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Despite increasing knowledge on the neuroimaging patterns of eating disorder (ED) symptoms in non-clinical populations, studies using whole-brain machine learning to identify connectome-based neuromarkers of ED symptomatology are absent. This study examined the association of connectivity within and between large-scale functional networks with specific symptomatic behaviors and cognitions using connectome-based predictive modeling (CPM).
CPM with ten-fold cross-validation was carried out to probe functional networks that were predictive of ED-associated symptomatology, including body image concerns, binge eating, and compensatory behaviors, within the discovery sample of 660 participants. The predictive ability of the identified networks was validated using an independent sample of 821 participants.
The connectivity predictive of body image concerns was identified within and between networks implicated in cognitive control (frontoparietal and medial frontal), reward sensitivity (subcortical), and visual perception (visual). Crucially, the set of connections in the positive network related to body image concerns identified in one sample was generalized to predict body image concerns in an independent sample, suggesting the replicability of this effect.
These findings point to the feasibility of using the functional connectome to predict ED symptomatology in the general population and provide the first evidence that functional interplay among distributed networks predicts body shape/weight concerns.
The relationship of a diet low in fiber with mortality has not been evaluated. This study aims to assess the burden of non-communicable chronic diseases (NCDs) attributable to a diet low in fiber globally from 1990 to 2019.
All data were from the Global Burden of Disease (GBD) Study 2019, in which the mortality, disability-adjusted life-years (DALYs), and years lived with disability (YLDs) were estimated with Bayesian geospatial regression using data at global, regional, and country level acquired from an extensively systematic review.
All data sourced from the GBD Study 2019.
All age groups for both sexes.
The age-standardized mortality rates (ASMRs) declined in most GBD regions; however, in Southern Sub-Saharan Africa, the ASMR increased from 4.07 (95% uncertainty interval (UI): [2.08, 6.34]) to 4.60 (95% UI: [2.59, 6.90]), and in Central Sub-Saharan Africa, the ASMR increased from 7.46 (95% UI: [3.64, 11.90]) to 9.34 (95% UI: [4.69, 15.25]). Uptrends were observed in the age-standardized YLDs rates attributable to a diet low in fiber in a number of GBD regions. The burden caused by diabetes mellitus increase in Central Asia, Southern Sub-Saharan Africa and Eastern Europe.
The burdens of disease attributable to a diet low in fiber in Southern Sub-Saharan Africa and Central Sub-Saharan Africa and the age-standardized YLDs rates in a number of GBD regions increased from 1990 to 2019. Therefore, greater efforts are needed to reduce the disease burden caused by a diet low in fiber.
We investigate the large-scale influence of numerical noises as tiny artificial stochastic disturbances on a sustained turbulence. Using two-dimensional (2-D) turbulent Rayleigh–Bénard convection (RBC) as an example, we solve numerically the Navier–Stokes equations, separately, by means of a traditional algorithm with double precision (denoted RKwD) and the so-called clean numerical simulation (CNS). The numerical simulation given by RKwD is a mixture of the ‘true’ physical solution and the ‘false’ numerical noises that are random and can be regarded as a kind of artificial stochastic disturbances; unfortunately, the ‘true’ physical solution is mostly at the same level as the ‘false’ numerical noises. By contrast, the CNS can greatly reduce the background numerical noise to any a required level so that the ‘false’ numerical noises are negligible compared with the ‘true’ physical solution, thus the CNS solution can be used as a ‘clean’ benchmark solution for comparison. It is found that the numerical noises as tiny artificial stochastic disturbances could indeed lead to large-scale deviations of simulations not only in spatio-temporal trajectories but also even in statistics. In particular, these numerical noises (as artificial stochastic disturbances) even lead to different types of flows. The shearing convection occurs for the RKwD simulations, and its corresponding flow field turns to a kind of zonal flow thereafter; however, the CNS benchmark solution always sustains the non-shearing vortical/roll-like convection during the whole process of simulation. Thus we provide rigorous evidence that numerical noises as a kind of small-scale artificial stochastic disturbances have quantitatively and qualitatively large-scale influences on a sustained turbulence, i.e. the 2-D turbulent RBC considered in this paper.
