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We here present a comparison of methods for the pretreatment of a batch of tree rings for high-precision measurement of radiocarbon at the Aarhus AMS Centre (AARAMS), Aarhus University, Denmark. The aim was to develop an efficient and high-throughput method able to pretreat ca. 50 samples at a time. We tested two methods for extracting α-cellulose from wood to find the most optimal for our use. One method used acetic acid, the other used HCl acid for the delignification. The testing was conducted on background 14C samples, in order to assess the effect of the different pretreatment methods on low-activity samples. Furthermore, the extracted wood and cellulose fractions were analyzed using Fourier transform infrared (FTIR) spectroscopy, which showed a successful extraction of α-cellulose from the samples. Cellulose samples were pretreated at AARAMS, and the graphitization and radiocarbon analysis of these samples were done at both AARAMS and the radiocarbon dating laboratory at Lund University to compare the graphitization and AMS machine performance. No significant offset was found between the two sets of measurements. Based on these tests, the pretreatment of tree rings for high-precision radiocarbon analysis at AARAMS will henceforth use HCI for the delignification.
Radiocarbon (14C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.
Brain imaging studies have shown altered amygdala activity during emotion processing in children and adolescents with oppositional defiant disorder (ODD) and conduct disorder (CD) compared to typically developing children and adolescents (TD). Here we aimed to assess whether aggression-related subtypes (reactive and proactive aggression) and callous-unemotional (CU) traits predicted variation in amygdala activity and skin conductance (SC) response during emotion processing.
We included 177 participants (n = 108 cases with disruptive behaviour and/or ODD/CD and n = 69 TD), aged 8–18 years, across nine sites in Europe, as part of the EU Aggressotype and MATRICS projects. All participants performed an emotional face-matching functional magnetic resonance imaging task.
Differences between cases and TD in affective processing, as well as specificity of activation patterns for aggression subtypes and CU traits, were assessed. Simultaneous SC recordings were acquired in a subsample (n = 63). Cases compared to TDs showed higher amygdala activity in response to negative faces (fearful and angry) v. shapes. Subtyping cases according to aggression-related subtypes did not significantly influence on amygdala activity; while stratification based on CU traits was more sensitive and revealed decreased amygdala activity in the high CU group. SC responses were significantly lower in cases and negatively correlated with CU traits, reactive and proactive aggression.
Our results showed differences in amygdala activity and SC responses to emotional faces between cases with ODD/CD and TD, while CU traits moderate both central (amygdala) and peripheral (SC) responses. Our insights regarding subtypes and trait-specific aggression could be used for improved diagnostics and personalized treatment.
The model of PGE describes the emergence of new systems based on reference by the activities carryover, embodiment and principle variation - qualitatively different manifestations of a transfer process. We investigate indicators which constitute these different manifestations measurably for different types of systems. We propose generalized variation operators to describe system development with respect to different product elements and system types. We use case studies from automotive, production systems and simulation models.
We sought to explore whether obstetric complications (OCs) are more likely to occur in the presence of familial/genetic susceptibility for schizophrenia or whether they themselves represent an independent environmental risk factor for schizophrenia.
The presence of OCs was assessed through maternal interview on 216 subjects, comprising 36 patients with schizophrenia from multiply affected families, 38 of their unaffected siblings, 31 schizophrenic patients with no family history of psychosis, 51 of their unaffected siblings and 60 normal comparison subjects. We examined the familiality of OCs and whether OCs were commoner in the patient and sibling groups than in the control group.
OCs tended to cluster within families, especially in multiply affected families. Patients with schizophrenia, especially those from multiply affected families, had a significantly higher rate of OCs compared to normal comparison subjects, but there was no evidence for an elevated rate of OCs in unaffected siblings.
Our data provides little evidence for a link between OCs and genetic susceptibility to schizophrenia. If high rates of OCs are related to schizophrenia genes, this relationship is weak and will only be detected by very large sample sizes.
Neuropsychological deficits are considered endophenotypes for schizophrenia, because they are not only found in patients but also in many of their unaffected relatives, albeit in attenuated form. It is not yet clear which of these deficits in relatives are related to genetic or to environmental causes. We tested effects of inferred genetic liability for schizophrenia on neurocognitive variables to address this problem.
Twenty-eight patients with schizophrenia, 129 non-affected biological parents and 143 matched controls were assessed with an extensive neuropsychological test battery including tests of attention, memory, executive functioning and motor soft signs. Twenty-two parents had an ancestral history of schizophrenia and therefore were hypothesized to be more likely than their spouses without such a history (n = 17) to carry a genetic risk for schizophrenia.
