The white-rot fungus, Phanerochaete chrysosporium, under combinatorial stress produces variable oil profiles following analysis of secondary metabolites.

AIMS: The effects of combinatorial stress on lipid production in Phanerochaete chrysosporium remain understudied. This species of white-rot fungi was cultivated on solid-state media while under variable levels of known abiotic and biotic stressors to establish the effect upon fungal oil profiles. METHODS AND RESULTS: Environmental stressors induced upon the fungus included the following: temperature, nutrient limitation and interspecies competition to assess impact upon oil profiles. Fatty acid type and its concentration were determined using analytical methods of gas chromatography and mass spectrometry. Growth rate under stress was established using high-performance liquid chromatography with ergosterol as the biomarker. Fungi grown on solid-state agar were able to simultaneously produce short- and long-chain fatty acids which appeared to be influenced by nutritional composition as well as temperature. Addition of nitrogen supplements increased the growth rate, but lipid dynamics remained unchanged. Introducing competition-induced stress had significantly altered the production of certain fatty acids beyond that of the monoculture while under nutrient-limiting conditions. Linoleic acid concentrations, for example, increased from an average of 885 ng µl-1 at monoculture towards 13 820 ng µl-1 at co-culture, following 7 days of incubation. CONCLUSIONS: Interspecies competition produced the most notable impact on lipid production for solid-state media cultivated fungi while the addition of nitrogen supplementation presented growth and lipid accumulation to be uncorrelated. Combinatorial stress therefore influences the yield of overall lipid production as well as the number of intermediate fatty acids produced, deriving similar oil profiles to the composition of vegetable and fish oils. SIGNIFICANCE AND IMPACT OF THE STUDY: Fungal secondary metabolism remains highly sensitive following combinatorial stress. The outcome impacts the research towards optimizing fungal oil profiles for biomass and nutrition. Future investigations on fungal stress tolerance mechanisms need to address these environmental factors throughout the experimental design.

Adverse childhood experiences and substance misuse in young people in India: results from the multisite cVEDA cohort.

BACKGROUND: Adverse childhood experiences (ACEs) increases vulnerability to externalising disorders such as substance misuse. The study aims to determine the prevalence of ACEs and its association with substance misuse. METHODS: Data from the Consortium on Vulnerability to Externalising Disorders and Addictions (cVEDA) in India was used (n = 9010). ACEs were evaluated using the World Health Organisation (WHO) Adverse Childhood Experiences International Questionnaire whilst substance misuse was assessed using the WHO Alcohol, Smoking and Substance Involvement Screening Test. A random-effects, two-stage individual patient data meta-analysis explained the associations between ACEs and substance misuse with adjustments for confounders such as sex and family structure. RESULTS: 1 in 2 participants reported child maltreatment ACEs and family level ACEs. Except for sexual abuse, males report more of every individual childhood adversity and are more likely to report misusing substances compared with females (87.3% vs. 12.7%). In adolescents, family level ACEs (adj OR 4.2, 95% CI 1.5-11.7) and collective level ACEs (adj OR 6.6, 95% CI 1.4-31.1) show associations with substance misuse whilst in young adults, child level ACEs such as maltreatment show similar strong associations (adj OR 2.0, 95% CI 1.1-3.5). CONCLUSION: ACEs such as abuse and domestic violence are strongly associated with substance misuse, most commonly tobacco, in adolescent and young adult males in India. The results suggest enhancing current ACE resilience programmes and 'trauma-informed' approaches to tackling longer-term impact of ACEs in India. FUNDING: Newton Bhabha Grant jointly funded by the Medical Research Council, UK (MR/N000390/1) and the Indian Council of Medical Research (ICMR/MRC-UK/3/M/2015-NCD-I).

Search for Electron Antineutrino Appearance in a Long-Baseline Muon Antineutrino Beam.

Electron antineutrino appearance is measured by the T2K experiment in an accelerator-produced antineutrino beam, using additional neutrino beam operation to constrain parameters of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) mixing matrix. T2K observes 15 candidate electron antineutrino events with a background expectation of 9.3 events. Including information from the kinematic distribution of observed events, the hypothesis of no electron antineutrino appearance is disfavored with a significance of 2.40σ and no discrepancy between data and PMNS predictions is found. A complementary analysis that introduces an additional free parameter which allows non-PMNS values of electron neutrino and antineutrino appearance also finds no discrepancy between data and PMNS predictions.

Functional connectivity changes associated with fMRI neurofeedback of right inferior frontal cortex in adolescents with ADHD.

