavior. This neurobehavioral profile may implicate neurochemical changes in the pathogenesis of these illnesses. Altered glutamate, myo-inositol and N-acetyl aspartate (NAA) concentrations are reported in restrictive AN, yet whether these extend to binge-eating disorders, or relate to habitual traits in affected individuals, remains unknown. We therefore used single-voxel proton magnetic resonance spectroscopy to measure glutamate, myo-inositol, and NAA in the right inferior lateral prefrontal cortex and the right occipital cortex of 85 women [n = 22 AN (binge-eating/purging subtype; AN-BP), n = 33 BN, n = 30 controls]. To index habitual behavior, participants performed an instrumental learning task and completed the Creature of Habit Scale. Women with AN-BP, but not BN, had reduced myo-inositol and NAA concentrations relative to controls in both regions. Although patient groups had intact instrumental learning task performance, both groups reported increased routine behaviors compared to controls, and automaticity was related to reduced prefrontal glutamate and NAA participants with AN-BP. Our findings extend previous reports of reduced myo-inositol and NAA levels in restrictive AN to AN-BP, which may reflect disrupted axonal-glial signaling. Although we found inconsistent support for increased habitual behavior in AN-BP and BN, we identified preliminary associations between prefrontal metabolites and automaticity in AN-BP. These results provide further evidence of unique neurobiological profiles across binge-eating disorders.

Medium-term outcomes in single anaesthetic bilateral total knee replacement surgery: a single surgeon series.

BACKGROUND: The lifetime risk of developing symptomatic knee osteoarthritis (OA) is estimated to be 45%, with up to two thirds of patients presenting with bilateral knee symptoms. Patients presenting with end stage bilateral knee OA may benefit from single anaesthetic bilateral total knee replacement (SABTKR). Our study aim was to compare the outcomes of SABTKR with unilateral total knee arthroplasty (TKA) in a single surgeon series over a 20 year period. METHODS: We performed a retrospective review of a single surgeon's data from the New Zealand Joint Registry (NZJR) over a 20-year period from January 1999 to December 2018. This review reports on patient demographics, functional outcomes, revision rates and mortality rates. RESULTS: 1225 total knee replacements were performed by the senior author (995 TKAs and 115 patients underwent SABTKRs) over the 20 year period reviewed. The mean ages of the TKA and SABTKR groups were 67.7 and 66.7 years, respectively. There was 16.9% mortality rate for the TKA group versus 7.8% in SABTKR group. There were no revisions in the SABTKR group versus 17 revisions in the TKA group representing a revision rate of 0.23/100 component years which can be viewed against a 20 year revision rate of 0.48/100 component years (p < 0.05) for all comers in the NZJR. CONCLUSION: This NZJR study demonstrates excellent medium term survival outcomes for selected patients having simultaneous bilateral total knee replacements.

Dopamine, Prediction Error and Beyond.

A large body of work has linked dopaminergic signaling to learning and reward processing. It stresses the role of dopamine in reward prediction error signaling, a key neural signal that allows us to learn from past experiences, and that facilitates optimal choice behavior. Latterly, it has become clear that dopamine does not merely code prediction error size but also signals the difference between the expected value of rewards, and the value of rewards actually received, which is obtained through the integration of reward attributes such as the type, amount, probability and delay. More recent work has posited a role of dopamine in learning beyond rewards. These theories suggest that dopamine codes absolute or unsigned prediction errors, playing a key role in how the brain models associative regularities within its environment, while incorporating critical information about the reliability of those regularities. Work is emerging supporting this perspective and, it has inspired theoretical models of how certain forms of mental pathology may emerge in relation to dopamine function. Such pathology is frequently related to disturbed inferences leading to altered internal models of the environment. Thus, it is critical to understand the role of dopamine in error-related learning and inference.

Genomic characterisation of Salmonella enterica serovar Wangata isolates obtained from different sources reveals low genomic diversity.