The association between dietary Cu intake and mortality risk remains uncertain. We aimed to investigate the relationship of dietary Cu intake with all-cause mortality among Chinese adults. A total of 17 310 participants from the China Health and Nutrition Survey, a national ongoing open cohort of Chinese participants, were included in the analysis. Dietary intake was measured by three consecutive 24-h dietary recalls in combination with a weighing inventory over the same 3 d. The average intakes of the 3-d dietary macronutrients and micronutrients were calculated. The study outcome was all-cause mortality. During a median follow-up of 9·0 years, 1324 (7·6 %) participants died. After adjusting for sex, age, BMI, ever alcohol drinking, ever smoking, education levels, occupations, urban or rural residents, systolic blood pressure, diastolic blood pressure and the intakes of fat, protein and carbohydrate, the association between dietary Cu intake and all-cause mortality followed a J-shape (Pfor nonlinearity = 0·047). When dietary Cu intake was assessed as quartiles, compared with those in the first quartile (<1·60 mg/d), the adjusted hazard ratios for all-cause mortality were 0·87 (95 % CI (0·71, 1·07)), 0·98 (95 % CI (0·79, 1·21)) and 1·49 (95 % CI (1·19, 1·86)), respectively, in participants in the second (1·60–<1·83 mg/d), third (1·83–<2·09 mg/d) and fourth (≥2·09 mg/d) quartiles. A series of subgroup analyses and sensitivity analyses showed similar results. Overall, our findings emphasised the importance of maintaining optimal dietary Cu intake levels for prevention of premature death.
Little is known regarding how the risk of suicide in refugees relates to their host country. Specifically, to what extent, inter-country differences in structural factors between the host countries may explain the association between refugee status and subsequent suicide is lacking in previous literature.
We aimed to investigate the risk of suicide among refugees in Sweden and Norway according to their sex, age, region/country of birth and duration of residence.
Each suicide case between the age of 18-64 years during 1998 and 2018 (17,572 and 9,443 cases in Sweden and Norway, respectively) was matched with up to 20 population-based controls, by sex and age. Multivariate-adjusted conditional logistic regression models yielding adjusted odds ratios (aORs) with 95% confidence intervals (95% CI) were used to test the association between refugee status and suicide.
The aORs for suicide in refugees in Sweden and Norway were 0.5 (95% CI: 0.5-0.6) and 0.3 (95% CI: 0.3-0.4), compared with the Swedish-born and Norwegian-born individuals, respectively. Stratification by region/country of birth showed similar statistically significant lower odds for most refugee groups in both host countries except for refugees from Eritrea (aOR 1.0, 95% CI: 0.7-1.6) in Sweden. The risk of suicide did not vary much across refugee groups by their duration of residence, sex and age.
The findings of almost similar suicide mortality advantages among refugees in two host countries may suggest that resiliency and culture/religion-bound attitudes could be more influential for suicide risk among refugees than other post-migration environmental and structural factors in the host country.
Psychiatric care following self-harm treatment is pivotal in patients´ life both in short- and long-terms.
To examine follow-up psychiatric care received by patients treated for deliberate self-harm (DSH), and to assess the influence of psychiatric referral and treatment attendance on risk for subsequent mortality.
Nationwide registries were interlinked to follow all DSH patients for data on personal socioeconomic status, clinical features of DSH, psychiatric treatment and cause of death. Data were analyzed with Logistic regression and cause-specific survival analysis.