Attention Deficit Hyperactivity Disorder (ADHD) is associated with poor self-control, underpinned by inferior fronto-striatal deficits. We showed previously that 18 ADHD adolescents over 11 runs of 8.5 min of real-time functional magnetic resonance neurofeedback of the right inferior frontal cortex (rIFC) progressively increased activation in 2 regions of the rIFC which was associated with clinical symptom improvement. In this study, we used functional connectivity analyses to investigate whether fMRI-Neurofeedback of rIFC resulted in dynamic functional connectivity changes in underlying neural networks. Whole-brain seed-based functional connectivity analyses were conducted using the two clusters showing progressively increased activation in rIFC as seed regions to test for changes in functional connectivity before and after 11 fMRI-Neurofeedback runs. Furthermore, we tested whether the resulting functional connectivity changes were associated with clinical symptom improvements and whether they were specific to fMRI-Neurofeedback of rIFC when compared to a control group who had to self-regulate another region. rIFC showed increased positive functional connectivity after relative to before fMRI-Neurofeedback with dorsal caudate and anterior cingulate and increased negative functional connectivity with regions of the default mode network (DMN) such as posterior cingulate and precuneus. Furthermore, the functional connectivity changes were correlated with clinical improvements and the functional connectivity and correlation findings were specific to the rIFC-Neurofeedback group. The findings show for the first time that fMRI-Neurofeedback of a typically dysfunctional frontal region in ADHD adolescents leads to strengthening within fronto-cingulo-striatal networks and to weakening of functional connectivity with posterior DMN regions and that this may be underlying clinical improvement.

Response to initial antipsychotic treatment in first episode psychosis is related to anterior cingulate glutamate levels: a multicentre 1H-MRS study (OPTiMiSE).

Conventional antipsychotic medication is ineffective in around a third of patients with schizophrenia, and the nature of the therapeutic response is unpredictable. We investigated whether response to antipsychotics is related to brain glutamate levels prior to treatment. Proton magnetic resonance spectroscopy was used to measure glutamate levels (Glu/Cr) in the anterior cingulate cortex (ACC) and in the thalamus in antipsychotic-naive or minimally medicated patients with first episode psychosis (FEP, n = 71) and healthy volunteers (n = 60), at three sites. Following scanning, patients were treated with amisulpride for 4 weeks (n = 65), then 1H-MRS was repeated (n = 46). Remission status was defined in terms of Positive and Negative Syndrome Scale for Schizophrenia (PANSS) scores. Higher levels of Glu/Cr in the ACC were associated with more severe symptoms at presentation and a lower likelihood of being in remission at 4 weeks (P < 0.05). There were longitudinal reductions in Glu/Cr in both the ACC and thalamus over the treatment period (P < 0.05), but these changes were not associated with the therapeutic response. There were no differences in baseline Glu/Cr between patients and controls. These results extend previous evidence linking higher levels of ACC glutamate with a poor antipsychotic response by showing that the association is evident before the initiation of treatment.

Machine learning to refine decision making within a syndromic surveillance service.

BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms. METHODS: A record of the risk assessment process was obtained from Public Health England for all 67,505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final 'Decision' outcome made by an epidemiologist of 'Alert', 'Monitor' or 'No-action'. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of 'No-action' outcomes. RESULTS: The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of 'Alert' outcomes. If the 'Alert' and 'Monitor' actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system. CONCLUSIONS: Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process.

HIV: ageing, cognition and neuroimaging at 4-year follow-up.

OBJECTIVES: The aim of the study was to investigate the hypothesis of accelerated cognitive ageing in HIV-positive individuals using longitudinal assessment of cognitive performance and quantitative magnetic resonance imaging (MRI). METHODS: We assessed a broad cognitive battery and quantitative MRI metrics [voxel-based morphometry (VBM) and diffusion tensor imaging (DTI)] in asymptomatic HIV-positive men who have sex with men (15 aged 20-40 years and 15 aged ≥ 50 years), and HIV-seronegative matched controls (nine aged 20-40 years and 16 aged ≥ 50 years). RESULTS: Being HIV positive was associated with greater decreases in executive function and global cognition. Additionally, using DTI, we found that the HIV-positive group had a greater increase in mean diffusivity, but we did not find group differences in volume change using VBM. With respect to the HIV status by age group interaction, this was statistically significant for change in global cognition, with older HIV-positive individuals showing greater global cognitive decline, but there were no significant interaction effects on other measures. Lastly, change in cognitive performance was correlated with change in the DTI measures, and this effect was stronger for the HIV-positive participants. CONCLUSIONS: In the present study, we found some evidence for accelerated ageing in HIV-positive individuals, with a statistically significant HIV status by age group interaction in global cognition, although this interaction could not be explained by the imaging findings. Moreover, we also found that change in cognitive performance was correlated with change in the DTI measures, and this effect was stronger for the HIV-positive participants. This will need replication in larger studies using a similarly lengthy follow-up period.

