The Human Affectome

Over the last decades, the interdisciplinary field of the affective sciences has seen proliferation rather than integration of theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human affective phenomena (what they are and how they work) which, shaped by academic motivations and values, have determined the affective constructs and operationalizations. An assumption on the purpose of affective phenomena can be used as a teleological principle to guide the construction of a common set of metaphysical and mechanistic assumptions—a framework for human affective research. In this capstone paper for the special issue “Towards an Integrated Understanding of the Human Affectome”, we gather the tiered purpose of human affective phenomena to synthesize assumptions that account for human affective phenomena collectively. This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Abstracts from the 8th International Conference on cGMP Generators, Effectors and Therapeutic Implications

This work was supported by a restricted research grant of Bayer AG

SFB 823 Reaction times of monitoring schemes for ARMA time series Discussion Paper Reaction times of monitoring schemes for ARMA time series *

Abstract This paper is concerned with deriving the limit distributions of stopping times devised to sequentially uncover structural breaks in the parameters of an autoregressive moving average, ARMA, time series. The stopping rules are defined as the first time lag for which detectors, based on CUSUMs and Page&apos;s CUSUMs for residuals, exceed the value of a prescribed threshold function. It is shown that the limit distributions crucially depend on a drift term induced by the underlying ARMA parameters. The precise form of the asymptotic is determined by an interplay between the location of the break point and the size of the change implied by the drift. The theoretical results are accompanied by a simulation study and applications to electroencephalography, EEG, and IBM data. The empirical results indicate a satisfactory behavior in finite samples

Case Report: Novel SAVI-Causing Variants in STING1 Expand the Clinical Disease Spectrum and Suggest a Refined Model of STING Activation.

Gain-of-function mutations in STING1 cause the monogenic interferonopathy, SAVI, which presents with early-onset systemic inflammation, cold-induced vasculopathy and/or interstitial lung disease. We identified 5 patients (3 kindreds) with predominantly peripheral vascular disease who harbor 3 novel STING1 variants, p.H72N, p.F153V, and p.G158A. The latter two were predicted by a previous cryo-EM structure model to cause STING autoactivation. The p.H72N variant in exon 3, however, is the first SAVI-causing variant in the transmembrane linker region. Mutations of p.H72 into either charged residues or hydrophobic residues all led to dramatic loss of cGAMP response, while amino acid changes to residues with polar side chains were able to maintain the wild type status. Structural modeling of these novel mutations suggests a reconciled model of STING activation, which indicates that STING dimers can oligomerize in both open and closed states which would obliviate a high-energy 180° rotation of the ligand-binding head for STING activation, thus refining existing models of STING activation. Quantitative comparison showed that an overall lower autoactivating potential of the disease-causing mutations was associated with less severe lung disease, more severe peripheral vascular disease and the absence of a robust interferon signature in whole blood. Our findings are important in understanding genotype-phenotype correlation, designing targeted STING inhibitors and in dissecting differentially activated pathways downstream of different STING mutations