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The fourth edition of Explaining the History of American Foreign Relations reconceptualizes this long-established classic to focus squarely on methods: not what we do, but how we do what we do. It presents revised, sharply focused essays on methods for researching national security, development, political economy, gender, religion, race, emotion, and nongovernmental organizations, alongside entirely new contributions on digital resources, spatial analysis, technology, materials, the natural world, the interaction of race and empire, US-Indigenous relations, ideology, and culture. The chapters are bracketed with an essay that assesses changes in the conception of US foreign relations history, and with an overview of how US foreign relations history is practiced in China. The essays, by scholars who have made a significant contribution in their areas of specialization, highlight conceptual approaches and methods that, taken together, offer an innovative and practical 'how-to' manual for both experienced scholars and newcomers to the field.
The brain’s default mode network (DMN) plays a role in social cognition, with altered DMN function being associated with social impairments across various neuropsychiatric disorders. However, the genetic basis linking sociability with DMN function remains underexplored. This study aimed to elucidate the shared genetics and causal relationship between sociability and DMN-related resting-state functional MRI (rs-fMRI) traits.
Methods
We conducted a comprehensive genomic analysis using large-scale genome-wide association study (GWAS) summary statistics for sociability and 31 activity and 64 connectivity DMN-related rs-fMRI traits (N = 34,691–342,461). We performed global and local genetic correlations analyses and bi-directional Mendelian randomization (MR) to assess shared and causal effects. We prioritized genes influencing both sociability and rs-fMRI traits by combining expression quantitative trait loci MR analyses, the CELLECT framework – integrating single-nucleus RNA sequencing (snRNA-seq) data with GWAS – and network propagation within a protein–protein interaction network.
Results
Significant local genetic correlations were identified between sociability and two rs-fMRI traits, one representing spontaneous activity within the temporal cortex, the other representing connectivity between the cingulate and angular/temporal cortices. MR analyses suggested potential causal effects of sociability on 12 rs-fMRI traits. Seventeen genes were highly prioritized, with LINGO1, ELAVL2, and CTNND1 emerging as top candidates. Among these, DRD2 was also identified, serving as a robust internal validation of our approach.
Conclusions
By combining genomic and transcriptomic data, our gene prioritization strategy may serve as a blueprint for future studies. Our findings can guide further research into the biological mechanisms underlying sociability and its role in the development, prognosis, and treatment of neuropsychiatric disorders.
There is wide variation in institutional sedation strategies in paediatric cardiac ICU. Validated tools such as State Behavioral Scale and Richmond Agitation Sedation Scale were created to help standardise sedation practices.
Methods:
This is a multi-phase, multicentre, prospective project with the goal of optimising safety and comfort for paediatric cardiac ICU patients. Phase one consisted of an educational intervention with a self-paced, web-based video module on optimal sedation practices using validated sedation screening tools. Participant knowledge was assessed via a de-identified, unmatched pre- and post-test survey. Survey scores were reported as an aggregate average score and compared using a t-test.
Results:
There were 259 pre-tests, and 142 post-tests collected during the video-assisted educational intervention. There was a significant increase in mean score on the post-test compared to the pre-test for both instruments: from 4 to 4.8/10 for State Behavioral Scale (p = 0.01) and from 4.5 to 4.9 for Richmond Agitation Sedation Scale (p = 0.04). 81% of respondents who completed the Richmond Agitation Sedation Scale post-test and 88.1% of those who completed the State Behavioral Scale post-test said their practice would change based on the new knowledge acquired.
Conclusion:
We report that our newly developed learning module intervention was effective in increasing short-term knowledge about optimal sedation and sedation scoring. Ongoing phase two efforts include evaluation of long-term compliance of validated sedation screening tools and developing an objective score to measure individual cumulative opioid dosing in the cardiac critical care unit.
