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Classic theories posit that depression is driven by a negative learning bias. Most studies supporting this proposition used small and selected samples, excluding patients with comorbidities. However, comorbidity between psychiatric disorders occurs in up to 70% of the population. Therefore, the generalizability of the negative bias hypothesis to a naturalistic psychiatric sample as well as the specificity of the bias to depression, remain unclear. In the present study, we tested the negative learning bias hypothesis in a large naturalistic sample of psychiatric patients, including depression, anxiety, addiction, attention-deficit/hyperactivity disorder, and/or autism. First, we assessed whether the negative bias hypothesis of depression generalized to a heterogeneous (and hence more naturalistic) depression sample compared with controls. Second, we assessed whether negative bias extends to other psychiatric disorders. Third, we adopted a dimensional approach, by using symptom severity as a way to assess associations across the sample.
We administered a probabilistic reversal learning task to 217 patients and 81 healthy controls. According to the negative bias hypothesis, participants with depression should exhibit enhanced learning and flexibility based on punishment v. reward. We combined analyses of traditional measures with more sensitive computational modeling.
In contrast to previous findings, this sample of depressed patients with psychiatric comorbidities did not show a negative learning bias.
These results speak against the generalizability of the negative learning bias hypothesis to depressed patients with comorbidities. This study highlights the importance of investigating unselected samples of psychiatric patients, which represent the vast majority of the psychiatric population.
This chapter focuses on advancements in the understanding of personality pathology gained from structural and functional neuroimaging studies. It draws from the literature on the most widely researched personality disorders including schizotypal, borderline, and antisocial personality disorder. Prominent findings in schizotypal personality disorder include abnormalities in temporal and frontal lobe volumes, decreased structural connectivity of temporal lobe regions, and inefficient recruitment of brain areas during task performance. In borderline personality disorder, neuroimaging findings are characterized by aberrant volume and activity of limbic and prefrontal brain areas that suggest diminished top-down control of affective responsivity. Studies in antisocial personality disorder reveal reduced volume in prefrontal and temporal lobe structures, white matter structure compromise, and altered brain network functional connectivity. Significant challenges in studying this complex population and limitations of current methodology are discussed. Suggestions for future directions of research in this field are provided.
This rejoinder uses the neuroimaging literature on affect regulation to exemplify how integration of complementary methods suggested by the commentaries could advance neurobiological understanding of personality disorders. It illustrates progressive insights gained from incorporating multiple sources of evidence including neuroimaging, genetics, and behavioral data associated with affect regulation. It also demonstrates the use of brain pattern activation analysis in addition to studying individual regions of interest to better understand the complex relationships between biological genotype, brain activity, and behavioral phenotype. The ways in which neuroimaging can serve as an endophenotype to bridge the gap between genes and distant phenotypes are highlighted.
Between 2010 and 2019 the international health care organization Partners In Health (PIH) and its sister organization Zanmi Lasante (ZL) mounted a long-term response to the 2010 Haiti earthquake, focused on mental health. Over that time, implementing a Theory of Change developed in 2012, the organization successfully developed a comprehensive, sustained community mental health system in Haiti's Central Plateau and Artibonite departments, directly serving a catchment area of 1.5 million people through multiple diagnosis-specific care pathways. The resulting ZL mental health system delivered 28 184 patient visits and served 6305 discrete patients at ZL facilities between January 2016 and September 2019. The experience of developing a system of mental health services in Haiti that currently provides ongoing care to thousands of people serves as a case study in major challenges involved in global mental health delivery. The essential components of the effort to develop and sustain this community mental health system are summarized.
