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Recent changes to US research funding are having far-reaching consequences that imperil the integrity of science and the provision of care to vulnerable populations. Resisting these changes, the BJPsych Portfolio reaffirms its commitment to publishing mental science and advancing psychiatric knowledge that improves the mental health of one and all.
The stars of the Milky Way carry the chemical history of our Galaxy in their atmospheres as they journey through its vast expanse. Like barcodes, we can extract the chemical fingerprints of stars from high-resolution spectroscopy. The fourth data release (DR4) of the Galactic Archaeology with HERMES (GALAH) Survey, based on a decade of observations, provides the chemical abundances of up to 32 elements for 917 588 stars that also have exquisite astrometric data from the Gaia satellite. For the first time, these elements include life-essential nitrogen to complement carbon, and oxygen as well as more measurements of rare-earth elements critical to modern-life electronics, offering unparalleled insights into the chemical composition of the Milky Way. For this release, we use neural networks to simultaneously fit stellar parameters and abundances across the whole wavelength range, leveraging synthetic grids computed with Spectroscopy Made Easy. These grids account for atomic line formation in non-local thermodynamic equilibrium for 14 elements. In a two-iteration process, we first fit stellar labels to all 1 085 520 spectra, then co-add repeated observations and refine these labels using astrometric data from Gaia and 2MASS photometry, improving the accuracy and precision of stellar parameters and abundances. Our validation thoroughly assesses the reliability of spectroscopic measurements and highlights key caveats. GALAH DR4 represents yet another milestone in Galactic archaeology, combining detailed chemical compositions from multiple nucleosynthetic channels with kinematic information and age estimates. The resulting dataset, covering nearly a million stars, opens new avenues for understanding not only the chemical and dynamical history of the Milky Way but also the broader questions of the origin of elements and the evolution of planets, stars, and galaxies.
Objectives/Goals: Cerebral amyloid angiopathy (CAA) characterized by the accumulation of amyloid-beta in the cerebrovasculature, affects blood vessel integrity leading to brain hemorrhages and an accelerated cognitive decline in Alzheimer’s disease patients. In this study, we are conducting a genome-wide association study to identify genetic risk factors for CAA. Methods/Study Population: We genotyped 1253 additional AD cases using and curated existing genome-wide genotype data from 110 AD and 502 non-AD donors from the Mayo Clinic Brain Bank. We performed QC and imputation of all datasets. We conducted GWAS in AD only (N = 1,363), non-AD only, as well as the combined cohort (N = 1,865) by testing imputed variant dosages for association with square root transformed CAA using linear regression, adjusting for relevant covariates. To assess associations in the context of major CAA risk factors, we performed interaction analysis with APOEe4 presence and sex; and pursued stratified analyses. We collected peripheral gene expression measures using RNA isolated from 188 PAXgene tube samples of 95 donors collected across multiple time points. More than 1/3 of these participants have MRI measures collected. Results/Anticipated Results: Variants at the APOE locus were identified as the most significant in our study. In addition, several other variants with suggestive association were found under the main model adjusting for AD neuropathology (Braak and Thal). LINC-PINT splice variant remained associated with lower CAA scores in AD cases without the APOEe4 risk allele. To enhance the robustness of our findings, we are pursuing further expansion of our study cohort. In the periphery, we expect to identify expression changes associated with neuroimaging indicators of CAA and determine if variants and genes discovered via GWAS are implicated in these changes. Discussion/Significance of Impact: We expect this study will provide further insight into the genetic architecture underlying risk for CAA both in the context of significant AD pathology and without. Characterization of genetic variants and functional outcomes in the context of neuropathology may lead to new avenues of research aimed at identifying biomarkers and therapies to treat CAA
Society of Thoracic Surgeons Congenital Heart Surgery Database is the largest congenital heart surgery database worldwide but does not provide information beyond primary episode of care. Linkage to hospital electronic health records would capture complications and comorbidities along with long-term outcomes for patients with CHD surgeries. The current study explores linkage success between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health record data in North Carolina and Georgia.