In the aftermath of the 2018 migrant caravans, the Mexican government arrested two migrants’ rights activists,1 but not because they gave food or donated clothes to the caravaneros. The transgressive nature of their activism consisted of walking and organizing alongside people whose presence in the country was unauthorized. They were charged with smuggling-related crimes; but they were really “guilty” of solidarity. In this essay, we outline what solidarity entails, what compels various actors to join in, and to what end. From an interdisciplinary perspective, we discuss the “what,” “where,” “who,” and “why” of solidarity. The purpose is to open a new epistemological horizon, providing tools to collectively reflect on the complex issues at the intersection between solidarity, migration, and law.
Psychiatric disorders and type 2 diabetes mellitus (T2DM) are heritable, polygenic, and often comorbid conditions, yet knowledge about their potential shared familial risk is lacking. We used family designs and T2DM polygenic risk score (T2DM-PRS) to investigate the genetic associations between psychiatric disorders and T2DM.
Methods
We linked 659 906 individuals born in Denmark 1990–2000 to their parents, grandparents, and aunts/uncles using population-based registers. We compared rates of T2DM in relatives of children with and without a diagnosis of any or one of 11 specific psychiatric disorders, including neuropsychiatric and neurodevelopmental disorders, using Cox regression. In a genotyped sample (iPSYCH2015) of individuals born 1981–2008 (n = 134 403), we used logistic regression to estimate associations between a T2DM-PRS and these psychiatric disorders.
Results
Among 5 235 300 relative pairs, relatives of individuals with a psychiatric disorder had an increased risk for T2DM with stronger associations for closer relatives (parents:hazard ratio = 1.38, 95% confidence interval 1.35–1.42; grandparents: 1.14, 1.13–1.15; and aunts/uncles: 1.19, 1.16–1.22). In the genetic sample, one standard deviation increase in T2DM-PRS was associated with an increased risk for any psychiatric disorder (odds ratio = 1.11, 1.08–1.14). Both familial T2DM and T2DM-PRS were significantly associated with seven of 11 psychiatric disorders, most strongly with attention-deficit/hyperactivity disorder and conduct disorder, and inversely with anorexia nervosa.
Conclusions
Our findings of familial co-aggregation and higher T2DM polygenic liability associated with psychiatric disorders point toward shared familial risk. This suggests that part of the comorbidity is explained by shared familial risks. The underlying mechanisms still remain largely unknown and the contributions of genetics and environment need further investigation.
Future pandemics may cause more severe respiratory illness in younger age groups than COVID-19, requiring many more mechanical ventilators. This publication synthesizes the experiences of diverse contributors to Medtronic’s mechanical ventilator supply chain during the pandemic, serving as a record of what worked and what didn’t, while identifying key factors affecting production ramp-up in this healthcare crisis.
Method:
In-depth, one-on-one interviews (n = 17) were held with key Medtronic personnel and suppliers. Template analysis was used, and interview content was analyzed for signals, initiatives, actions, and outcomes, as well as influencing forces.
Results:
Key findings revealed many factors limiting ventilator production ramp-up. Supply chain strengths and weaknesses were identified. Political factors played a role in allocating ventilators and also supported production. Commercial considerations were not priority, but economic awareness was essential to support suppliers. Workers were motivated and flexible. Component shortages, space, production processes, and logistics were challenges. Legally based pressures were reported e.g., import and export restrictions.
Conclusion:
Crisis response alone is not enough; preparation is essential. Coordinated international strategies are more effective than individual country responses. Supply chain resilience based on visibility and flexibility is key. This research can help public health planners and the medical device industry prepare for future healthcare crises.
Perceived loneliness and objective social network size are related but distinct factors, which negatively affect mental health and are prevalent in patients who have experienced childhood maltreatment (CM), for example, patients with persistent depressive disorder (PDD) and borderline personality disorder (BPD). This cross-diagnostic study investigated whether loneliness, social network size, or both are associated with self-reported CM.
