Hyperthyroidism, hypothyroidism, thyroid stimulating hormone, and dementia risk: results from the NHANES 2011-2012 and Mendelian randomization analysis.

Introduction: As the world ages, dementia places a heavy burden on society and the economy, but current methods of diagnosing dementia are still limited and there are no better therapies that target the causes of dementia. The purpose of this work is to explore the relationship between thyroid disease, thyroid stimulating hormone (TSH) concentrations, free tetraiodothyronine (FT4) concentrations and cognitive function.

Methods: This study utilized cognitive function and thyroid data from the 2011-2012 National Health and Nutrition Examination Survey (NHANES) to assess the relationship between different groups of TSH and FT4 concentrations and cognitive function using weighted logistic regression and restricted cubic spline (RCS), and then used two-sample Mendelian Randomization (MR) to assess the causal relationship between hyperthyroidism, hypothyroidism, TSH and FT4 concentrations with dementia.

Analysis of Influence of Behavioral Adoption Threshold Diversity on Multi-Layer Network.

The same people exhibit various adoption behaviors for the same information on various networks. Previous studies, however, did not examine the variety of adoption behaviors on multi-layer networks or take into consideration this phenomenon. Therefore, we refer to this phenomenon, which lacks systematic analysis and investigation, as behavioral adoption diversity on multi-layered networks.

Behavioral Propagation Based on Passionate Psychology on Single Networks with Limited Contact.

Passionate psychology behavior is a common behavior in everyday society but has been rarely studied on complex networks; so, it needs to be explored in more scenarios. In fact, the limited contact feature network will be closer to the real scene. In this paper, we study the influence of sensitive behavior and the heterogeneity of individual contact ability in a single-layer limited-contact network, and propose a single-layer model with limited contact that includes passionate psychology behaviors.

Influence of heterogeneity of infection thresholds on epidemic spreading with neighbor resource supporting.

The spread of disease on complex networks has attracted wide attention in physics, mathematics, and epidemiology. Recent works have demonstrated that individuals always exhibit different criteria for disease infection in a network that significantly influences the epidemic dynamics. In this paper, considering the heterogeneity of node susceptibility, we proposed an infection threshold model with neighbor resource support.

The effect of information-driven resource allocation on the propagation of epidemic with incubation period.

In the pandemic of COVID-19, there are exposed individuals who are infected but lack distinct clinical symptoms. In addition, the diffusion of related information drives aware individuals to spontaneously seek resources for protection. The special spreading characteristic and coevolution of different processes may induce unexpected spreading phenomena.

Underestimated disease prevalence and severe phenotypes in patients with biallelic variants: A cohort study of primary familial brain calcification from China.

Background: Primary familial brain calcification (PFBC) is a rare calcifying disorder of the brain with extensive clinical and genetic heterogeneity. Its prevalence is underestimated due to clinical selection bias (compared with symptomatic PFBC patients, asymptomatic ones are less likely to undergo genetic testing).

Methods: A total of 273 PFBC probands were enrolled in a multicenter retrospective cohort study by two different approaches.

Dynamics of social contagions with local trend imitation.

Research on social contagion dynamics has not yet included a theoretical analysis of the ubiquitous local trend imitation (LTI) characteristic. We propose a social contagion model with a tent-like adoption probability to investigate the effect of this LTI characteristic on behavior spreading. We also propose a generalized edge-based compartmental theory to describe the proposed model.

Information filtering based on corrected redundancy-eliminating mass diffusion.

Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects' attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE) which is based on a spreading process on the network.