Methods:
The Society of Thoracic Surgeons Congenital Heart Surgery Database was linked to hospital electronic health records from four North Carolina congenital heart surgery using indirect identifiers like date of birth, sex, admission, and discharge dates, from 2008 to 2013. Indirect linkage was performed at the admissions level and compared to two other linkages using a “direct identifier,” medical record number: (1) linkage between Society of Thoracic Surgeons Congenital Heart Surgery Database and electronic health records from a subset of patients from one North Carolina institution and (2) linkage between Society of Thoracic Surgeons data from two Georgia facilities and Georgia’s CHD repository, which also uses direct identifiers for linkage.
Results:
Indirect identifiers successfully linked 79% (3692/4685) of Society of Thoracic Surgeons Congenital Heart Surgery Database admissions across four North Carolina hospitals. Direct linkage techniques successfully matched Society of Thoracic Surgeons Congenital Heart Surgery Database to 90.2% of electronic health records from the North Carolina subsample. Linkage between Society of Thoracic Surgeons and Georgia’s CHD repository was 99.5% (7,544/7,585).
Conclusions:
Linkage methodology was successfully demonstrated between surgical data and hospital-based electronic health records in North Carolina and Georgia, uniting granular procedural details with clinical, developmental, and economic data. Indirect identifiers linked most patients, consistent with similar linkages in adult populations. Future directions include applying these linkage techniques with other data sources and exploring long-term outcomes in linked populations.
NASA’s all-sky survey mission, the Transiting Exoplanet Survey Satellite (TESS), is specifically engineered to detect exoplanets that transit bright stars. Thus far, TESS has successfully identified approximately 400 transiting exoplanets, in addition to roughly 6 000 candidate exoplanets pending confirmation. In this study, we present the results of our ongoing project, the Validation of Transiting Exoplanets using Statistical Tools (VaTEST). Our dedicated effort is focused on the confirmation and characterisation of new exoplanets through the application of statistical validation tools. Through a combination of ground-based telescope data, high-resolution imaging, and the utilisation of the statistical validation tool known as TRICERATOPS, we have successfully discovered eight potential super-Earths. These planets bear the designations: TOI-238b (1.61$^{+0.09} _{-0.10}$ R$_\oplus$), TOI-771b (1.42$^{+0.11} _{-0.09}$ R$_\oplus$), TOI-871b (1.66$^{+0.11} _{-0.11}$ R$_\oplus$), TOI-1467b (1.83$^{+0.16} _{-0.15}$ R$_\oplus$), TOI-1739b (1.69$^{+0.10} _{-0.08}$ R$_\oplus$), TOI-2068b (1.82$^{+0.16} _{-0.15}$ R$_\oplus$), TOI-4559b (1.42$^{+0.13} _{-0.11}$ R$_\oplus$), and TOI-5799b (1.62$^{+0.19} _{-0.13}$ R$_\oplus$). Among all these planets, six of them fall within the region known as ‘keystone planets’, which makes them particularly interesting for study. Based on the location of TOI-771b and TOI-4559b below the radius valley we characterised them as likely super-Earths, though radial velocity mass measurements for these planets will provide more details about their characterisation. It is noteworthy that planets within the size range investigated herein are absent from our own solar system, making their study crucial for gaining insights into the evolutionary stages between Earth and Neptune.
In this controlled study, we found that exposure to ultraviolet-C (UV-C) radiation was able to arrest the growth of selected pathogenic enteric and nonfermenting Gram-negative rods. Further studies are needed to confirm the clinical efficacy and determine optimal implementation strategies for utilizing UV-C terminal disinfection.
Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).
Participants and Methods:
This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.
Results:
Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.
Conclusions:
The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.
We present detailed characterization of laser-driven fusion and neutron production ($\sim {10}^5$/second) using 8 mJ, 40 fs laser pulses on a thin (<1 μm) D${}_2$O liquid sheet employing a measurement suite. At relativistic intensity ($\sim 5\times {10}^{18}$ W/cm${}^2$) and high repetition rate (1 kHz), the system produces deuterium–deuterium (D-D) fusion, allowing for consistent neutron generation. Evidence of D-D fusion neutron production is verified by a measurement suite with three independent detection systems: an EJ-309 organic scintillator with pulse-shape discrimination, a ${}^3\mathrm{He}$ proportional counter and a set of 36 bubble detectors. Time-of-flight analysis of the scintillator data shows the energy of the produced neutrons to be consistent with 2.45 MeV. Particle-in-cell simulations using the WarpX code support significant neutron production from D-D fusion events in the laser–target interaction region. This high-repetition-rate laser-driven neutron source could provide a low-cost, on-demand test bed for radiation hardening and imaging applications.