Search for CP Violation in Neutrino and Antineutrino Oscillations by the T2K Experiment with 2.2×10

The T2K experiment measures muon neutrino disappearance and electron neutrino appearance in accelerator-produced neutrino and antineutrino beams. With an exposure of 14.7(7.6)×10^{20} protons on target in the neutrino (antineutrino) mode, 89 ν_{e} candidates and seven anti-ν_{e} candidates are observed, while 67.5 and 9.0 are expected for δ_{CP}=0 and normal mass ordering. The obtained 2σ confidence interval for the CP-violating phase, δ_{CP}, does not include the CP-conserving cases (δ_{CP}=0, π). The best-fit values of other parameters are sin^{2}θ_{23}=0.526_{-0.036}^{+0.032} and Δm_{32}^{2}=2.463_{-0.070}^{+0.071}×10^{-3} eV^{2}/c^{4}.

Combined Analysis of Neutrino and Antineutrino Oscillations at T2K.

T2K reports its first results in the search for CP violation in neutrino oscillations using appearance and disappearance channels for neutrino- and antineutrino-mode beams. The data include all runs from January 2010 to May 2016 and comprise 7.482×10^{20} protons on target in neutrino mode, which yielded in the far detector 32 e-like and 135 µ-like events, and 7.471×10^{20} protons on target in antineutrino mode, which yielded 4 e-like and 66 µ-like events. Reactor measurements of sin^{2}2θ_{13} have been used as an additional constraint. The one-dimensional confidence interval at 90% for the phase δ_{CP} spans the range (-3.13, -0.39) for normal mass ordering. The CP conservation hypothesis (δ_{CP}=0, π) is excluded at 90% C.L.

Anatomical integration and rich-club connectivity in euthymic bipolar disorder.

BACKGROUND: Although repeatedly associated with white matter microstructural alterations, bipolar disorder (BD) has been relatively unexplored using complex network analysis. This method combines structural and diffusion magnetic resonance imaging (MRI) to model the brain as a network and evaluate its topological properties. A group of highly interconnected high-density structures, termed the 'rich-club', represents an important network for integration of brain functioning. This study aimed to assess structural and rich-club connectivity properties in BD through graph theory analyses. METHOD: We obtained structural and diffusion MRI scans from 42 euthymic patients with BD type I and 43 age- and gender-matched healthy volunteers. Weighted fractional anisotropy connections mapped between cortical and subcortical structures defined the neuroanatomical networks. Next, we examined between-group differences in features of graph properties and sub-networks. RESULTS: Patients exhibited significantly reduced clustering coefficient and global efficiency, compared with controls globally and regionally in frontal and occipital regions. Additionally, patients displayed weaker sub-network connectivity in distributed regions. Rich-club analysis revealed subtly reduced density in patients, which did not withstand multiple comparison correction. However, hub identification in most participants indicated differentially affected rich-club membership in the BD group, with two hubs absent when compared with controls, namely the superior frontal gyrus and thalamus. CONCLUSIONS: This graph theory analysis presents a thorough investigation of topological features of connectivity in euthymic BD. Abnormalities of global and local measures and network components provide further neuroanatomically specific evidence for distributed dysconnectivity as a trait feature of BD.

New Elements To Consider When Modeling the Hazards Associated with Botulinum Neurotoxin in Food.

Botulinum neurotoxins (BoNTs) produced by the anaerobic bacterium Clostridium botulinum are the most potent biological substances known to mankind. BoNTs are the agents responsible for botulism, a rare condition affecting the neuromuscular junction and causing a spectrum of diseases ranging from mild cranial nerve palsies to acute respiratory failure and death. BoNTs are a potential biowarfare threat and a public health hazard, since outbreaks of foodborne botulism are caused by the ingestion of preformed BoNTs in food. Currently, mathematical models relating to the hazards associated with C. botulinum, which are largely empirical, make major contributions to botulinum risk assessment. Evaluated using statistical techniques, these models simulate the response of the bacterium to environmental conditions. Though empirical models have been successfully incorporated into risk assessments to support food safety decision making, this process includes significant uncertainties so that relevant decision making is frequently conservative and inflexible. Progression involves encoding into the models cellular processes at a molecular level, especially the details of the genetic and molecular machinery. This addition drives the connection between biological mechanisms and botulism risk assessment and hazard management strategies. This review brings together elements currently described in the literature that will be useful in building quantitative models of C. botulinum neurotoxin production. Subsequently, it outlines how the established form of modeling could be extended to include these new elements. Ultimately, this can offer further contributions to risk assessments to support food safety decision making.

