A generative model of the connectome with dynamic axon growth.

Connectome generative models, otherwise known as generative network models, provide insight into the wiring principles underpinning brain network organization. While these models can approximate numerous statistical properties of empirical networks, they typically fail to explicitly characterize an important contributor to brain organization-axonal growth. Emulating the chemoaffinity-guided axonal growth, we provide a novel generative model in which axons dynamically steer the direction of propagation based on distance-dependent chemoattractive forces acting on their growth cones.

A systematic review of economic evaluation of healthcare associated infection prevention and control interventions in long term care facilities.

Background: Healthcare-associated infections (HCAI) are common in long-term care facilities (LTCF) and cause significant burden. Infection prevention and control (IPC) measures include the clinical best practices (CBP) of hand hygiene, hygiene and sanitation, screening, and basic and additional precautions. Few studies demonstrate their cost-effectiveness in LTCF, and those that do, largely focus on one CBP.

NOD1 Agonist Induces Proliferation and Plasma Cell Differentiation of Mouse B Cells Especially CD23 B Cells.

Background: Like innate cells, B cells also express Pattern Recognition Receptors (PRRs) to detect danger signal such as tissue damage or pathogen intrusion. Production of specific antibodies by plasma cells results from the activation and differentiation of B cells following three signals: (i) antigen recognition by B Cell Receptors, (ii) recognition of danger and (iii) T-cell help. However, it is unclear whether T-cell help is dispensable for B cell activation and differentiation or not.

Topological cluster statistic (TCS): Toward structural connectivity-guided fMRI cluster enhancement.

Functional magnetic resonance imaging (fMRI) studies most commonly use cluster-based inference to detect local changes in brain activity. Insufficient statistical power and disproportionate false-positive rates reportedly hinder optimal inference. We propose a structural connectivity-guided clustering framework, called topological cluster statistic (TCS), that enhances sensitivity by leveraging white matter anatomical connectivity information.

Hierarchical communities in the larval connectome: Links to cellular annotations and network topology.

One of the longstanding aims of network neuroscience is to link a connectome's topological properties-i.e., features defined from connectivity alone-with an organism's neurobiology.