Interventions in environmental conservation are intended to make things better, not worse. Yet unintended and unanticipated consequences plague environmental conservation; key is how uncertainty plays out. Insights from the intellectual humility literature offer constructive strategies for coming to terms with uncertainty. Strategies such as self-distancing and self-assessment of causal complexity can be incorporated into conservation decision-making processes. Including reflection on what we know and do not know in the decision-making process potentially reduces unintended and unanticipated consequences of environmental conservation and management decisions. An important caution is not to have intellectual humility legitimate failing to act in the face of uncertainty.
We performed a systematic literature review and meta-analysis on the effectiveness of coronavirus disease 2019 (COVID-19) vaccination against post-COVID conditions (long COVID) among fully vaccinated individuals.
Design:
Systematic literature review/meta-analysis.
Methods:
We searched PubMed, Cumulative Index to Nursing and Allied Health, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to June 2, 2023, for studies evaluating the COVID-19 vaccine effectiveness (VE) against post-COVID conditions among fully vaccinated individuals who received two doses of COVID-19 vaccine. A post-COVID condition was defined as any symptom that was present four or more weeks after COVID-19 infection. We calculated the pooled diagnostic odds ratio (DOR) (95% confidence interval) for post-COVID conditions between fully vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% x (1-DOR).
Results:
Thirty-two studies with 775,931 individuals evaluated the effect of vaccination on post-COVID conditions, of which, twenty-four studies were included in the meta-analysis. The pooled DOR for post-COVID conditions among fully vaccinated individuals was 0.680 (95% CI: 0.523–0.885) with an estimated VE of 32.0% (11.5%–47.7%). Vaccine effectiveness was 36.9% (23.1%–48.2%) among those who received two doses of COVID-19 vaccine before COVID-19 infection and 68.7% (64.7%–72.2%) among those who received three doses before COVID-19 infection. The stratified analysis demonstrated no protection against post-COVID conditions among those who received COVID-19 vaccination after COVID-19 infection.
Conclusions:
Receiving a complete COVID-19 vaccination prior to contracting the virus resulted in a significant reduction in post-COVID conditions throughout the study period, including during the Omicron era. Vaccine effectiveness demonstrated an increase when supplementary doses were administered.
We recently reported on the radio-frequency attenuation length of cold polar ice at Summit Station, Greenland, based on bi-static radar measurements of radio-frequency bedrock echo strengths taken during the summer of 2021. Those data also allow studies of (a) the relative contributions of coherent (such as discrete internal conducting layers with sub-centimeter transverse scale) vs incoherent (e.g. bulk volumetric) scattering, (b) the magnitude of internal layer reflection coefficients, (c) limits on signal propagation velocity asymmetries (‘birefringence’) and (d) limits on signal dispersion in-ice over a bandwidth of ~100 MHz. We find that (1) attenuation lengths approach 1 km in our band, (2) after averaging 10 000 echo triggers, reflected signals observable over the thermal floor (to depths of ~1500 m) are consistent with being entirely coherent, (3) internal layer reflectivities are ≈–60$\to$–70 dB, (4) birefringent effects for vertically propagating signals are smaller by an order of magnitude relative to South Pole and (5) within our experimental limits, glacial ice is non-dispersive over the frequency band relevant for neutrino detection experiments.
Although multiple studies have revealed that coronavirus disease 2019 (COVID-19) vaccines can reduce COVID-19–related outcomes, little is known about their impact on post–COVID-19 conditions. We performed a systematic literature review and meta-analysis on the effectiveness of COVID-19 vaccination against post–COVID-19 conditions (ie, long COVID).
