Leveraging Interactions for Stationary and Dynamic Financial Distress Prediction: A Spatio-Temporal Financial Graph Attention Network

Financial distress prediction is a prominent research topic in information systems, with two primary modelling categories: stationary and dynamic modelling. Recent stationary modelling works have leveraged company interactions to improve prediction performance, considering the heterogeneity of interactions while ignoring the dynamicity. However, few dynamic modelling works utilized interactions. To address the inconsistency and limitation of stationary and dynamic modelling works in leveraging interactions, we propose the Spatio-Temporal Financial Graph Attention Network with Meta-learning (STFGAN-Meta). STFGAN-Meta leverages interactions\u27 spatial heterogeneity via the Spatial Aggregation module and temporal dynamicity via the Temporal Aggregation module. STFGAN-Meta introduces the Meta-learning Optimization module to unify stationary and dynamic modelling. Our experimental evaluation demonstrates that leveraging dynamicity and heterogeneity of interactions outperforms leveraging dynamicity or heterogeneity alone. Meta-learning succeeds in providing a generalized approach between stationary and dynamic modelling. STFGAN-Meta can be a promising risk assessment and decision-making tool in the financial industry

Superdensity Operators for Spacetime Quantum Mechanics

We introduce superdensity operators as a tool for analyzing quantum information in spacetime. Superdensity operators encode spacetime correlation functions in an operator framework, and support a natural generalization of Hilbert space techniques and Dirac's transformation theory as traditionally applied to standard density operators. Superdensity operators can be measured experimentally, but accessing their full content requires novel procedures. We demonstrate these statements on several examples. The superdensity formalism suggests useful definitions of spacetime entropies and spacetime quantum channels. For example, we show that the von Neumann entropy of a superdensity operator is related to a quantum generalization of the Kolmogorov-Sinai entropy, and compute this for a many-body system. We also suggest experimental protocols for measuring spacetime entropies.Comment: 43+16 pages, 12 figures; v2: typos fixed, references adde

FTO Genotype and 2-Year Change in Body Composition and Fat Distribution in Response to Weight-Loss Diets: The POUNDS LOST Trial

Recent evidence suggests that the fat mass and obesity-associated gene (FTO) genotype may interact with dietary intakes in relation to adiposity. We tested the effect of FTO variant on weight loss in response to 2-year diet interventions. FTO rs1558902 was genotyped in 742 obese adults who were randomly assigned to one of four diets differing in the proportions of fat, protein, and carbohydrate. Body composition and fat distribution were measured by dual-energy x-ray absorptiometry and computed tomography. We found significant modification effects for intervention varying in dietary protein on 2-year changes in fat-free mass, whole body total percentage of fat mass, total adipose tissue mass, visceral adipose tissue mass, and superficial adipose tissue mass (for all interactions, P < 0.05). Carriers of the risk allele had a greater reduction in weight, body composition, and fat distribution in response to a high-protein diet, whereas an opposite genetic effect was observed on changes in fat distribution in response to a low-protein diet. Likewise, significant interaction patterns also were observed at 6 months. Our data suggest that a high-protein diet may be beneficial for weight loss and improvement of body composition and fat distribution in individuals with the risk allele of the FTO variant rs1558902