Measurement of Coherent π

We report the first measurement of the flux-averaged cross section for charged current coherent π^{+} production on carbon for neutrino energies less than 1.5 GeV, and with a restriction on the final state phase space volume in the T2K near detector, ND280. Comparisons are made with predictions from the Rein-Sehgal coherent production model and the model by Alvarez-Ruso et al., the latter representing the first implementation of an instance of the new class of microscopic coherent models in a neutrino interaction Monte Carlo event generator. We observe a clear event excess above background, disagreeing with the null results reported by K2K and SciBooNE in a similar neutrino energy region. The measured flux-averaged cross sections are below those predicted by both the Rein-Sehgal and Alvarez-Ruso et al.

Measurement of Muon Antineutrino Oscillations with an Accelerator-Produced Off-Axis Beam.

T2K reports its first measurements of the parameters governing the disappearance of ν[over ¯]_{µ} in an off-axis beam due to flavor change induced by neutrino oscillations. The quasimonochromatic ν[over ¯]_{µ} beam, produced with a peak energy of 0.6 GeV at J-PARC, is observed at the far detector Super-Kamiokande, 295 km away, where the ν[over ¯]_{µ} survival probability is expected to be minimal. Using a data set corresponding to 4.01×10^{20} protons on target, 34 fully contained µ-like events were observed. The best-fit oscillation parameters are sin^{2}(θ[over ¯]_{23})=0.45 and |Δm[over ¯]_{32}^{2}|=2.51×10^{-3} eV^{2} with 68% confidence intervals of 0.38-0.64 and 2.26-2.80×10^{-3} eV^{2}, respectively. These results are in agreement with existing antineutrino parameter measurements and also with the ν_{µ} disappearance parameters measured by T2K.

Genomic architecture of human neuroanatomical diversity.

Human brain anatomy is strikingly diverse and highly inheritable: genetic factors may explain up to 80% of its variability. Prior studies have tried to detect genetic variants with a large effect on neuroanatomical diversity, but those currently identified account for <5% of the variance. Here, based on our analyses of neuroimaging and whole-genome genotyping data from 1765 subjects, we show that up to 54% of this heritability is captured by large numbers of single-nucleotide polymorphisms of small-effect spread throughout the genome, especially within genes and close regulatory regions. The genetic bases of neuroanatomical diversity appear to be relatively independent of those of body size (height), but shared with those of verbal intelligence scores. The study of this genomic architecture should help us better understand brain evolution and disease.

Single nucleotide polymorphism in the neuroplastin locus associates with cortical thickness and intellectual ability in adolescents.

Despite the recognition that cortical thickness is heritable and correlates with intellectual ability in children and adolescents, the genes contributing to individual differences in these traits remain unknown. We conducted a large-scale association study in 1583 adolescents to identify genes affecting cortical thickness. Single-nucleotide polymorphisms (SNPs; n=54,837) within genes whose expression changed between stages of growth and differentiation of a human neural stem cell line were selected for association analyses with average cortical thickness. We identified a variant, rs7171755, associating with thinner cortex in the left hemisphere (P=1.12 × 10(-)(7)), particularly in the frontal and temporal lobes. Localized effects of this SNP on cortical thickness differently affected verbal and nonverbal intellectual abilities. The rs7171755 polymorphism acted in cis to affect expression in the human brain of the synaptic cell adhesion glycoprotein-encoding gene NPTN. We also found that cortical thickness and NPTN expression were on average higher in the right hemisphere, suggesting that asymmetric NPTN expression may render the left hemisphere more sensitive to the effects of NPTN mutations, accounting for the lateralized effect of rs7171755 found in our study. Altogether, our findings support a potential role for regional synaptic dysfunctions in forms of intellectual deficits.

Resilience and corpus callosum microstructure in adolescence.