Methods
Loneliness and social network size were assessed in a population-based sample at two time points (Study 1, N = 509), and a clinical group of patients with PDD or BPD (Study 2, N = 190) using the UCLA Loneliness Scale and the Social Network Index. Further measures were the Childhood Trauma Questionnaire, and standard depression rating scales. Linear regression analyses were applied to compare associations of loneliness or social network size with CM. Multiple mediation analyses were used to test the relative importance of loneliness and social network size in the relationship between CM and depressive symptoms.
Results
In both studies, loneliness showed a stronger association than social network size with CM. This was particularly marked for emotional neglect and emotional abuse. Loneliness but not social network size mediated the relationship between CM and depressive symptoms.
Conclusions
Loneliness is particularly associated with self-reported CM, and in this respect distinct from the social network size. Our results underline the importance of differentiating both psychosocial constructs and suggest focusing on perceived loneliness and its etiological underpinnings by mechanism-based psychosocial interventions.
In daycare centres, the close contact of children with other children and employees favours the transmission of infections. The majority of children <6 years attend daycare programmes in Germany, but the role of daycare centres in the SARS-CoV-2 pandemic is unclear. We investigated the transmission risk in daycare centres and the spread of SARS-CoV-2 to associated households. 30 daycare groups with at least one recent laboratory-confirmed SARS-CoV-2 case were enrolled in the study (10/2020–06/2021). Close contact persons within daycare and households were examined over a 12-day period (repeated SARS-CoV-2 PCR tests, genetic sequencing of viruses, symptom diary). Households were interviewed to gain comprehensive information on each outbreak. We determined primary cases for all daycare groups. The number of secondary cases varied considerably between daycare groups. The pooled secondary attack rate (SAR) across all 30 daycare centres was 9.6%. The SAR tended to be higher when the Alpha variant was detected (15.9% vs. 5.1% with evidence of wild type). The household SAR was 53.3%. Exposed daycare children were less likely to get infected with SARS-CoV-2 than employees (7.7% vs. 15.5%). Containment measures in daycare programmes are critical to reduce SARS-CoV-2 transmission, especially to avoid spread to associated households.
Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities.
Methods
We combined two novel approaches. First, normative modeling to map deviations from the typical age-related pattern at the level of the individual of (i) activity during emotion matching and (ii) of anatomical images derived from DBD cases (n = 77) and controls (n = 52) aged 8–18 years from the EU-funded Aggressotype and MATRICS consortia. Second, linked independent component analysis to integrate subject-specific deviations from both modalities.
Results
While cases exhibited on average a higher activity than would be expected for their age during face processing in regions such as the amygdala when compared to controls these positive deviations were widespread at the individual level. A multimodal integration of all functional and anatomical deviations explained 23% of the variance in the clinical DBD phenotype. Most notably, the top marker, encompassing the default mode network (DMN) and subcortical regions such as the amygdala and the striatum, was related to aggression across the whole sample.
Conclusions
Overall increased age-related deviations in the amygdala in DBD suggest a maturational delay, which has to be further validated in future studies. Further, the integration of individual deviation patterns from multiple imaging modalities allowed to dissect some of the heterogeneity of DBD and identified the DMN, the striatum and the amygdala as neural signatures that were associated with aggression.
The 21st Century Cures Act preserved the FDA’s authority to regulate several categories of software that incorporate artificial intelligence/machine learning (AI/ML) techniques. The agency’s draft guidance on Clinical Decision Support Software proposed an approach for regulating CDS software and shed light on the FDA’s approach to genomic software. This chapter explains why the FDA’s proposed approach to regulating software is unlikely to preempt failure-to-warn suits. It then turns to design-defect suits, focusing on adaptive AI/ML software that continues to redesign itself throughout the product lifecycle. How will common defenses work when the state of the art is in the robotic “mind” of an AI/ML algorithm? We also reflect on broader impacts on patients, clinicians, software developers, and healthcare systems and ask whether the FDA is the “right” regulator to address the unresolved ethical and medical practice concerns that surround this software.