Salmonella enterica serovar Wangata is an important pathogen in New South Wales (NSW), Australia. The incidence of S. Wangata is increasing and transmission is suspected to be via a non-food source. A recent outbreak investigation of sources of S. Wangata recovered isolates from humans, domestic animals, wildlife and the environment. Here, we extend that investigation by characterising and describing the genomic determinates of these isolates. We found that Australian S. Wangata isolates from different sources exhibited similar virulence and antimicrobial resistance gene profiles. There were no major genomic differences between isolates obtained from different geographical regions within Australia or from different host species. In addition, we found evidence (low number of SNPs and identical virulence gene profiles) suggestive of an international transmission event between Australia and the United Kingdom. This study supports the hypothesis that S. Wangata is shared between different hosts in NSW, Australia and provides strong justification for the continued use of genomic surveillance of Salmonella.

Divergent geography of Salmonella Wangata and Salmonella Typhimurium epidemiology in New South Wales, Australia.

Salmonella enterica serovar Wangata is an important cause of salmonellosis in the state of New South Wales, Australia. Standard surveillance has not identified a common food source and cases have been attributed to an unknown environmental or wildlife reservoir. Investigation of the spatial distribution of cases may provide valuable insights into local risk factors for infection and the potential role of the environment and wildlife. Using conditional autoregressive analysis, we explored the association between laboratory-confirmed cases of S. Wangata reported to the New South Wales Department of Health and human socio-demographic, climate, land cover and wildlife features. For comparison, a model was also fitted to investigate the association of cases of Salmonella enterica serovar Typhimurium, an established foodborne serotype, with the same features. To determine if cases of S. Wangata were associated with potential wildlife reservoir species, additional variables were included in the S. Wangata model that indicated areas of high suitability for each species. We found that cases of S. Wangata were associated with warmer temperatures, proximity to wetlands and amphibian species richness. In contrast, cases of S. Typhimurium were associated with human demographic features (proportion of the population comprising children <5 years old), climate (mean annual precipitation and mean annual temperature) and land cover (proportion comprising urban and evergreen broadleaf forest). These findings support the hypothesis that S. Wangata is likely to be associated with an environmental source. Whilst we expected S. Typhimurium to be associated with the human socio-demographic feature, the significance of the land cover features was surprising and might suggest the epidemiology of S. Typhimurium in Australia is more complex than currently understood.

The aetiology of posterior glenohumeral dislocations and occurrence of associated injuries: a systematic review.

AIMS: The glenohumeral joint is the most frequently dislocated articulation, but possibly due to the lower prevalence of posterior shoulder dislocations, approximately 50% to 79% of posterior glenohumeral dislocations are missed at initial presentation. The aim of this study was to systematically evaluate the most recent evidence involving the aetiology of posterior glenohumeral dislocations, as well as the diagnosis and treatment. MATERIALS AND METHODS: A systematic search was conducted using PubMed (MEDLINE), Web of Science, Embase, and Cochrane (January 1997 to September 2017), with references from articles also evaluated. Studies reporting patients who experienced an acute posterior glenohumeral joint subluxation and/or dislocation, as well as the aetiology of posterior glenohumeral dislocations, were included. RESULTS: A total of 54 studies met the inclusion criteria. In total, 182 patients were included in this analysis; study sizes ranged from one to 66 patients, with a mean age of 44.2 years (sd 13.7). There was a higher proportion of male patients. In all, 216 shoulders were included with 148 unilateral injuries and 34 bilateral. Seizures were implicated in 38% of patients (n = 69), with falls, road traffic accidents, electric shock, and iatrogenic reasons also described. Time to diagnosis varied across studies from immediate up to a delay of 25 years. Multiple associated injuries are described. CONCLUSION: This review provides an up-to-date insight into the aetiology of posterior shoulder dislocations. Our results showed that seizures were most commonly implicated. Overall, reduction was achieved via open means in the majority of shoulders. We also found that delayed diagnosis is common.

Diversity of Salmonella serotypes from humans, food, domestic animals and wildlife in New South Wales, Australia.

