Background: Neuronal and circuit level abnormalities of excitation and inhibition are shown to be associated with tau and amyloid-beta (Aβ) in preclinical models of Alzheimer's disease (AD). These relationships remain poorly understood in patients with AD.Methods: Using empirical spectra from magnetoencephalography (MEG) and computational modeling (neural mass model; NMM) we examined excitatory and inhibitory parameters of neuronal subpopulations and investigated their specific associations to regional tau and Aβ, measured by positron emission tomography (PET), in patients with AD.Results: Patients with AD showed abnormal excitatory and inhibitory time-constants and neural gains compared to age-matched controls. Increased excitatory time-constants distinctly correlated with higher tau depositions while increased inhibitory time-constants distinctly correlated with higher Aβ depositions.Conclusions: Our results provide critical insights about potential mechanistic links between abnormal neural oscillations and cellular correlates of impaired excitatory and inhibitory synaptic functions associated with tau and Aβ in patients with AD.Funding: This study was supported by the National Institutes of Health grants: K08AG058749 (KGR), F32AG050434-01A1 (KGR), K23 AG038357 (KAV), P50 AG023501, P01 AG19724 (BLM), P50-AG023501 (BLM & GDR), R01 AG045611 (GDR); AG034570, AG062542 (WJ); NS100440 (SSN), DC176960 (SSN), DC017091 (SSN), AG062196 (SSN); a grant from John Douglas French Alzheimer's Foundation (KAV); grants from Larry L. Hillblom Foundation: 2015-A-034-FEL and (KGR); 2019-A-013-SUP (KGR); a grant from the Alzheimer's Association: (PCTRB-13-288476) (KAV), and made possible by Part the CloudTM, (ETAC-09-133596); a grant from Tau Consortium (GDR & WJJ), and a gift from the S. D. Bechtel Jr. Foundation.

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The presence of micronuclei (MN) in mammalian cells is related to several mutagenetic stresses. MN are formed as a result of chromosome damage and can be readily identified in exfoliated epithelial cells. MN is chromatin particles derived from acentric chromosomal fragments, which are not incorporated into the daughter nucleus after mitosis. It can be visualized by chromatin stains. A variety of factors influences the formation of MN in cells such as age, sex, genetic constitution, physical and chemical agents, adverse habits such as tobacco, areca nut chewing, smoking, and alcohol consumption. Micronucleation has important implications in the genomic plasticity of tumor cells. The present paper reviews the origin, fate and scoring criteria of MN that serves as a biomarker of exposure to genetic toxins, and for the risk of cancer.

Juvenile insulin-dependent diabetes mellitus type 1 (IDDM) is a well-recognized worldwide entity, the significance of which has increased because of its recent upsurging trends, warranting attention on variety of its clinical expressions, in particular, pertaining to skin, an aspect seldom taken cognizance of. Hence an endeavour to recap the related dermatoses, such as limited joint mobility syndrome including sclerodermoid (scleroderma-like) changes, xerosis, necrobiosis lipoidica diabeticorum, granuloma annulare, diabetic foot syndrome, has been made. Complexities relating to the recently explored issues of atopic dermatitis and drug hypersensitivity syndrome have also been covered adequately. In addition, the current concepts of the physiopathology of type 1 diabetes-related dermatoses are briefly recapitulated for clarity.

We explore the stability and dynamic properties of a hierarchical, linearized, and analytic spectral graph model for neural oscillations that integrates the structuring wiring of the brain. Previously we have shown that this model can accurately capture the frequency spectra and the spatial patterns of the alpha and beta frequency bands obtained from magnetoencephalography recordings without regionally varying parameters. Here, we show that this macroscopic model based on long-range excitatory connections exhibits dynamic oscillations with a frequency in the alpha band even without any oscillations implemented at the mesoscopic level. We show that depending on the parameters, the model can exhibit combinations of damped oscillations, limit cycles, or unstable oscillations. We determined bounds on model parameters that ensure stability of the oscillations simulated by the model. Finally, we estimated time-varying model parameters to capture the temporal fluctuations in magnetoencephalography activity. We show that a dynamic spectral graph modeling framework with a parsimonious set of biophysically interpretable model parameters can thereby be employed to capture oscillatory fluctuations observed in electrophysiological data in various brain states and diseases.