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
Aims
To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
Method
This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
Results
The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
Conclusions
Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
Aims
To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
Method
Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
Results
Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
Conclusions
AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
A recent genome-wide association study (GWAS) identified 12 independent loci significantly associated with attention-deficit/hyperactivity disorder (ADHD). Polygenic risk scores (PRS), derived from the GWAS, can be used to assess genetic overlap between ADHD and other traits. Using ADHD samples from several international sites, we derived PRS for ADHD from the recent GWAS to test whether genetic variants that contribute to ADHD also influence two cognitive functions that show strong association with ADHD: attention regulation and response inhibition, captured by reaction time variability (RTV) and commission errors (CE).
Methods
The discovery GWAS included 19 099 ADHD cases and 34 194 control participants. The combined target sample included 845 people with ADHD (age: 8–40 years). RTV and CE were available from reaction time and response inhibition tasks. ADHD PRS were calculated from the GWAS using a leave-one-study-out approach. Regression analyses were run to investigate whether ADHD PRS were associated with CE and RTV. Results across sites were combined via random effect meta-analyses.
Results
When combining the studies in meta-analyses, results were significant for RTV (R2 = 0.011, β = 0.088, p = 0.02) but not for CE (R2 = 0.011, β = 0.013, p = 0.732). No significant association was found between ADHD PRS and RTV or CE in any sample individually (p > 0.10).
Conclusions
We detected a significant association between PRS for ADHD and RTV (but not CE) in individuals with ADHD, suggesting that common genetic risk variants for ADHD influence attention regulation.
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.
Methods
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.
Results
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.
Conclusions
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.
Implementation of genome-scale sequencing in clinical care has significant challenges: the technology is highly dimensional with many kinds of potential results, results interpretation and delivery require expertise and coordination across multiple medical specialties, clinical utility may be uncertain, and there may be broader familial or societal implications beyond the individual participant. Transdisciplinary consortia and collaborative team science are well poised to address these challenges. However, understanding the complex web of organizational, institutional, physical, environmental, technologic, and other political and societal factors that influence the effectiveness of consortia is understudied. We describe our experience working in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, a multi-institutional translational genomics consortium.
Methods:
A key aspect of the CSER consortium was the juxtaposition of site-specific measures with the need to identify consensus measures related to clinical utility and to create a core set of harmonized measures. During this harmonization process, we sought to minimize participant burden, accommodate project-specific choices, and use validated measures that allow data sharing.
Results:
Identifying platforms to ensure swift communication between teams and management of materials and data were essential to our harmonization efforts. Funding agencies can help consortia by clarifying key study design elements across projects during the proposal preparation phase and by providing a framework for data sharing data across participating projects.
Conclusions:
In summary, time and resources must be devoted to developing and implementing collaborative practices as preparatory work at the beginning of project timelines to improve the effectiveness of research consortia.
Davidbrownite-(NH4), (NH4,K)5(V4+O)2(C2O4)[PO2.75(OH)1.25]4·3H2O, is a new mineral species from the Rowley mine, Maricopa County, Arizona, USA. It occurs in an unusual bat-guano-related, post-mining assemblage of phases that include a variety of vanadates, phosphates, oxalates and chlorides, some containing NH4+. Other secondary minerals found in association with davidbrownite-(NH4) are antipinite, fluorite, mimetite, mottramite, quartz, rowleyite, salammoniac, struvite, vanadinite, willemite and wulfenite. Crystals of davidbrownite-(NH4) are light green–blue needles or narrow blades up to ~0.2 mm long. The streak is white, the lustre is vitreous, Mohs hardness is ca. 2, tenacity is brittle and fracture is splintery. There are two good cleavages in the [010] zone, probably {100} and {001}. The measured density is 2.12(2) g cm–3. Davidbrownite-(NH4) is optically biaxial (+) with α = 1.540(2), β = 1.550(5) and γ = 1.582(2) (white light); 2V = 58.5(5)°; moderate r > v dispersion; and orientation Z = b and Y ≈ a. Pleochroism: X = pale blue, Y = nearly colourless, Z = light blue; and Y < X < Z. Electron microprobe analysis gave the empirical formula [(NH4)3.11K1.73Na0.09]Σ4.93[(V4+1.92Mg0.01Al0.02)Σ1.95O2](C2O4) [(P3.94As0.12)Σ4.06O10.94(OH)5.06]·3H2O, with the C and H content provided by the crystal structure. Raman and infrared spectroscopy confirmed the presence of NH4 and C2O4. Davidbrownite-(NH4) is monoclinic, P21/c, with a = 10.356(6), b = 8.923(5), c = 13.486(7) Å, β = 92.618(9)°, V = 1244.9(12) Å3 and Z = 2. The crystal structure of davidbrownite-(NH4) (R1 = 0.0524 for 2062 Io > 2σI reflections) consists of a chain structural unit with the formula {(V4+O)2(C2O4)[PO2.75(OH)1.25]4}5–, and a disordered interstitial complex containing five large monovalent cations (NH4+ and K+) and three H2O groups pfu. Strong hydrogen bonds form links within and between the chains.