This review offers an update on research conducted with FinnTwin12 (FT12), the youngest of the three Finnish Twin Cohorts. FT12 was designed as a two-stage study. In the first stage, we conducted multiwave questionnaire research enrolling all eligible twins born in Finland during 1983–1987 along with their biological parents. In stage 2, we intensively studied a subset of these twins with in-school assessments at age 12 and semistructured poly-diagnostic interviews at age 14. At baseline, parents of intensively studied twins were administered the adult version of the interview. Laboratory studies with repeat interviews, neuropsychological tests, and collection of DNA were made of intensively studied twins during follow-up in early adulthood. The basic aim of the FT12 study design was to obtain information on individual, familial and school/neighborhood risks for substance use/abuse prior to the onset of regular tobacco and alcohol use and then track trajectories of use and abuse and their consequences into adulthood. But the longitudinal assessments were not narrowly limited to this basic aim, and with multiwave, multirater assessments from ages 11 to 12, the study has created a richly informative data set for analyses of gene–environment interactions of both candidate genes and genomewide measures with measured risk-relevant environments. Because 25 years have elapsed since the start of the study, we are planning a fifth-wave follow-up assessment.
Introduction: Cigarette addiction results from both pharmacological effects of nicotine and the rewarding effects of associated cues, including respiratory tract sensations.
Aims: This study sought to evaluate the initial acceptability of a non-nicotine botanical formulation that provided similar respiratory tract cues.
Methods: Two active test products and matching placebos were evaluated. One test product, an e-cigarette-like device, delivered a visible aerosol upon puffing; the other test product delivered an invisible vapour at ambient temperature. Test products delivered a botanical extract with flavourings and vehicle; the placebos delivered flavourings and vehicle only. Sixteen participants had 3-h ad libitum access to each test product and associated placebos, and were deprived of combustible cigarettes for 1 h before and throughout the 3-h evaluation period. Subjects rated the satisfaction (primary outcome) and other sensory qualities of the products. Safety evaluations included pulmonary function testing and monitoring vital signs.
Results: Satisfaction ratings (seven-point scale) were significantly greater for the active e-cigarette-like condition; M = 3.18, SD = 1.04 versus M = 2.69, SD = 1.22. Safety evaluations showed no clinically significant changes.
Conclusions: The results support the potential acceptability of a non-nicotine cigarette substitute in providing satisfaction to smokers. This approach merits further evaluation for safety and acceptability in tobacco harm reduction and cessation.
There is a growing interest in using cognitive–behavioural therapy (CBT) with people who have Asperger syndrome and comorbid mental health problems.
To examine whether modified group CBT for clinically significant anxiety in an Asperger syndrome population is feasible and likely to be efficacious.
Using a randomised assessor-blind trial, 52 individuals with Asperger syndrome were randomised into a treatment arm or a waiting-list control arm. After 24 weeks, those in the waiting-list control arm received treatment, while those initially randomised to treatment were followed up for 24 weeks.
The conversion rate for this trial was high (1.6:1), while attrition was 13%. After 24 weeks, there was no significant difference between those randomised to the treatment arm compared with those randomised to the waiting-list control arm on the primary outcome measure, the Hamilton Rating Scale for Anxiety.
Trials of psychological therapies with this population are feasible. Larger definitive trials are now needed.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
We analyzed birth order differences in means and variances of height and body mass index (BMI) in monozygotic (MZ) and dizygotic (DZ) twins from infancy to old age. The data were derived from the international CODATwins database. The total number of height and BMI measures from 0.5 to 79.5 years of age was 397,466. As expected, first-born twins had greater birth weight than second-born twins. With respect to height, first-born twins were slightly taller than second-born twins in childhood. After adjusting the results for birth weight, the birth order differences decreased and were no longer statistically significant. First-born twins had greater BMI than the second-born twins over childhood and adolescence. After adjusting the results for birth weight, birth order was still associated with BMI until 12 years of age. No interaction effect between birth order and zygosity was found. Only limited evidence was found that birth order influenced variances of height or BMI. The results were similar among boys and girls and also in MZ and DZ twins. Overall, the differences in height and BMI between first- and second-born twins were modest even in early childhood, while adjustment for birth weight reduced the birth order differences but did not remove them for BMI.