Unaffected parents of schizophrenic patients showed significant deficits in a wide array of neuropsychological tasks and task domains. However, comparison of more likely and less likely carriers of illness-related genes showed specifically attentional and executive functioning, but not memory, to vary with degree of inferred genetic loading.
Attentional and executive (frontal) impairments vary with genetic loading for schizophrenia and can be considered true endophenotypes for this disorder. Consequently, these functions are particularly suited to evaluate the functional impact of candidate genes for schizophrenia in future studies.
The consequences of Childhood trauma (CT) become increasingly apparent. The available data suggest that (1) CT is related to persisting alterations of HPA activity, (2) CT is related to psychopathology in patients with substance use disorders (SUD), and (3) alterations of HPA activity are related to craving and psychopathology. However, none of the existing studies have tried to integrate these different perspectives.
We assessed anxiety (STAI), depression (BDI) and craving (OCDS-D) in a consecutive sample of 42 patients with alcohol dependence (37% female, 63% male) on day 1 (t1) and day 14 (t2) after their admission to a detoxification unit. Morning plasma levels of cortisol and ACTH were assessed and a standard dexamethasone test (DST) was performed (t2). Finally, the Childhood Trauma Questionnaire was administered.
At t1, cortisol levels correlated significantly with anxiety (r=.34*) and sexual abuse (r=.38*). An inverse relationship was found between ACTH levels and both, emotional abuse and emotional neglect (t1: r=-.33*, r=-.39*; t2: r=-.32*, r=-.51**). This relationship persisted when controlling for depression. Craving was related to anxiety and depression (t1: r=.53**, r=.60**; t2: r=.39*, r=.35*), but not to cortisol or ACTH levels. No relationships existed between CT and the DST outcome.
Our results give first evidence that CT is related to changes of the HPA activity in SUD patients, but they could not be further clarified by the DST. Psychopathology was related to both, early trauma and craving. Future studies should try to further examine these complex relationships.
Prolactin (PRL) data from adolescents treated with olanzapine are presented.
Data from 454 adolescents (13-18, mean=15.9 yrs) with schizophrenia or bipolar mania were pooled from 4 olanzapine (2.5-20.0mg/day) studies (4-32 weeks; 2 double-blind, placebo-controlled studies [combined for acute phase endpoint PRL levels] with open-label extensions; 2 open-label studies). Age- and sex-specific Covance reference ranges defined normal PRL; categorical increases were based on multiples of the upper limit of normal (ULN). Baseline-to-endpoint PRL changes in adolescents were compared with data pooled from 84 olanzapine clinical trials in adults with schizophrenia or bipolar disorder.
Olanzapine-treated adolescents had mean PRL increases at both the acute (11.4μg/L) and open-label endpoints (4.7μg/L). Of those patients with normal PRL levels at baseline (N=311), high PRL occurred in 54.7% at anytime; 32.2% at endpoint. The percentage of patients in which PRL levels shifted from normal-to-abnormal was smaller at endpoint than at anytime during treatment; 26.7% shifted to a higher category. Among patients with normal baseline PRL, 32.7% remained <=1X ULN; 32.3% increased to 1¬<=2X; 6.0%, >2-<=3X; and 1.2%, >3X at anytime; 4.6% had at >=1 potentially PRL-related adverse event. Adolescents had significantly higher mean changes at endpoint (p=.004), and a greater incidence of high PRL levels at anytime during olanzapine treatment (p<.001) versus adults.
Incidence of high PRL was significantly higher, and mean increases in PRL were significantly greater in adolescents versus adults. Mean increases and high PRL incidence were lower at the open-label compared with the acute phase endpoint.
The changes in metabolic parameters in olanzapine-treated adolescents were examined.
Data from 454 adolescents (13–18, mean=15.9 years) with schizophrenia or bipolar I disorder were pooled from 4 olanzapine (2.5–20.0mg/day) studies (4–32 weeks). Changes in metabolic parameters in adolescents were compared with those of olanzapine-treated adults (pooled from 84 clinical trials); changes in weight and BMI were compared with US age- and sex-adjusted standardized growth curves.