Birth Weight, Genetic Susceptibility, and Adulthood Risk of Type 2 Diabetes

OBJECTIVE Both stressful intrauterine milieus and genetic susceptibility have been linked to later-life diabetes risk. The current study aims to examine the interaction between low birth weight, a surrogate measure of stressful intrauterine milieus, and genetic susceptibility in relation to risk of type 2 diabetes in adulthood. RESEARCH DESIGN AND METHODS The analysis included two independent, nested case-control studies of 2,591 type 2 diabetic case subjects and 3,052 healthy control subjects. We developed two genotype scores: an obesity genotype score based on 32 BMI-predisposing variants and a diabetes genotype score based on 35 diabetes-predisposing variants. RESULTS Obesity genotype scores showed a stronger association with type 2 diabetes risk in individuals with low birth weight. In low–birth weight individuals, the multivariable-adjusted odds ratio (OR) was 2.55 (95% CI 1.34–4.84) by comparing extreme quartiles of the obesity genotype score, while the OR was 1.27 (1.04–1.55) among individuals with birth weight >2.5 kg (P for interaction = 0.017). We did not observe significant interaction between diabetes genotype scores and birth weight with regard to risk of type 2 diabetes. In a comparison of extreme quartiles of the diabetes gene score, the multivariable-adjusted OR was 3.80 (1.76–8.24) among individuals with low birth weight and 2.27 (1.82–2.83) among those with high birth weight (P for interaction = 0.16). CONCLUSIONS Our data suggest that low birth weight and genetic susceptibility to obesity may synergistically affect adulthood risk of type 2 diabetes

Genetic Predisposition to Dyslipidemia and Type 2 Diabetes Risk in Two Prospective Cohorts

Dyslipidemia has been associated with type 2 diabetes, but it remains unclear whether dyslipidemia plays a causal role in type 2 diabetes. We aimed to examine the association between the genetic predisposition to dyslipdemia and type 2 diabetes risk. The current study included 2,447 patients with type 2 diabetes and 3,052 control participants of European ancestry from the Nurses’ Health Study and the Health Professionals Follow-up Study. Genetic predisposition to dyslipidemia was estimated by three genotype scores of lipids (LDL cholesterol, HDL cholesterol, and triglycerides) on the basis of the established loci for blood lipids. Linear relation analysis indicated that the HDL cholesterol and triglyceride genotype scores, but not the LDL cholesterol genotype score, were linearly related to elevated type 2 diabetes risk. Each point of the HDL cholesterol and triglyceride genotype scores was associated with a 3% (odds ratio [OR] 1.03 [95% CI 1.01–1.04]) and a 2% (1.02 [1.00–1.04]) increased risk of developing type 2 diabetes, respectively. The ORs were 1.39 (1.17–1.65) and 1.19 (1.01–1.41) for type 2 diabetes by comparing extreme quartiles of the HDL cholesterol genotype score and triglyceride genotype score, respectively. In conclusion, genetic predisposition to low HDL cholesterol or high triglycerides is related to elevated type 2 diabetes risk

Adiposity and weight change in mid-life in relation to healthy survival after age 70 in women: prospective cohort study

Objective: To examine the hypothesis that mid-life adiposity is associated with a reduced probability of maintaining an optimal health status among those who survive to older ages. Design: Prospective cohort study. Setting: The Nurses’ Health Study, United States. Participants: 17 065 women who survived until at least the age of 70, provided information on occurrence of chronic disease, cognitive function, physical function, and mental health at older ages, and were free from major chronic diseases at mid-life (mean age was 50 at baseline in 1976). Main outcome measures: Healthy survival to age 70 and over was defined as having no history of 11 major chronic diseases and having no substantial cognitive, physical, or mental limitations. Results: Of the women who survived until at least age 70, 1686 (9.9%) met our criteria for healthy survival. Increased body mass index (BMI) at baseline was significantly associated with linearly reduced odds of healthy survival compared with usual survival, after adjustment for various lifestyle and dietary variables (P<0.001 for trend). Compared with lean women (BMI 18.5-22.9), obese women (BMI ≥30) had 79% lower odds of healthy survival (odds ratio 0.21, 95% confidence interval 0.15 to 0.29). In addition, the more weight gained from age 18 until mid-life, the less likely was healthy survival after the age of 70. The lowest odds of healthy survival were among women who were overweight (BMI ≥25) at age 18 and gained ≥10 kg weight (0.18, 0.09 to 0.36), relative to women who were lean (BMI 18.5-22.9) and maintained a stable weight. Conclusions: These data provide evidence that adiposity in mid-life is strongly related to a reduced probability of healthy survival among women who live to older ages, and emphasise the importance of maintaining a healthy weight from early adulthood