Grazing season length (GSL) on grassland farms with ruminant production systems can influence farm economics, livestock disease transmission, environmental impact, milk and meat quality, and consumer choice. Bioclimatic variables are biologically meaningful climate variables that may enable predictions of the impact of future climate change on GSL on European farms. The present study investigated the spatial relationship between current GSL (months) measured by EUROSTAT on dairy, beef and sheep farms in 706, 774 and 878 regions, respectively, and bioclimatic variables. A stepwise multiple regression model revealed a highly significant association between observed GSL and bioclimatic variables across Europe. Mean GSL was positively associated with the mean temperature of the coldest quarter and isothermality, and negatively associated with precipitation in the wettest month. Extrapolating these relationships to future climate change scenarios, most European countries were predicted to have a net increase in GSL with the increase being largest (up to 2·5 months) in the north-east of Europe. However, there were also predictions of increased variability between regions and decreases in GSL of up to 1·5 months in some areas such as the west of France, the south-west of Norway and the west coast of Britain. The study quantified and mapped the potential impact of climate change on GSL for dairy, beef and sheep farms across Europe.
The nematode Angiostrongylus vasorum is becoming more widely recorded globally, and is of increasing concern as a cause of disease in dogs. Apparent geographic spread is difficult to confirm due to a lack of standardized disease recording systems, increasing awareness among veterinary clinicians, and recent improvements in diagnostic technologies. This study examines the hypothesis that A. vasorum has spread in recent years by repeating the methods of a previous survey of the fox population. The hearts and lungs of 442 foxes from across Great Britain were collected and examined by dissection and flushing of the pulmonary circulation and microscopic inspection of tracheal scrapes. Sampling and parasite extraction methods were identical to an earlier survey in 2005 to ensure comparability. Prevalence of A. vasorum was 18·3% (exact binomial confidence bounds 14·9–22·3), compared with 7·3% previously (5·3–9·9, n = 546), and had increased significantly in most regions, e.g. 7·4% in the Northern UK (previously zero) and 50·8% in the south-east (previously 23·2%). Other nematodes identified were Crenosoma vulpis (prevalence 10·8%, CI 8·1–14·2) and Eucoleus aerophilus (31·6%, CI 27·3–36·2). These data support the proposal that A. vasorum has increased in prevalence and has spread geographically in Great Britain.
Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question.
Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes.
Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6–72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors.
Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.
To determine whether multidrug-resistant (MDR) gram-negative organisms are present in Afghanistan or Iraq soil samples, contaminate standard deployed hospital or modular operating rooms (ORs), or aerosolize during surgical procedures.
US military hospitals in the United States, Afghanistan, and Iraq.
Soil samples were collected from sites throughout Afghanistan and Iraq and analyzed for presence of MDR bacteria. Environmental sampling of selected newly established modular and deployed OR high-touch surfaces and equipment was performed to determine the presence of bacterial contamination. Gram-negative bacteria aerosolization during OR surgical procedures was determined by microbiological analysis of settle plate growth.
Subsurface soil sample isolates recovered in Afghanistan and Iraq included various pansusceptible members of Enterobacteriaceae, Vibrio species, Pseudomonas species, Acinetobacter Iwojfii, and coagulase-negative Staphylococcus (CNS). OR contamination studies in Afghanistan revealed 1 surface with a Micrococcus luteus. Newly established US-based modular ORs and the colocated fixed-facility ORs revealed no gram-negative bacterial contamination prior to the opening of the modular OR and 5 weeks later. Bacterial aerosolization during surgery in a deployed fixed hospital revealed a mean gram-negative bacteria colony count of 12.8 colony-forming units (CFU)/dm2/h (standard deviation [SD], 17.0) during surgeries and 6.5 CFU/dm2/h (SD, 7.5; P = .14) when the OR was not in use.
This study demonstrates no significant gram-negative bacilli colonization of modular and fixed-facility ORs or dirt and no significant aerosolization of these bacilli during surgical procedures. These results lend additional support to the role of nosocomial transmission of MDR pathogens or the colonization of the patient themselves prior to injury.