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Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient.
Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology.
Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions.
These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the ‘dysconnectivity hypothesis’ of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.
This paper integrates seemingly disjoint studies on consumer behavior in micro and macroanalyses via an intertemporal two-stage budgeting procedure with durable goods and liquidity constraints. The model specifies an indirect utility function as a function of nondurable consumption, commodity (nondurables) prices, and durables stock, and derives the demand functions for nondurable goods. A demand function for durable goods is derived in an adjustment cost framework. The consumption growth equation accounts for relative price effects with precautionary saving, durables stock, and liquidity constraints. The stochastic discount factor is approximated by a time-varying linear function of nondurable consumption growth, commodity price growth, durables stock growth, and disposable income growth. The demand functions for six nondurable goods and services are jointly estimated with the Euler equations for bonds, stocks, and durable goods with allowance for liquidity constraints, using US data. Estimation provides new findings for intertemporal consumption and a multifactor consumption-based capital asset pricing model.
The concept of electoral competition plays a central role in many subfields of political science, but no consensus exists on how to measure it. One key challenge is how to conceptualize and measure electoral competitiveness at the district level across alternative electoral systems. Recent efforts to meet this challenge have introduced general measures of competitiveness which rest on explicit calculations about how votes translate into seats, but also implicit assumptions about how effort maps into votes (and how costly effort is). We investigate how assumptions about the effort-to-votes mapping affect the units in which competitiveness is best measured, arguing in favor of vote-share-denominated measures and against vote-share-per-seat measures. Whether elections under multimember proportional representation systems are judged more or less competitive than single-member plurality or runoff elections depends directly on the units in which competitiveness is assessed (and hence on assumptions about how effort maps into votes).
Whereas genetic susceptibility increases the risk for major depressive disorder (MDD), non-genetic protective factors may mitigate this risk. In a large-scale prospective study of US Army soldiers, we examined whether trait resilience and/or unit cohesion could protect against the onset of MDD following combat deployment, even in soldiers at high polygenic risk.
Data were analyzed from 3079 soldiers of European ancestry assessed before and after their deployment to Afghanistan. Incident MDD was defined as no MDD episode at pre-deployment, followed by a MDD episode following deployment. Polygenic risk scores were constructed from a large-scale genome-wide association study of major depression. We first examined the main effects of the MDD PRS and each protective factor on incident MDD. We then tested the effects of each protective factor on incident MDD across strata of polygenic risk.
Polygenic risk showed a dose–response relationship to depression, such that soldiers at high polygenic risk had greatest odds for incident MDD. Both unit cohesion and trait resilience were prospectively associated with reduced risk for incident MDD. Notably, the protective effect of unit cohesion persisted even in soldiers at highest polygenic risk.
Polygenic risk was associated with new-onset MDD in deployed soldiers. However, unit cohesion – an index of perceived support and morale – was protective against incident MDD even among those at highest genetic risk, and may represent a potent target for promoting resilience in vulnerable soldiers. Findings illustrate the value of combining genomic and environmental data in a prospective design to identify robust protective factors for mental health.
The authors developed a practical and clinically useful model to predict the risk of psychosis that utilizes clinical characteristics empirically demonstrated to be strong predictors of conversion to psychosis in clinical high-risk (CHR) individuals. The model is based upon the Structured Interview for Psychosis Risk Syndromes (SIPS) and accompanying clinical interview, and yields scores indicating one's risk of conversion.
Baseline data, including demographic and clinical characteristics measured by the SIPS, were obtained on 199 CHR individuals seeking evaluation in the early detection and intervention for mental disorders program at the New York State Psychiatric Institute at Columbia University Medical Center. Each patient was followed for up to 2 years or until they developed a syndromal DSM-4 disorder. A LASSO logistic fitting procedure was used to construct a model for conversion specifically to a psychotic disorder.
At 2 years, 64 patients (32.2%) converted to a psychotic disorder. The top five variables with relatively large standardized effect sizes included SIPS subscales of visual perceptual abnormalities, dysphoric mood, unusual thought content, disorganized communication, and violent ideation. The concordance index (c-index) was 0.73, indicating a moderately strong ability to discriminate between converters and non-converters.
The prediction model performed well in classifying converters and non-converters and revealed SIPS measures that are relatively strong predictors of conversion, comparable with the risk calculator published by NAPLS (c-index = 0.71), but requiring only a structured clinical interview. Future work will seek to externally validate the model and enhance its performance with the incorporation of relevant biomarkers.