BACKGROUND: Salmonella is an important human pathogen in Australia and annual case rates continue to increase. In addition to foodborne exposures, cases have been associated with animal and contaminated environment contact. However, routine surveillance in Australia has tended to focus on humans and food, with no reported attempts to collate and compare Salmonella data from a wider range of potential sources of exposure. METHODS: Salmonella data from humans, food, animals and environments were collated from a range of surveillance and diagnostic sources in New South Wales (NSW). Data were categorised to reflect one of 29 sample origins. Serotype diversity was described for each category, and the distribution of serotypes commonly isolated from humans was examined for each sample origin. The distribution of serotypes along the livestock-food-human continuum and at the companion animal-wildlife interface was also examined. RESULTS: In total, 49,872 Salmonella isolates were included in this analysis, comprising 325 serotypes. The vast majority of these isolates were from humans (n = 38,106). Overall S. Typhimurium was the most frequently isolated serotype and was isolated from all sample categories except natural environment and game meat. S. Enteriditis was not isolated from any livestock animal, however sporadic cases were documented in food, companion animals and a reptile. Many serotypes that were frequently isolated from livestock animals and associated food products were only rarely isolated from humans. In addition, a number of key human serotypes were only sporadically isolated from livestock and food products, suggesting alternative sources of infection. In particular, S. Paratyphi B Java and S. Wangata were more often isolated from wild animals. Finally, there was some overlap between serotypes in companion animals and wildlife, with cats in particular having a large number of serotypes in common with wild birds. CONCLUSIONS: This is the most comprehensive description of Salmonella data from humans, food, livestock, wildlife, companion animals and various environments in Australia reported to date. Results confirm that livestock and food are important sources of salmonellosis in humans but that alternative sources - such as contact with wildlife and environments - warrant further investigation. Surveillance in NSW is largely human-focussed: major knowledge gaps exist regarding the diversity and frequency of serotypes in animals. More systematic surveillance of domestic animals and wildlife is needed to inform targeted control strategies and quantitative source attribution modelling in this state.

Associations between cortical thickness, structural connectivity and severity of dimensional bulimia nervosa symptomatology.

Bulimia nervosa (BN) is a psychiatric illness defined by preoccupation with body image (cognitive 'symptoms'), binge eating and compensatory behaviors. Although diagnosed BN has been related to grey matter alterations, characterization of brain structure in women with a range of BN symptoms has not been made. This study examined whether cortical thickness (CT) values scaled with severity of BN cognitions in 33 women with variable BN pathology. We then assessed global structural connectivity (SC) of CT to determine if individual differences in global SC relate to BN symptom severity. We used the Eating Disorder Examination Questionnaire (EDE-Q) as a continuous measure of BN symptom severity. EDE-Q score was negatively related to global CT and local CT in the left middle frontal gyrus, right superior frontal gyrus and bilateral orbitofrontal cortex (OFC) and temporoparietal regions. Moreover, cortical thinning was most pronounced in regions with high global connectivity. Finally, individual contributions to global SC at the group level related to EDE-Q score, where increased EDE-Q score correlated with reduced connectivity of the left OFC and middle temporal cortex and increased connectivity of the right superior parietal lobule. Findings represent the first evidence of cortical thinning that relates to cognitive BN symptoms.

Insulin and leptin excite anorexigenic pro-opiomelanocortin neurones via activation of TRPC5 channels.

Pro-opiomelanocortin (POMC) neurones within the hypothalamic arcuate nucleus are vital anorexigenic neurones. Both the insulin receptor and leptin receptor are coupled to activation of phosphatidylinositide-3 kinase (PI3K) to regulate multiple functions that increase POMC neuronal excitability. Using whole-cell recording in several mammalian species, we have found that both insulin and leptin depolarised POMC neurones via activation of transient receptor potential (TRPC)5 channels. TRPC5 channels have been rigorously characterised as the downstream effector based on their biophysical properties, pharmacological profile, and localisation by immunocytochemistry and single-cell reverse transcriptase-polymerase chain reaction. By contrast, insulin and leptin hyperpolarise and inhibit neuropeptide Y/agouti-related peptide neurones via activation of KATP channels. As proof of principle, insulin given i.c.v. robustly inhibits food intake and increases O2 utilisation, CO2 production and metabolic heat production. Therefore, these findings indicate that the depolarisation/excitation of POMC neurones by insulin and leptin is preserved across mammalian species and the activation of TRPC5 channels is likely a major mechanism by which insulin and leptin regulate energy homeostasis in mammals.

