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Alzheimer’s disease (AD) is the most common form of dementia and results in neurodegeneration and cognitive impairment. White matter (WM) is affected in AD and has implications for neural circuitry and cognitive function. The trajectory of these changes across age, however, is still not well understood, especially at earlier stages in life. To address this, we used theApp^{NL-G-F/NL-G-F}knock-in (APPKI) mouse model that harbors a single copy knock-in of the human amyloid precursor protein (APP) gene with three familial AD mutations. We performedin vivodiffusion tensor imaging (DTI) to study how the structural properties of the brain change across age in the context of AD. In late age APPKI mice, we observed reduced fractional anisotropy (FA), a proxy of WM integrity, in multiple brain regions, including the hippocampus, anterior commissure (AC), neocortex, and hypothalamus. At the cellular level, we observed greater numbers of oligodendrocytes in middle age (prior to observations in DTI) in both the AC, a major interhemispheric WM tract, and the hippocampus, which is involved in memory and heavily affected in AD, prior to observations in DTI. Proteomics analysis of the hippocampus also revealed altered expression of oligodendrocyte-related proteins with age and in APPKI mice. Together, these results help to improve our understanding of the development of AD pathology with age, and imply that middle age may be an important temporal window for potential therapeutic intervention.

 

Introduction Alzheimer's disease (AD) is a progressive neurodegenerative disease. The early processes of AD, however, are not fully understood and likely begin years before symptoms manifest. Importantly, disruption of the default mode network, including the hippocampus, has been implicated in AD. Methods To examine the role of functional network connectivity changes in the early stages of AD, we performed resting-state functional magnetic resonance imaging (rs-fMRI) using a mouse model harboring three familial AD mutations ( App NL-G-F/NL-G-F knock-in, APPKI) in female mice in early, middle, and late age groups. The interhemispheric and intrahemispheric functional connectivity (FC) of the hippocampus was modeled across age. Results We observed higher interhemispheric functional connectivity (FC) in the hippocampus across age. This was reduced, however, in APPKI mice in later age. Further, we observed loss of hemispheric asymmetry in FC in APPKI mice. Discussion Together, this suggests that there are early changes in hippocampal FC prior to heavy onset of amyloid β plaques, and which may be clinically relevant as an early biomarker of AD. 

Natural selection is inherently a multivariate phenomenon. The selection pressure on size (natural and artificial) and the age at which selection occurs is likely to induce evolutionary changes in growth rates across the entire life history. However, the covariance structure that will determine the path of evolution for size at age has been studied in only a few fish species. We therefore estimated the genetic covariance function for size throughout ontogeny using Atlantic silversides (Menidia menidia) as the model system. Over a 3‐year period, a total of 542 families were used to estimate the genetic covariance in length at age from hatch through maturity. The function‐valued trait approach was employed to estimate the genetic covariance functions. A Bayesian hierarchical model was used to account for the unbalanced design, unequal measurement intervals, unequal sample sizes, and family‐aggregated data. To improve mixing, we developed a two‐stage sampler using a Gibbs sampler to generate the posterior of a well‐mixing approximate model followed by an importance sampler to draw samples from posterior of the completely specified model. We found that heritability of length is age‐specific and there are strong genetic correlations in length across ages that last 30 days or more. We used these estimates in a hypothetical model predicting the evolutionary response to harvesting following a single generation of selection under both sigmoidal and unimodal patterns of gear selectivity to illustrate the potential outcomes of ignoring the genetic correlations. In these scenarios, genetic correlations were found to have a strong effect on both the direction and magnitude of the response to harvest selection.

 

Bacterial infections cause a wide range of host immune disorders, resulting in local and systemic tissue damage. Antibiotics are pharmacological interventions for treating bacterial infections, but increased antimicrobial resistance and the delayed development of new antibiotics have led to a major global health threat, the so‐called “superbugs.” Bacterial infections consist of two processes: pathogen invasion and host immune responses. Developing nanotherapeutics to target these two pathways may be effective for eliminating bacteria and restoring host homeostasis, thus possibly finding new treatments for bacterial infections. This review offers new approaches for developing nanotherapeutics based on the pathogenesis of infectious diseases. The mechanisms through which nanoparticles target infectious microenvironments are outlined, alongside a discussion of techniques that used target phagocytes to deliver antibiotics to eliminate intracellular pathogens. A new concept is also reviewed—host‐directed therapy for bacterial infections, such as targeting immune cells for the delivery of anti‐inflammatory agents and vaccine developments using bacterial‐membrane‐derived nanovesicles. This review demonstrates the translational potential of nanomedicine for improving infectious disease treatments.