The study identified 43153 patients involving 69569 DSH episodes. Of these patients 15.7% were referred or transferred to psychiatric services and 51.0% attended psychiatric treatment within subsequent 3 months. Evidently, prior psychiatric history and psychiatric comorbidities had strong influence on both referral and attendance to psychiatric healthcare, personal socioeconomic status also deviated the likelihoods. During the follow-up, 7041 patients died from suicide (n=911) or other causes (n=6130). While suicide risk was highly associated with male gender, middle age, and particularly, prior and coexisting psychopathologies, other cause mortality was strongly associated with old age and socioeconomic disadvantages. Meanwhile, a referral to psychiatric services was associated with suicide risk, and the risk was particularly high for patients who received the referral but did not attend psychiatric treatment. The observed effect was more pronounced during the early years, and in patients of young or middle age and those with a clear intent of self-harm.
The insightful findings highlight the importance of patients´ attendance and engagement in follow-up psychiatric care on risk for subsequent mortality.
Cryptosporidium spp. are important pathogens with some species causing diarrhoea in humans and animals. Sheep are one of the most common potential hosts for various Cryptosporidium spp. The prevalence of Cryptosporidium in sheep globally was evaluated from published information including molecular data via meta-analysis. In total, 126 datasets from 41 countries were included for final quantitative analysis. Sheep aged <3 months had a significantly higher prevalence (27.8%; 3284/11 938) than those at the age of 3–12 and >12 months. The prevalence of Cryptosporidium in sheep with diarrhoea of 35.4% (844/1915) was higher than in sheep that did not show diarrhoea (11.3%; 176/1691). Fourteen Cryptosporidium species/genotypes were detected in sheep globally. The proportion of subgenotype family XIIa of Cryptosporidium ubiquitum was 90.0% (216/240); the proportions of subgenotypes IIdA20G1 and IIaA15G2R1 of Cryptosporidium parvum were 15.4% (62/402) and 19.7% (79/402). The results indicate that C. parvum is the dominant species in Europe while Cryptosporidium xiaoi is the dominant species in Oceania, Asia and Africa and C. ubiquitum is the dominant species in North America and South America. Subgenotype family IIa of C. parvum is particularly widespread among sheep worldwide. The results highlight the role of sheep as a reservoir host for zoonotic cryptosporidia and the need for further study of prevalence, transmission and control of this pathogen in sheep.
As an integral ingredient of human sociality, prosocial behavior requires learning what acts can benefit or harm others. However, it remains unknown how individuals adjust prosocial learning to avoid punishment or to pursue reward. Given that arginine vasopressin (AVP) is a neuropeptide that has been involved in modulating various social behaviors in mammals, it could be a crucial neurochemical facilitator that supports prosocial learning.
In 50 placebo controls and 54 participants with AVP administration, we examined the modulation of AVP on the prosocial learning characterized by reward and punishment framework, as well as its underlying neurocomputational mechanisms combining computational modeling, event-related potentials and oscillations.
We found a self-bias that individuals learn to avoid punishment asymmetrically more severely than reward-seeking. Importantly, AVP increased behavioral performances and learning rates when making decisions to avoid losses for others and to obtain gains for self. These behavioral effects were underpinned by larger responses of stimulus-preceding negativity (SPN) to anticipation, as well as higher punishment-related feedback-related negativity (FRN) for prosocial learning and reward-related P300 for proself benefits, while FRN and P300 neural processes were integrated into theta (4–7 Hz) oscillation at the outcome evaluation stage.
These results suggest that AVP context-dependently up-regulates altruism for concerning others' losses and reward-seeking for self-oriented benefits. Our findings provide insight into the selectively modulatory roles of AVP in prosocial behaviors depending on learning contexts between proself reward-seeking and prosocial punishment-avoidance.
Family functioning is associated with anxiety and depression. Perinatal depression and anxiety are common and influence the well-being of women, partners and their offspring. However, little is known about differences in associations between family functioning and mood symptoms in women and their partners in early pregnancy.
Investigating differences in associations between family functioning and anxious and depressive symptoms in women and their partners in early pregnancy.
In total, 171 woman–partner pairs were enrolled. The Edinburgh Postnatal Depression Scale (EPDS), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-Item scale (GAD-7) and Family Assessment Device (FAD) were performed. Correlation analysis and multiple linear regression analysis were applied to investigate the associations.