Olanzapine-treated adolescents had significant increases from baseline-to-endpoint in fasting glucose (p=.021); total cholesterol, LDL, and triglycerides (p<.001); and significant decreases in HDL (p<.001). Significantly more adolescents gained >=7% of their baseline weight versus adults (65.1% vs. 35.6%, p<.001); mean change from baseline-to-endpoint in weight was significantly greater in adolescents (7.0 vs. 3.3kg, p<.001). Adolescents had significantly lower mean changes from baseline-to-endpoint in fasting glucose (0.3 vs. 0.1mmol/L, p=.002) and triglycerides (0.3 vs. 0.2mmol/L, p=.007) versus adults. Significantly more adults experienced treatment-emergent normal-to-high changes at anytime in fasting glucose (4.8% vs. 1.2%, p=.033), total cholesterol (6.9% vs. 1.1%, p=.001), LDL (5.8% vs. 1.5%, p=.014), and triglycerides (25.7% vs. 17.4%, p=.030). Compared with standardized growth curves, olanzapine-treated adolescents had greater increases from baseline-to-endpoint in weight (1.0 vs. 7.1kg, p<.001), height (0.5 vs. 0.7cm, p<.001), and BMI (0.2 vs. 2.2kg/m2, p<.001).
Olanzapine-treated adolescents may gain significantly more weight compared with adults, but may have smaller changes in other metabolic parameters. Clinicians may want to consider both efficacy and changes in metabolic parameters when selecting treatment options for individual adolescent patients.
Smoking-behaviour is influenced by environmental and genetic risk factors. Established epidemiological risk factors include early age at onset (AaO), depression, positive family history (FH+) of depression/alcohol-dependence, low education, older birth cohort, and male gender. Genomewide-association-studies (GWAS) have identified genetic risk variants for smoking-behaviour. In the present study we investigated correlations between these epidemiological and genetic risk factors and smoking-behaviour in a large population-based German sample. Genetic risk was defined in terms of a polygenic score – the accumulated effect of seven independent genetic risk markers for smoking-behaviour identified through GWAS.
The sample comprised 1736 individuals (815 males, 921 females). Dependent variables were: smoking-duration, nicotine-dependence, cigarettes–per-day, ever-smoking, and smoking-cessation. The effect of the epidemiological risk factors, the polygenic risk score, and their combined effect on the smoking-behaviours was tested via linear or logistic regression analyses.
The following associations were detected: AaO and birth cohort with smoking-duration (p=0.004; p<0.001); AaO, education and FH+ depression with nicotine-dependence (p=0.002; p=0.092); sex and AaO with cigarettes–per-day (p=0.020; p<0.001); FH+ alcohol dependence with eversmoking (p=0.049); and birth cohort and education with smoking-cessation (p=0.001; p=0.029). The polygenic risk score showed a trend towards association with nicotine-dependence (p=0.113) and cigarettes–per-day (p=0.109). In the combined analyses, the polygenic risk score improved the regression model for nicotine-dependence, cigarettes–per-day, and smoking-cessation.
The addition of GWAS information concerning genetic risk factors explained an increased fraction of the smoking behaviours nicotine dependence, CPD, and smoking cessation. Future studies are warranted to elucidate the biological correlates of these genetic risk factors.
Self-reported activity restriction is an established correlate of depression in dementia caregivers (dCGs). It is plausible that the daily distribution of objectively measured activity is also altered in dCGs with depression symptoms; if so, such activity characteristics could provide a passively measurable marker of depression or specific times to target preventive interventions. We therefore investigated how levels of activity throughout the day differed in dCGs with and without depression symptoms, then tested whether any such differences predicted changes in symptoms 6 months later.
Design, setting, participants, and measurements:
We examined 56 dCGs (mean age = 71, standard deviation (SD) = 6.7; 68% female) and used clustering to identify subgroups which had distinct depression symptom levels, leveraging baseline Center for Epidemiologic Studies of Depression Scale–Revised Edition and Patient Health Questionnaire-9 (PHQ-9) measures, as well as a PHQ-9 score from 6 months later. Using wrist activity (mean recording length = 12.9 days, minimum = 6 days), we calculated average hourly activity levels and then assessed when activity levels relate to depression symptoms and changes in symptoms 6 months later.
Clustering identified subgroups characterized by: (1) no/minimal symptoms (36%) and (2) depression symptoms (64%). After multiple comparison correction, the group of dCGs with depression symptoms was less active from 8 to 10 AM (Cohen’s d ≤ −0.9). These morning activity levels predicted the degree of symptom change on the PHQ-9 6 months later (per SD unit β = −0.8, 95% confidence interval: −1.6, −0.1, p = 0.03) independent of self-reported activity restriction and other key factors.