Genome-wide association study and annotating candidate gene networks affecting age at first calving in Nellore cattle.

We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken.

Multiple-trait genomewide mapping and gene network analysis for scrotal circumference growth curves in Brahman cattle.

Fertility traits are economically important in cattle breeding programs. Scrotal circumference (SC) measures are repeatable, easily obtained, highly heritable, and positively correlated with female fertility traits and sperm quality traits in males. A useful approach to summarize SC measures over time is using nonlinear models, which summarize specific measures of SC in a few parameters with biological interpretation. This approach facilitates the selection of bulls with larger SC and maturity index (K), that is, early maturing animals. Because SC is a sex-limited trait, identifying the underlying genomics of growth curve parameters will allow selection across both males and females. We reported the first multitrait genomewide association study (GWAS) of estimated growth curve parameters for SC data in Brahman cattle. Five widely used nonlinear models were tested to fit a total of 3,612 SC records, measured at 6, 12, 18, and 24 mo of age. The von Bertalanffy model, individually fitted for each animal, best fit this SC data. Parameter estimates SC at maturity (A) and K as well as SC at all ages were jointly analyzed in a GWAS to identify 1-Mb regions most strongly associated with each trait. Heritabilities were 0.25 for K and 0.32 for A and ranged from 0.51 to 0.72 for SC at 6 (SC6), 12 (SC12), 18 (SC18), and 24 mo of age (SC24). An overlapping window on chromosome 14 explaining around 0.8% of genetic variance for K, SC12, SC18, and SC24 was observed. The major positional candidate genes within 1 Mb upstream and downstream of this overlapping window were , , , and . Windows of 1 Mb explaining more than 0.4% of each trait on chromosomes 1, 3, 6, 7, 14, 17, 18, 24, 25, and 26 were identified. Pathways and net-work analyses were indicated through transcription factors playing a role on fertility traits: , , , , , , and . Further validation studies on larger populations or other breeds are required to validate these findings and to improve our understanding of the biology and complex genetic architecture of traits associated with scrotal growth and male fertility in cattle.

Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum.

Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness.SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that are modulated by the brain chemical dopamine are sensitive to reward variability. Here, we aimed to directly relate dopamine to learning about variable rewards, and the neural encoding of associated teaching signals. We perturbed dopamine in healthy individuals using dopaminergic medication and asked them to predict variable rewards while we made brain scans. Dopamine perturbations impaired learning and the neural encoding of reward variability, thus establishing a direct link between dopamine and adaptation to reward variability. These results aid our understanding of clinical conditions associated with dopaminergic dysfunction, such as psychosis.

Adaptive Prediction Error Coding in the Human Midbrain and Striatum Facilitates Behavioral Adaptation and Learning Efficiency.

Effective error-driven learning benefits from scaling of prediction errors to reward variability. Such behavioral adaptation may be facilitated by neurons coding prediction errors relative to the standard deviation (SD) of reward distributions. To investigate this hypothesis, we required participants to predict the magnitude of upcoming reward drawn from distributions with different SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. In line with the notion of adaptive coding, BOLD response slopes in the Substantia Nigra/Ventral Tegmental Area (SN/VTA) and ventral striatum were steeper for prediction errors occurring in distributions with smaller SDs. SN/VTA adaptation was not instantaneous but developed across trials. Adaptive prediction error coding was paralleled by behavioral adaptation, as reflected by SD-dependent changes in learning rate. Crucially, increased SN/VTA and ventral striatal adaptation was related to improved task performance. These results suggest that adaptive coding facilitates behavioral adaptation and supports efficient learning.

Differential Patterns of Dysconnectivity in Mirror Neuron and Mentalizing Networks in Schizophrenia.