In pregnant women, all the subscale scores on the FAD were correlated with total scores on the EPDS and GAD-7 (all P < 0.05), whereas only the Roles subscale showed a predicting effect in regression models (P < 0.01). In partners, all the subscale scores on the FAD were related to total scores on the PHQ-9 (all P < 0.05), whereas only the Problem Solving subscale showed a predicting effect (P = 0.029).
Our findings indicate that family functioning in the domain of roles is associated with anxious and depressive symptoms in pregnant women and functioning in the domain of problem solving is associated with depressive symptoms in partners. Clinicians should pay special attention to roles and problem solving when assessing mood symptoms in pregnant women and their partners. This study also provides a basis for family health education in early pregnancy.
In the simplest sense, reading acquisition is a process of learning how a writing system represents a spoken language. It requires conscious awareness of how the basic graphic symbol, the grapheme, represents a spoken unit. However, unlike language acquisition, which occurs naturally, rapidly, and automatically in most children, learning to read is a lifetime developmental process that requires effort, explicit instruction, and conscious awareness of the language structure (known as metalinguistic awareness). Many children fail to achieve full proficiency in reading, and some exhibit specific problems with reading, writing, and spelling despite adequate intelligence, motivation, and educational opportunity. This specific learning difficulty, known as developmental dyslexia, has varying incidence rates depending on the diagnostic criteria and the language examined. The divergent incidence rates, together with some findings suggesting that dyslexia has different behavioural and neural manifestations within and across cultures, has led to the question of whether the underlying causes of dyslexia differ across writing systems and whether it is possible to be dyslexic in one language and not dyslexic in another.
Persistent psychological distress associated with the coronavirus disease 2019 (COVID-19) pandemic has been well documented. This study aimed to identify pre-COVID brain functional connectome that predicts pandemic-related distress symptoms among young adults.
Baseline neuroimaging studies and assessment of general distress using the Depression, Anxiety and Stress Scale were performed with 100 healthy individuals prior to wide recognition of the health risks associated with the emergence of COVID-19. They were recontacted for the Impact of Event Scale-Revised and the Posttraumatic Stress Disorder Checklist in the period of community-level outbreaks, and for follow-up distress evaluation again 1 year later. We employed the network-based statistic approach to identify connectome that predicted the increase of distress based on 136-region-parcellation with assigned network membership. Predictive performance of connectome features and causal relations were examined by cross-validation and mediation analyses.
The connectome features that predicted emergence of distress after COVID contained 70 neural connections. Most within-network connections were located in the default mode network (DMN), and affective network-DMN and dorsal attention network-DMN links largely constituted between-network pairs. The hippocampus emerged as the most critical hub region. Predictive models of the connectome remained robust in cross-validation. Mediation analyses demonstrated that COVID-related posttraumatic stress partially explained the correlation of connectome to the development of general distress.
Brain functional connectome may fingerprint individuals with vulnerability to psychological distress associated with the COVID pandemic. Individuals with brain neuromarkers may benefit from the corresponding interventions to reduce the risk or severity of distress related to fear of COVID-related challenges.
The autonomous underwater vehicle (AUV) has a problem with feature loss when recognizing small targets underwater. At present, algorithms usually use multi-scale feature extraction to solve the problem, but this method increases the computational effort of the algorithm. In addition, low underwater light and turbid water result in incomplete information on target features. This paper proposes an enhanced dilated convolution framework (EHDC) for underwater blurred target recognition. Firstly, this paper extracts small target features through hybrid dilated convolution networks, increasing the perceptive field of the algorithm without increasing the computational power of the algorithm. Secondly, the proposed algorithm learns spatial semantic features through an adaptive correlation matrix and compensates for the missing features of the target. Finally, this paper fuses spatial semantic features and visual features for the recognition of small underwater blurred targets. Experiments show that the proposed method improves the recognition accuracy by 1.04% compared to existing methods when recognizing small underwater blurred targets.