These novel findings suggest that morning activity may protect dCGs from depression symptoms. Future studies should test whether helping dCGs get active in the morning influences the other features of depression in this population (i.e. insomnia, intrusive thoughts, and perceived activity restriction).
The thymus undergoes a critical period of growth and development early in gestation and, by mid-gestation, immature thymocytes are subject to positive and negative selection. Exposure to undernutrition during these periods may permanently affect phenotype. We measured thymulin concentrations, as a proxy for thymic size and function, in children (n = 290; aged 9–13 years) born to participants in a cluster-randomized trial of maternal vitamin A or β-carotene supplementation in rural Nepal (1994–1997). The geometric mean (95% confidence interval) thymulin concentration was 1.37 ng/ml (1.27, 1.47). A multivariate model of early-life exposures revealed a positive association with gestational age at delivery (β = 0.02; P = 0.05) and higher concentrations among children born to β-carotene-supplemented mothers (β = 0.19; P < 0.05). At ∼9–12 years of age, thymulin was positively associated with all anthropometric measures, with height retained in our multivariate model (β = 0.02; P < 0.001). There was significant seasonal variation: concentrations tended to be lower pre-monsoon (β = −0.13; P = 0.15), during the monsoon (β = −0.22; P = 0.04), and pre-harvest (β = −0.34; P = 0.01), relative to the post-harvest season. All early-life associations, except supplementation, were mediated in part by nutritional status at follow-up. Our findings underscore the known sensitivity of the thymus to nutrition, including potentially lasting effects of early nutritional exposures. The relevance of these findings to later disease risk remains to be explored, particularly given the role of thymulin in the neuroendocrine regulation of inflammation.
Maternal systemic inflammation during pregnancy may restrict embryo−fetal growth, but the extent of this effect remains poorly established in undernourished populations. In a cohort of 653 maternal−newborn dyads participating in a multi-armed, micronutrient supplementation trial in southern Nepal, we investigated associations between maternal inflammation, assessed by serum α1-acid glycoprotein and C-reactive protein, in the first and third trimesters of pregnancy, and newborn weight, length and head and chest circumferences. Median (IQR) maternal concentrations in α1-acid glycoprotein and C-reactive protein in the first and third trimesters were 0.65 (0.53–0.76) and 0.40 (0.33–0.50) g/l, and 0.56 (0.25–1.54) and 1.07 (0.43–2.32) mg/l, respectively. α1-acid glycoprotein was inversely associated with birth size: weight, length, head circumference and chest circumference were lower by 116 g (P = 2.3 × 10−6), and 0.45 (P = 3.1 × 10−5), 0.18 (P = 0.0191) and 0.48 (P = 1.7 × 10−7) cm, respectively, per 50% increase in α1-acid glycoprotein averaged across both trimesters. Adjustment for maternal age, parity, gestational age, nutritional and socio-economic status and daily micronutrient supplementation failed to alter any association. Serum C-reactive protein concentration was largely unassociated with newborn size. In rural Nepal, birth size was inversely associated with low-grade, chronic inflammation during pregnancy as indicated by serum α1-acid glycoprotein.
Gerrit J. Gonschorek, PhD candidate at the Institute of Economics, Department of International Economic Policy, University of Freiburg, Germany.,
Günther G. Schulze, Professor of Economics at the Institute of Economics, University of Freiburg, Germany; and Adjunct Professor at the Arndt- Corden Department of Economics, Crawford School of Public Policy, ANU College of Asia and the Pacific, Australian National University, Canberra.
In 2001, Indonesia embarked on a far-reaching decentralization reform that devolved core responsibilities such as health, primary and secondary education and infrastructure to the districts. While the centre retained authority over foreign affairs, defence, law enforcement, justice, fiscal and monetary policy, and religion, control of all other functions was transferred to the regions — at least in principle (Sjahrir 2016). This implied a huge shift of expenditure from the centre to the regions (districts and provinces), which now spend around a third of the consolidated state budget. Yet, fiscal decentralization, which was accompanied by political and administrative decentralization, has remained largely one-sided. While local governments have authority over their spending, they rely heavily on transfers from the centre to finance their expenditure (Schulze and Sjahrir 2014). This particularly concerns districts, which received only 10–16 per cent of their revenue from own sources (tax and non-tax) between 2011 and 2016. Transfers to local governments accounted for around 30 per cent of central expenditure in recent years (Figure 4.1), making the design of the intergovernmental transfer system crucial for the success of the decentralization reform.