Methods:
We searched PubMed, CINAHL, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to April 27, 2022, for studies evaluating COVID-19 vaccine effectiveness against post–COVID-19 conditions among individuals who received at least 1 dose of Pfizer/BioNTech, Moderna, AstraZeneca, or Janssen vaccine. A post–COVID-19 condition was defined as any symptom that was present 3 or more weeks after having COVID-19. Editorials, commentaries, reviews, study protocols, and studies in the pediatric population were excluded. We calculated the pooled diagnostic odds ratios (DORs) for post–COVID-19 conditions between vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% × (1 − DOR).
Results:
In total, 10 studies with 1,600,830 individuals evaluated the effect of vaccination on post–COVID-19 conditions, of which 6 studies were included in the meta-analysis. The pooled DOR for post–COVID-19 conditions among individuals vaccinated with at least 1 dose was 0.708 (95% confidence interval (CI), 0.692–0.725) with an estimated vaccine effectiveness of 29.2% (95% CI, 27.5%–30.8%). The vaccine effectiveness was 35.3% (95% CI, 32.3%–38.1%) among those who received the COVID-19 vaccine before having COVID-19, and 27.4% (95% CI, 25.4%–29.3%) among those who received it after having COVID-19.
Conclusions:
COVID-19 vaccination both before and after having COVID-19 significantly decreased post–COVID-19 conditions for the circulating variants during the study period although vaccine effectiveness was low.
Cognitive training (CT) and aerobic exercise both show promising moderate impact on cognition and everyday functioning in schizophrenia. Aerobic exercise is hypothesized to increase brain-derived neurotrophic factor (BDNF) and thereby synaptic plasticity, leading to increased learning capacity. Systematic CT should take advantage of increased learning capacity and be more effective when combined with aerobic exercise.
Methods
We examined the impact of a 6-month program of cognitive training & exercise (CT&E) compared to cognitive training alone (CT) in 47 first-episode schizophrenia outpatients. All participants were provided the same Posit Science computerized CT, 4 h/week, using BrainHQ and SocialVille programs. The CT&E group also participated in total body circuit training exercises to enhance aerobic conditioning. Clinic and home-based exercise were combined for a target of 150 min per week.
Results
The MATRICS Consensus Cognitive Battery Overall Composite improved significantly more with CT&E than with CT alone (p = 0.04), particularly in the first 3 months (6.5 v. 2.2 T-score points, p < 0.02). Work/school functioning improved substantially more with CT&E than with CT alone by 6 months (p < 0.001). BDNF gain tended to predict the amount of cognitive gain but did not reach significance. The cognitive gain by 3 months predicted the amount of work/school functioning improvement at 6 months. The amount of exercise completed was strongly associated with the degree of cognitive and work/school functioning improvement.
Conclusions
Aerobic exercise significantly enhances the impact of CT on cognition and functional outcome in first-episode schizophrenia, apparently driven by the amount of exercise completed.
Evidence-based psychotherapies (EBPs) are underused in health care settings. Aligning implementation of EBPs with the needs of health care leaders (i.e., operational stakeholders) can potentially accelerate their uptake into routine practice. Operational stakeholders (such as hospital leaders, clinical directors, and national program officers) can influence development and oversight of clinical programs as well as policy directives at local, regional, and national levels. Thus, engaging these stakeholders during the implementation and dissemination of EBPs is critical when targeting wider use in health care settings. This article describes how research–operations partnerships were leveraged to increase implementation of an empirically supported psychotherapy – brief Cognitive Behavioral Therapy (brief CBT) – in Veterans Health Administration (VA) primary care settings. The partnered implementation and dissemination efforts were informed by the empirically derived World Health Organization’s ExpandNet framework. A steering committee was formed and included several VA operational stakeholders who helped align the brief CBT program with the implementation needs of VA primary care settings. During the first 18 months of the project, partnerships facilitated rapid implementation of brief CBT at eight VA facilities, including training of 12 providers who saw 120 patients, in addition to expanded program elements to better support sustainability (e.g., train-the-trainer procedures).