The topological Langmuir-cyclotron wave (TLCW) is a recently identified topological surface excitation in magnetized plasmas. We show that TLCW originates from the topological phase transition at the Langmuir wave-cyclotron wave resonance. By isofrequency surface analysis and two- and three-dimensional time-dependent simulations, we demonstrate that the TLCW can propagate robustly along complex phase transition interfaces in a unidirectional manner and without scattering. Because of these desirable features, the TLCW could be explored as an effective mechanism to drive current and flow in magnetized plasmas. The analysis also establishes a close connection between the newly instituted topological phase classification of plasmas and the classical Clemmow-Mullaly-Allis (CMA) diagram of plasma waves.
Meeting individuals' social care needs is a core element of UK social policy. However, the conceptualisation and operationalisation of ‘unmet need’ remain a challenge. This paper advances our understanding by incorporating a temporal dimension into the conceptual framework on unmet need to investigate the dynamics of met and unmet need for social care over time. Using data from Waves 8 and 9 of the English Longitudinal Study of Ageing, this paper examines five possible trajectories among individuals with a social care need for bathing or dressing at baseline: (a) no longer having such a need; (b) having continued needs met; (c) delayed needs met; (d) newly arisen unmet needs; and (e) repeated unmet needs. The results indicate that amongst those with need at baseline, unmet need has decreased over time – indicating that some needs for social care may be fulfilled with a delay. However, a significant proportion of older people experienced repeated unmet needs, particularly those who were younger, with no spouse or civil partner, and those whose activities of daily living index scores worsened over time. Understanding the dynamics of unmet need can support policy makers in better ensuring that those facing an elevated risk of repeated unmet need over time do not fall through the social care safety net.
This article reviews selected research on foreign language teaching and learning published in local, high-impact journals in China over the past ten years (2012–2021). A bibliometric analysis was conducted to elicit the most frequently researched topics in the field, which were grouped into four categories, that is, language learning and use, language pedagogy, language learners and teachers, and Teaching English as a Foreign Language approaches/theories, and a number of sub-categories. This was then followed by an in-depth and critical review of 71 studies corresponding to those categories and sub-categories. The review concluded with a discussion of inadequacies and recommendations for future research. It is hoped that a review on the experience of Chinese practitioners and researchers’ efforts to promote foreign language education may contribute to language teaching research and development in the international field.
This report describes a cluster of patients infected by Serratia marcescens in a metropolitan neonatal intensive care unit (NICU) and a package of infection control interventions that enabled rapid, effective termination of the outbreak.
Cross-sectional analytical study using whole-genome sequencing (WGS) for phylogenetic cluster analysis and identification of virulence and resistance genes.
NICU in a metropolitan tertiary-care hospital in Sydney, Australia.
All neonates admitted to the level 2 and level 3 neonatal unit.
Active inpatient and environmental screening for Serratia marcescens isolates with WGS analysis for identification of resistance genes as well as cluster relatedness between isolates. Planning and implementation of a targeted, multifaceted infection control intervention.
The cluster of 10 neonates colonized or infected with Serratia marcescens was identified in a metropolitan NICU. Two initial cases involved devastating intracranial infections with brain abscesses, highlighting the virulence of this organism. A targeted and comprehensive infection control intervention guided by WGS findings enabled termination of this outbreak within 15 days of onset. WGS examination demonstrated phylogenetic linkage across the cluster, and genomic unrelatedness of later strains identified in the neonatal unit and elsewhere.
A comprehensive, multipronged, infection control package incorporating close stakeholder engagement, frequent microbiological patient screening, environmental screening, enhanced cleaning, optimization of hand hygiene and healthcare worker education was paramount to the prompt control of Serratia marcescens transmission in this neonatal outbreak. WGS was instrumental in establishing relatedness between isolates and identification of possible transmission pathways in an outbreak setting.