From a normative perspective, intergovernmental fiscal transfer systems should fulfil three basic functions. First, they should internalize externalities created by regional spillovers, such as public goods that benefit people from multiple local jurisdictions (Oates 1999), cross-border pollution or the erosion of tax bases in the presence of interjurisdictional competition (Wilson 1999). Second, they should incentivize local governments to mobilize resources and spend their resources efficiently. And third, they should have an equalizing function through which differences in economic development across regions are counterbalanced (Shah 2006; Boadway and Shah 2007). In the case of a one-sided fiscal decentralization, transfers of course have a major financing function (Boadway and Shah 2007). In short, intergovernmental fiscal transfers are an instrument that allow benefitting from the advantages of fiscal decentralization while minimizing its costs in terms of fiscal inequity or negative external effects (Boadway 2007). Yet, in practice, the allocation of transfers is often determined by political considerations like rewarding core voters or targeting swing voters (Gonschorek, Schulze and Sjahrir 2018; Weingast 2009, 2014). Moreover, transfer systems are often designed as a result of lobbying for regional interests.
Prior research has established associations between neighbourhood poverty and cumulative biological risk (CBR). CBR is conceptualized as indicative of the effects of stress on biological functioning, and is linked with increased morbidity and mortality. Studies suggest that supportive social relationships may be health protective, and may erode under conditions of poverty. This study examines whether social relationships are inversely associated with CBR and whether associations between neighbourhood poverty and CBR are mediated through social relationships. Data were from a stratified probability sample community survey (n=919) of residents of Detroit, Michigan, USA (2002–2003) and from the 2000 US Census. The outcome variable, CBR, included anthropometric and clinical measures. Independent variables included four indicators of social relationships: social support, neighbourhood satisfaction, social cohesion and neighbourhood participation. Multilevel models were used to test both research questions, with neighbourhood poverty and social relationships included at the block group level, and social relationships also included at the individual level, to disentangle individual from neighbourhood effects. Findings suggest some associations between social relationships and CBR after accounting for neighbourhood poverty and individual characteristics. In models that accounted for all indicators of social relationships, individual-level social support was associated with greater CBR (β=0.12, p=0.04), while neighbourhood-level social support was marginally significantly protective of CBR (within-neighbourhood: β=−0.36, p=0.06; between-neighbourhood: β=−0.24, p=0.06). In contrast, individual-level neighbourhood satisfaction was protective of CBR (β=−0.10, p=0.02), with no within-neighbourhood (β=0.06, p=0.54) or between-neighbourhood association (β=−0.04, p=0.38). Results indicate no significant association between either social cohesion or neighbourhood participation and CBR. Associations between neighbourhood poverty and CBR were not mediated by social relationships. These findings suggest that neighbourhood-level social support and individual-level neighbourhood satisfaction may be health protective and that neighbourhood poverty, social support and neighbourhood satisfaction are associated with CBR through independent pathways.
Based on the vulnerability–stress model, we aimed to (1) determine new onset of depression in individuals who had not shown evidence of depression at baseline (5 years earlier) and (2) identify social, psychological, behavioral, and somatic predictors.
Longitudinal data of N = 10 036 participants (40–79 years) were evaluated who had no evidence of depression at baseline based on Patient Health Questionnaire (PHQ-9), no history of depression, or intake of antidepressants. Multivariate logistic regression models were used to predict the onset of depression.
Prevalence of new cases of depression was 4.4%. Higher rates of women (5.1%) than men (3.8%) were due to their excess incidence <60 years of age. Regression analyses revealed significant social, psychological, behavioral, and somatic predictors: loneliness [odds ratio (OR) 2.01; 95% confidence interval (CI) 1.48–2.71], generalized anxiety (OR 2.65; 1.79–3.85), social phobia (OR 1.87; 1.34–2.57), panic (OR 1.67; 1.01–2.64), type D personality (OR 1.85; 1.47–2.32), smoking (OR 1.35; 1.05–1.71), and comorbid cancer (OR 1.58; 1.09–2.24). Protective factors were age (OR 0.88; 0.83–0.93) and social support (OR 0.93; 0.90–0.95). Stratified by sex, cancer was predictive for women; for men smoking and life events. Entered additionally, the PHQ-9 baseline score was strongly predictive (OR 1.40; 1.34–1.47), generalized anxiety became only marginally, and panic was no longer predictive. Other predictors remained significant, albeit weaker.
Psychobiological vulnerability, stress, and illness-related factors were predictive of new onset of depression, whereas social support was protective. Baseline subclinical depression was an additional risk weakening the relationship between anxiety and depression by taking their overlap into account. Vulnerability factors differed between men and women.