The present paper presents a fundamentally novel approach to model individual differences of persons with the same biologically heterogeneous mental disorder. Unlike prevalent case-control analyses, that assume a clear distinction between patient and control groups and thereby introducing the concept of an ‘average patient’, we describe each patient's biology individually, gaining insights into the different facets that characterize persistent attention-deficit/hyperactivity disorder (ADHD).
Methods
Using a normative modeling approach, we mapped inter-individual differences in reference to normative structural brain changes across the lifespan to examine the degree to which case-control analyses disguise differences between individuals.
Results
At the level of the individual, deviations from the normative model were frequent in persistent ADHD. However, the overlap of more than 2% between participants with ADHD was only observed in few brain loci. On average, participants with ADHD showed significantly reduced gray matter in the cerebellum and hippocampus compared to healthy individuals. While the case-control differences were in line with the literature on ADHD, individuals with ADHD only marginally reflected these group differences.
Conclusions
Case-control comparisons, disguise inter-individual differences in brain biology in individuals with persistent ADHD. The present results show that the ‘average ADHD patient’ has limited informative value, providing the first evidence for the necessity to explore different biological facets of ADHD at the level of the individual and practical means to achieve this end.
Traits of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are strongly associated in children and adolescents, largely due to genetic factors. Less is known about the phenotypic and aetiological overlap between ADHD and ASD traits in adults.
Methods
We studied 6866 individuals aged 20–28 years from the Swedish Study of Young Adult Twins. Inattention (IA) and hyperactivity/impulsivity (HI) were assessed using the WHO Adult ADHD Self-Report Scale-V1.1. Repetitive and restricted behaviours (RRB) and social interaction and communication (SIC) were assessed using the Autism-Tics, ADHD, and other Comorbidities inventory. We used structural equation modelling to decompose covariance between these ADHD and ASD trait dimensions into genetic and shared/non-shared environmental components.
Results
At the phenotypic level, IA was similarly correlated with RRB (r = 0.33; 95% Confidence Interval (CI) 0.31–0.36) and with SIC (r = 0.32; 95% CI 0.29–0.34), whereas HI was more strongly associated with RRB (r = 0.38; 95% CI 0.35–0.40) than with SIC (r = 0.24; 95% CI 0.21–0.26). Genetic and non-shared environmental effects accounted for similar proportions of the phenotypic correlations, whereas shared environmental effects were of minimal importance. The highest genetic correlation was between HI and RRB (r = 0.56; 95% 0.46–0.65), and the lowest was between HI and SIC (r = 0.33; 95% CI 0.23–0.43).
Conclusions
We found evidence for dimension-specific phenotypic and aetiological overlap between ADHD and ASD traits in adults. Future studies investigating mechanisms underlying comorbidity between ADHD and ASD may benefit from exploring several symptom-dimensions, rather than considering only broad diagnostic categories.