Recommendations for protein intake are based on total body weight; however, these recommendations do not consider lean body mass (LBM). The purpose of the present study was to identify the average protein intake in g/kg LBM in a group of healthy Masters Athletes (≥26 years of age, exercising ≥2 d/week). Data were obtained from a cross-sectional study. Body weight (kg), height (cm) and LBM via dual-energy X-ray absorptiometry were measured. Dietary intake was measured using a 2005 Block Food Frequency Questionnaire. The average energy intake, the percent energy from protein and the average protein intake in g/kg LBM were calculated. Differences between protein intake and the US Recommended Dietary Allowance (US RDA) (0⋅8 g/kg body weight) were determined. Alpha levels were set a priori to P < 0⋅05. A total of 176 participants (94 women, 82 men; 39 ± 11 years of age; body mass index: 24⋅6 ± 3⋅4 kg/m2) were analysed. The average energy intake, the percent protein energy and the average protein intake were 7996⋅9 ± 110⋅9 kilojoules (kJ)/d (1,910⋅4 ± 26⋅5 kcal), 15⋅5 ± 2⋅6 % and 1⋅43 ± 0⋅53 g/kg LBM, respectively. No differences existed between women and men for protein intake/kg LBM. Both sexes had significantly higher protein intakes than the US RDA (P < 0⋅001). We identified the average protein intake (g/kg LBM) in healthy Masters Athletes that may contribute to evolving perspectives on the determination of protein needs. The present study helps establish the relationship between protein intake and LBM so that we may further increase our accuracy when developing future protein recommendations.
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.
Refreezing of meltwater in firn is a major component of Greenland ice-sheet's mass budget, but in situ observations are rare. Here, we compare the firn density and total ice layer thickness in the upper 15 m of 19 new and 27 previously published firn cores drilled at 15 locations in southwest Greenland (1850–2360 m a.s.l.) between 1989 and 2019. At all sites, ice layer thickness covaries with density over time and space. At the two sites with the earliest observations (1989 and 1998), bulk density increased by 15–18%, in the top 15 m over 28 and 21 years, respectively. However, following the extreme melt in 2012, elevation-detrended density using 30 cores from all sites decreased by 15 kg m−3 a−1 in the top 3.75 m between 2013 and 2019. In contrast, the lowest elevation site's density shows no trend. Thus, temporary build-up in firn pore space and meltwater infiltration capacity is possible despite the long-term increase in Greenland ice-sheet melting.
Health disparities between Appalachia and the rest of the country are widening. To address this, the Appalachian Translational Research Network (ATRN) organizes an annual ATRN Health Summit. The most recent Summit was held online September 22–23, 2020, and hosted by Wake Forest Clinical and Translational Science Institute in partnership with the Northwest Area Health Education Center. The Summit, titled “Community-Engaged Research in Translational Science: Innovations to Improve Health in Appalachia,” brought together a diverse group of 141 stakeholders from communities, academic institutions, and the National Center for Advancing Translational Science (NCATS) to highlight current research, identify innovative approaches to translational science and community-engaged research, develop cross-regional research partnerships, and establish and disseminate priorities for future Appalachian-focused research. The Summit included three plenary presentations and 39 presentations within 12 concurrent breakout sessions. Here, we describe the Summit planning process and implementation, highlight some of the research presented, and outline nine emergent themes to guide future Appalachian-focused research.
Quasi-periodic plasmoid formation at the tip of magnetic streamer structures is observed to occur in experiments on the Big Red Ball as well as in simulations of these experiments performed with the extended magnetohydrodynamics code, NIMROD. This plasmoid formation is found to occur on a characteristic time scale dependent on pressure gradients and magnetic curvature in both experiment and simulation. Single mode, or laminar, plasmoids exist when the pressure gradient is modest, but give way to turbulent plasmoid ejection when the system drive is higher, which produces plasmoids of many sizes. However, a critical pressure gradient is also observed, below which plasmoids are never formed. A simple heuristic model of this plasmoid formation process is presented and suggested to be a consequence of a dynamic loss of equilibrium in the high-$\beta$ region of the helmet streamer. This model is capable of explaining the periodicity of plasmoids observed in the experiment and simulations, and produces plasmoid periods of 90 minutes when applied to two-dimensional models of solar streamers with a height of $3R_\odot$. This is consistent with the location and frequency at which periodic plasma blobs have been observed to form by Large Angle and Spectrometric Coronograph and Sun Earth Connection Coronal and Heliospheric Investigation instruments.