The Lyman alpha emission from Comet Bennett (1970II) was measured near perihelion (March 1970) by the University of Colorado ultraviolet photometer experiment on OGO-5 The spectrometer field of view of about 3° crossed the cometary hydrogen coma four times. The hydrogen coma was observed to extend more than 30 x 106 km in the antisolar direction.
A model for the hydrogen density was developed which took the actual cometary motion and the gradients of the forces of gravitation and radiation pressure into account Exact trajectories of atoms in the orbital plane representing the column densities perpendicular to the plane were calculated. The variation of the hydrogen lifetime along the trajectory as well as the solar Lα profile were considered.
Texture-engineered ceramics enable access to a vast array of novel texture-property relations leading to property values ranging between those of single crystals and isotropic bulk ceramics. Recently developed templated grain growth and magnetic alignment texturing methods yield high quality crystallographic texture, and thus significant advances in achievable texture-engineered properties in magnetic, piezoelectric, electronic, optical, thermoelectric, and structural ceramics. In this paper, we outline the fundamental basis for these texture-engineered properties and review recent contributions to the field of texture-engineered ceramics with an update on the properties of textured lead-free and lead-based piezoelectrics. We propose that further property improvements can be realized through development of processes that improve crystallographic alignment of the grain structure, create biaxial texture, and explore a wider array of crystallographic orientations. There is a critical need to model the physics of texture-engineered ceramics, and more comprehensively characterize texture, thus enabling testing of texture orientation-property relations and materials performance. We believe that in situ measurements of texture evolution can lead to a more fundamental and comprehensive understanding of the mechanisms of texture development.
Driving in persons with dementia poses risks that must be counterbalanced with the importance of the care for autonomy and mobility. Physicians often find substantial challenges in the assessment and reporting of driving safety for persons with dementia. This paper describes a driving in dementia decision tool (DD-DT) developed to aid physicians in deciding when to report older drivers with either mild dementia or mild cognitive impairment to local transportation administrators.
A multi-faceted, computerized decision support tool was developed, using a systematic literature and guideline review, expert opinion from an earlier Delphi study, as well as qualitative interviews and focus groups with physicians, caregivers of former drivers with dementia, and transportation administrators. The tool integrates inputs from the physician-user about the patient's clinical and driving history as well as cognitive findings, and it produces a recommendation for reporting to transportation administrators. This recommendation is translated into a customized reporting form for the transportation authority, if applicable, and additional resources are provided for the patient and caregiver.
An innovative approach was needed to develop the DD-DT. The literature and guideline review confirmed the algorithm derived from the earlier Delphi study, and barriers identified in the qualitative research were incorporated into the design of the tool.
To detail the activities of the Veterans Health Administration (VHA) Antimicrobial Stewardship Initiative and evaluate outcomes of the program.
The VHA is a large integrated healthcare system serving approximately 6 million individuals annually at more than 140 medical facilities.
Utilization of nationally developed resources, proportional distribution of antibiotics, changes in stewardship practices and patient safety measures were reported. In addition, inpatient antimicrobial use was evaluated before and after implementation of national stewardship activities.
Nationally developed stewardship resources were well utilized, and many stewardship practices significantly increased, including development of written stewardship policies at 92% of facilities by 2015 (P<.05). While the proportional distribution of antibiotics did not change, inpatient antibiotic use significantly decreased after VHA Antimicrobial Stewardship Initiative activities began (P<.0001). A 12% decrease in antibiotic use was noted overall. The VHA has also noted significantly declining use of antimicrobials prescribed for resistant Gram-negative organisms, including carbapenems, as well as declining hospital readmission and mortality rates. Concurrently, the VHA reported decreasing rates of Clostridium difficile infection.
The VHA National Antimicrobial Stewardship Initiative includes continuing education, disease-specific guidelines, and development of example policies in addition to other highly utilized resources. While no specific ideal level of antimicrobial utilization has been established, the VHA has shown that improving antimicrobial usage in a large healthcare system may be achieved through national guidance and resources with local implementation of antimicrobial stewardship programs.