Impairments of social cognition are well documented in patients with schizophrenia (SCZ), but the neural basis remains poorly understood. In light of evidence that suggests that the "mirror neuron system" (MNS) and the "mentalizing network" (MENT) are key substrates of intersubjectivity and joint action, it has been suggested that dysfunction of these neural networks may underlie social difficulties in SCZ patients. Additionally, MNS and MENT might be associated differently with positive vs negative symptoms, given prior social cognitive and symptom associations. We assessed resting state functional connectivity (RSFC) in meta-analytically defined MNS and MENT networks in this patient group. Magnetic resonance imaging (MRI) scans were obtained from 116 patients and 133 age-, gender- and movement-matched healthy controls (HC) at 5 different MRI sites. Network connectivity was analyzed for group differences and correlations with clinical symptoms. Results demonstrated decreased connectivity within the MNS and also the MENT in patients compared to controls. Notably, dysconnectivity of the MNS was related to symptom severity, while no such relationship was observed for the MENT. In sum, these findings demonstrate that differential patterns of dysconnectivity exist in SCZ patients, which may contribute differently to the interpersonal difficulties commonly observed in the disorder.

A specific nanomanufacturing challenge.

For a science to become a technology, a certain level of control has to have been established over the way items are fabricated for manufacture and use. Here we first consider the challenge of making and using a LEGO(®) brick scaled down by a factor of 10(n) for n = 0-6 in each spatial dimension, i.e. from millimetres to nanometres. We consider both the manufacture and the subsequent properties of the nanobricks that pertain to their use in constructing and dismantling structures. As n increases, the ability to use fails first, to manufacture fails second and to fabricate fails last. Applied to the vast literature in nanoscience, this process emphasises the unmanufacturability of most nanoscale artefacts.

Accuracy of genomic selection for age at puberty in a multi-breed population of tropically adapted beef cattle.

Genomic selection is becoming a standard tool in livestock breeding programs, particularly for traits that are hard to measure. Accuracy of genomic selection can be improved by increasing the quantity and quality of data and potentially by improving analytical methods. Adding genotypes and phenotypes from additional breeds or crosses often improves the accuracy of genomic predictions but requires specific methodology. A model was developed to incorporate breed composition estimated from genotypes into genomic selection models. This method was applied to age at puberty data in female beef cattle (as estimated from age at first observation of a corpus luteum) from a mix of Brahman and Tropical Composite beef cattle. In this dataset, the new model incorporating breed composition did not increase the accuracy of genomic selection. However, the breeding values exhibited slightly less bias (as assessed by deviation of regression of phenotype on genomic breeding values from the expected value of 1). Adding additional Brahman animals to the Tropical Composite analysis increased the accuracy of genomic predictions and did not affect the accuracy of the Brahman predictions.

Scaling prediction errors to reward variability benefits error-driven learning in humans.

Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influence of prediction error scaling and, in particular, the consequences for learning performance. Participants explicitly predicted reward magnitudes that were drawn from different probability distributions with specific standard deviations. By fitting the data with reinforcement learning models, we found scaling of prediction errors, in addition to the learning rate decay shown previously. Importantly, the prediction error scaling was closely related to learning performance, defined as accuracy in predicting the mean of reward distributions, across individual participants. In addition, participants who scaled prediction errors relative to standard deviation also presented with more similar performance for different standard deviations, indicating that increases in standard deviation did not substantially decrease "adapters'" accuracy in predicting the means of reward distributions. However, exaggerated scaling beyond the standard deviation resulted in impaired performance. Thus efficient adaptation makes learning more robust to changing variability.

Correction: Iminoborylene complexes: evaluation of synthetic routes towards BN-allenylidenes and unexpected reactivity towards carbodiimides.

Correction for 'Iminoborylene complexes: evaluation of synthetic routes towards BN-allenylidenes and unexpected reactivity towards carbodiimides' by J. Niemeyer et al., Dalton Trans., 2015, DOI: 10.1039/c5dt00131e.