Forward-backward and period doubling bifurcations in a discrete epidemic model with vaccination and limited medical resources.

A discrete epidemic model with vaccination and limited medical resources is proposed to understand its underlying dynamics. The model induces a nonsmooth two dimensional map that exhibits a surprising array of dynamical behavior including the phenomena of the forward-backward bifurcation and period doubling route to chaos with feasible parameters in an invariant region. We demonstrate, among other things, that the model generates the above described phenomena as the transmission rate or the basic reproduction number of the disease gradually increases provided that the immunization rate is low, the vaccine failure rate is high and the medical resources are limited.

[Bioinformatics analysis of programmed cell death ligand 1 co-expression genes and their regulatory network in head and neck squamous cell carcinoma].

Objective: This study aimed to construct a network of programmed celldeath ligand 1 (PD-L1) co-expression genes and screen potential biomarkers for PD-L1 expression in head and neck squamous cell carcinoma (HNSCC) by bioinformatics analysis. Moreover, the genes and pathways participating in PD-L1 and regulating the tumor immune status were determined.

Methods: The HNSCC transcriptomic dataset in TCGA was selected to retrieve gene sets on the cBioPortal platform, where PD-L1 co-expressional genes were acquired.

[Congenital infiltrating lipomatosis of face with seizures: a case report].

Congenital infiltrating lipomatosis of the face is a rare disorder resulting from overgrowth of adipose tissues. This condition presents gradually with swelling along with age, hypertrophy of adjacent bones, and tooth abnormalities. This study reports a case of congenital infiltrating lipomatosis of face with seizures and reviews relevant literature on the etiology, clinical symptom, diagnosis, and treatment of this condition.

Diversity of hysteresis in a fully cooperative coinfection model.

We propose a fully cooperative coinfection model in which singly infected individuals are more likely to acquire a second disease than susceptible ones and doubly infected individuals are also assumed to be more contagious than singly infected ones. The dynamics of such a fully cooperative coinfection model is investigated through the well-mixed approach. In particular, discontinuous outbreak transitions from the disease free state or the low prevalence state to the high prevalence state can be separately observed as a disease transmission rate crosses a threshold α from the below when the epidemic is still in the early stages.

Global stability for epidemic models on multiplex networks.

In this work, we consider an epidemic model in a two-layer network in which the dynamics of susceptible-infected-susceptible process in the physical layer coexists with that of a cyclic process of unaware-aware-unaware in the virtual layer. For such multiplex network, we shall define the basic reproduction number [Formula: see text] in the virtual layer, which is similar to the basic reproduction number [Formula: see text] defined in the physical layer. We show analytically that if [Formula: see text] and [Formula: see text], then the disease and information free equilibrium is globally stable and if [Formula: see text] and [Formula: see text], then the disease free and information saturated equilibrium is globally stable for all initial conditions except at the origin.

The impact of vaccine success and awareness on epidemic dynamics.

The role of vaccine success is introduced into an epidemic spreading model consisting of three states: susceptible, infectious, and vaccinated. Moreover, the effect of three types, namely, contact, local, and global, of infection awareness and immunization awareness is also taken into consideration. The model generalizes those considered in Pastor-Satorras and Vespignani [Phys.

The impact of vaccine failure rate on epidemic dynamics in responsive networks.

An SIS model based on the microscopic Markov-chain approximation is considered in this paper. It is assumed that the individual vaccination behavior depends on the contact awareness, local and global information of an epidemic. To better simulate the real situation, the vaccine failure rate is also taken into consideration.

Cluster synchronization in networks of neurons with chemical synapses.

In this work, we study the cluster synchronization of chemically coupled and generally formulated networks which are allowed to be nonidentical. The sufficient condition for the existence of stably synchronous clusters is derived. Specifically, we only need to check the stability of the origins of m decoupled linear systems.

Coordinate transformation and matrix measure approach for synchronization of complex networks.

Global synchronization in complex networks has attracted considerable interest in various fields. There are mainly two analytical approaches for studying such time-varying networks. The first approach is Lyapunov function-based methods.

Global synchronization in lattices of coupled chaotic systems.

Based on the concept of matrix measures, we study global stability of synchronization in networks. Our results apply to quite general connectivity topology. In addition, a rigorous lower bound on the coupling strength for global synchronization of all oscillators is also obtained.