Late Neogene Sirius Group strata from Tillite Spur and Quartz Hills in the Reedy Glacier area, Antarctica, demonstrate the variability in Sirius Group facies and contrasts Sirius Group strata deposited at high and low paleo-elevation, respectively. The Tillite Spur and Quartz Hills Formations (Pliocene) are formally defined here.The Tillite Spur Formation type section crops out on the edge of the Wisconsin Plateau overlooking Tillite Spur. It comprises 32m of alternating coarse gray conglomerate and muddy olive-brown diamictites. The Quartz Hills Formation type section crops out above the western margin of Reedy Glacier in a pre-existing cirque towards the southern end of the Quartz Hills. It comprises c.100m of alternating massive diamictites and rhythmically interbedded sandstone and laminated mudstones which were deposited close to sea level and subsequently rapidly uplifted (>500 m Myr−1) to their present elevation at c. 1500 m. Three orders of paleoclimatic variability are recorded in the Sirius Group strata from Reedy Valley: (1) recycled marine microfloras in glacial diamictites indicate intervals of marine incursion into the Antarctic cratonic interior co-occurring with reductions in the East Antarctic ice sheet; (2) an advancing and retreating paleo-Reedy Glacier deposited a glacial/interglacial sequence alternating on a 10-100 kyr scale; 3) Centimeter and millimeter stratification in strata of the Quartz Hills Formation record annual kyr scale variability.
This study compared the longer-term effects of a very low-carbohydrate, high-fat diet with a high-carbohydrate, low-fat diet on cognitive performance in individuals with type 2 diabetes (T2D). In total, 115 obese adults with T2D (sixty-six males, BMI: 34·6 (sd 4·3) kg/m2, age: 58 (sd 7) years, HbA1c: 7·3 (sd 1·1) %, diabetes duration: 8 (sd 6) years) were randomised to consume either an energy-restricted, very low-carbohydrate, low-saturated-fat (LC) diet or an energy-matched high unrefined carbohydrate, low-fat (HC) diet with supervised aerobic/resistance exercise (60 min, 3 d/week) for 52 weeks. Body weight, HbA1c and cognitive performance assessing perceptual speed, reasoning speed, reasoning ability, working memory, verbal fluency, processing speed, short-term memory, inhibition and memory scanning speed were assessed before and after intervention. No differences in the changes in cognitive test performance scores between the diet groups were observed for any of the cognitive function outcomes assessed (P≥0·24 time×diet). Percentage reduction in body weight correlated with improvements with perceptual speed performance. In obese adults with T2D, both LC and HC weight-loss diets combined with exercise training had similar effects on cognitive performance. This suggests that an LC diet integrated within a lifestyle modification programme can be used as a strategy for weight and diabetes management without the concern of negatively affecting cognitive function.
Dietary mycoprotein decreases energy intake in lean individuals. The effects in overweight individuals are unclear, and the mechanisms remain to be elucidated. This study aimed to investigate the effect of mycoprotein on energy intake, appetite regulation, and the metabolic phenotype in overweight and obese volunteers. In two randomised-controlled trials, fifty-five volunteers (age: 31 (95 % CI 27, 35) years), BMI: 28·0 (95 % CI 27·3, 28·7) kg/m2) consumed a test meal containing low (44 g), medium (88 g) or high (132 g) mycoprotein or isoenergetic chicken meals. Visual analogue scales and blood samples were collected to measure appetite, glucose, insulin, peptide tyrosine-tyrosine (PYY) and glucagon-like peptide-1 (GLP-1). Ad libitum energy intake was assessed after 3 h in part A (n 36). Gastric emptying by the paracetamol method, resting energy expenditure and substrate oxidation were recorded in part B (n 14). Metabonomics was used to compare plasma and urine samples in response to the test meals. Mycoprotein reduced energy intake by 10 % (280 kJ (67 kcal)) compared with chicken at the high content (P=0·009). All mycoprotein meals reduced insulin concentrations compared with chicken (incremental AUClow (IAUClow): −8 %, IAUCmedium: −12 %, IAUChigh: −21 %, P=0·004). There was no significant difference in glucose, PYY, GLP-1, gastric emptying rate and energy expenditure. Following chicken intake, paracetamol-glucuronide was positively associated with fullness. After mycoprotein, creatinine and the deamination product of isoleucine, α-keto-β-methyl-N-valerate, were inversely related to fullness, whereas the ketone body, β-hydroxybutyrate, was positively associated. In conclusion, mycoprotein reduces energy intake and insulin release in overweight volunteers. The mechanism does not involve changes in PYY and GLP-1. The metabonomics analysis may bring new understanding to the appetite regulatory properties of food.
We present our earlier measurement of the coronal fields above a sunspot in the active region, NOAA #4741, which was obtained using microwave spectroscopy from the Owens Valley Radio Observatory (OVRO) in a form that allows comparison with theoretical models. Our empirical results for the coronal fields are compared with several theoretical models in order to understand the magnetic structure of a static sunspot. It is found that the presence of transverse pressure gradients should be considered to get a satisfactory fit.