BACKGROUND: Resilience is the capacity of individuals to resist mental disorders despite exposure to stress. Little is known about its neural underpinnings. The putative variation of white-matter microstructure with resilience in adolescence, a critical period for brain maturation and onset of high-prevalence mental disorders, has not been assessed by diffusion tensor imaging (DTI). Lower fractional anisotropy (FA) though, has been reported in the corpus callosum (CC), the brain's largest white-matter structure, in psychiatric and stress-related conditions. We hypothesized that higher FA in the CC would characterize stress-resilient adolescents. METHOD: Three groups of adolescents recruited from the community were compared: resilient with low risk of mental disorder despite high exposure to lifetime stress (n = 55), at-risk of mental disorder exposed to the same level of stress (n = 68), and controls (n = 123). Personality was assessed by the NEO-Five Factor Inventory (NEO-FFI). Voxelwise statistics of DTI values in CC were obtained using tract-based spatial statistics. Regional projections were identified by probabilistic tractography. RESULTS: Higher FA values were detected in the anterior CC of resilient compared to both non-resilient and control adolescents. FA values varied according to resilience capacity. Seed regional changes in anterior CC projected onto anterior cingulate and frontal cortex. Neuroticism and three other NEO-FFI factor scores differentiated non-resilient participants from the other two groups. CONCLUSION: High FA was detected in resilient adolescents in an anterior CC region projecting to frontal areas subserving cognitive resources. Psychiatric risk was associated with personality characteristics. Resilience in adolescence may be related to white-matter microstructure.

White-matter microstructure and gray-matter volumes in adolescents with subthreshold bipolar symptoms.

Abnormalities in white-matter (WM) microstructure, as lower fractional anisotropy (FA), have been reported in adolescent-onset bipolar disorder and in youth at familial risk for bipolarity. We sought to determine whether healthy adolescents with subthreshold bipolar symptoms (SBP) would have early WM microstructural alterations and whether those alterations would be associated with differences in gray-matter (GM) volumes. Forty-two adolescents with three core manic symptoms and no psychiatric diagnosis, and 126 adolescents matched by age and sex, with no psychiatric diagnosis or symptoms, were identified after screening the IMAGEN database of 2223 young adolescents recruited from the general population. After image quality control, voxel-wise statistics were performed on the diffusion parameters using tract-based spatial statistics in 25 SBP adolescents and 77 controls, and on GM and WM images using voxel-based morphometry in 30 SBP adolescents and 106 controls. As compared with healthy controls, adolescents with SBP displayed lower FA values in a number of WM tracts, particularly in the corpus callosum, cingulum, bilateral superior and inferior longitudinal fasciculi, uncinate fasciculi and corticospinal tracts. Radial diffusivity was mainly higher in posterior parts of bilateral superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculi and right cingulum. As compared with controls, SBP adolescents had lower GM volume in the left anterior cingulate region. This is the first study to investigate WM microstructure and GM morphometric variations in adolescents with SBP. The widespread FA alterations in association and projection tracts, associated with GM changes in regions involved in mood disorders, suggest altered structural connectivity in those adolescents.

Dehydrative thiolation of allenols: indium vs gold catalysis.

Intermolecular additions of thiols to allenols via formal S(N)2' selectivity to produce functionalized dienes are described. Although this dehydrative reaction was initially developed using gold(I) catalysis, indium(III) proves to be a far superior catalyst in terms of selectivity and substrate scope.

Status and future of Quantitative Microbiological Risk Assessment in China.

Since the implementation of the Food Safety Law of the People's Republic of China in 2009 use of Quantitative Microbiological Risk Assessment (QMRA) has increased. QMRA is used to assess the risk posed to consumers by pathogenic bacteria which cause the majority of foodborne outbreaks in China. This review analyses the progress of QMRA research in China from 2000 to 2013 and discusses 3 possible improvements for the future. These improvements include planning and scoping to initiate QMRA, effectiveness of microbial risk assessment utility for risk management decision making, and application of QMRA to establish appropriate Food Safety Objectives.

Precise measurement of the neutrino mixing parameter θ23 from muon neutrino disappearance in an off-axis beam.

New data from the T2K neutrino oscillation experiment produce the most precise measurement of the neutrino mixing parameter θ23. Using an off-axis neutrino beam with a peak energy of 0.6 GeV and a data set corresponding to 6.57×10(20) protons on target, T2K has fit the energy-dependent νµ oscillation probability to determine oscillation parameters. The 68% confidence limit on sin(2)(θ23) is 0.514(-0.056)(+0.055) (0.511±0.055), assuming normal (inverted) mass hierarchy. The best-fit mass-squared splitting for normal hierarchy is Δm32(2)=(2.51±0.10)×10(-3) eV(2)/c(4) (inverted hierarchy: Δm13(2)=(2.48±0.10)×10(-3) eV(2)/c(4)). Adding a model of multinucleon interactions that affect neutrino energy reconstruction is found to produce only small biases in neutrino oscillation parameter extraction at current levels of statistical uncertainty.