A new framework for semi-Markovian parametric multi-state models with interval censoring.

There are few computational and methodological tools available for the analysis of general multi-state models with interval censoring. Here, we propose a general framework for parametric inference with interval censored multi-state data. Our framework can accommodate any parametric model for the transition times, and covariates may be included in various ways. We present a general method for constructing the likelihood, which we have implemented in a ready-to-use R package, smms, available on GitHub. The R package also computes the required high-dimensional integrals in an efficient manner. Further, we explore connections between our modelling framework and existing approaches: our models fall under the class of semi-Markovian multi-state models, but with a different, and sparser parameterisation than what is often seen. We illustrate our framework through a dataset monitoring heart transplant patients. Finally, we investigate the effect of some forms of misspecification of the model assumptions through simulations.

Sleep cycle-dependent vascular dynamics in male mice and the predicted effects on perivascular cerebrospinal fluid flow and solute transport.

Perivascular spaces are important highways for fluid and solute transport in the brain enabling efficient waste clearance during sleep. However, the underlying mechanisms augmenting perivascular flow in sleep are unknown. Using two-photon imaging of naturally sleeping male mice we demonstrate sleep cycle-dependent vascular dynamics of pial arteries and penetrating arterioles: slow, large-amplitude oscillations in NREM sleep, a vasodilation in REM sleep, and a vasoconstriction upon awakening at the end of a sleep cycle and microarousals in NREM and intermediate sleep. These vascular dynamics are mirrored by changes in the size of the perivascular spaces of the penetrating arterioles: slow fluctuations in NREM sleep, reduction in REM sleep and an enlargement upon awakening after REM sleep and during microarousals in NREM and intermediate sleep. By biomechanical modeling we demonstrate that these sleep cycle-dependent perivascular dynamics likely enhance fluid flow and solute transport in perivascular spaces to levels comparable to cardiac pulsation-driven oscillations.

Impaired astrocytic Ca2+ signaling in awake-behaving Alzheimer's disease transgenic mice.

Increased astrocytic Ca2+ signaling has been shown in Alzheimer's disease mouse models, but to date no reports have characterized behaviorally induced astrocytic Ca2+ signaling in such mice. Here, we employ an event-based algorithm to assess astrocytic Ca2+ signals in the neocortex of awake-behaving tg-ArcSwe mice and non-transgenic wildtype littermates while monitoring pupil responses and behavior. We demonstrate an attenuated astrocytic Ca2+ response to locomotion and an uncoupling of pupil responses and astrocytic Ca2+ signaling in 15-month-old plaque-bearing mice. Using the genetically encoded fluorescent norepinephrine sensor GRABNE, we demonstrate a reduced norepinephrine signaling during spontaneous running and startle responses in the transgenic mice, providing a possible mechanistic underpinning of the observed reduced astrocytic Ca2+ responses. Our data points to a dysfunction in the norepinephrine-astrocyte Ca2+ activity axis, which may account for some of the cognitive deficits observed in Alzheimer's disease.

Neurodegenerative conditions such as Parkinson's or Alzheimer's disease are characterized by neurons dying and being damaged. Yet neurons are only one type of brain actors; astrocytes, for example, are star-shaped 'companion' cells that have recently emerged as being able to fine-tune neuronal communication. In particular, they can respond to norepinephrine, a signaling molecule that acts to prepare the brain and body for action. This activation results, for instance, in astrocytes releasing chemicals that can act on neurons. Certain cognitive symptoms associated with Alzheimer's disease could be due to a lack of norepinephrine. In parallel, studies in anaesthetized mice have shown perturbed astrocyte signaling in a model of the condition. Disrupted norepinephrine-triggered astrocyte signaling could therefore be implicated in the symptoms of the disease. Experiments in awake mice are needed to investigate this link, especially as anesthesia is known to disrupt the activity of astrocytes. To explore this question, Åbjørsbråten, Skaaraas et al. conducted experiments in naturally behaving mice expressing mutations found in patients with early-onset Alzheimer's disease. These mice develop hallmarks of the disorder. Compared to their healthy counterparts, these animals had reduced astrocyte signaling when running or being startled. Similarly, a fluorescent molecular marker for norepinephrine demonstrated less signaling in the modified mice compared to healthy ones. Over 55 million individuals currently live with Alzheimer's disease. The results by Åbjørsbråten, Skaaraas et al. suggest that astrocyte­norepinephrine communication may be implicated in the condition, an avenue of research that could potentially lead to developing new treatments.

Begonia-A Two-Photon Imaging Analysis Pipeline for Astrocytic Ca2+ Signals.

Imaging the intact brain of awake behaving mice without the dampening effects of anesthesia, has revealed an exceedingly rich repertoire of astrocytic Ca2+ signals. Analyzing and interpreting such complex signals pose many challenges. Traditional analyses of fluorescent changes typically rely on manually outlined static region-of-interests, but such analyses fail to capture the intricate spatiotemporal patterns of astrocytic Ca2+ dynamics. Moreover, all astrocytic Ca2+ imaging data obtained from awake behaving mice need to be interpreted in light of the complex behavioral patterns of the animal. Hence processing multimodal data, including animal behavior metrics, stimulation timings, and electrophysiological signals is needed to interpret astrocytic Ca2+ signals. Managing and incorporating these data types into a coherent analysis pipeline is challenging and time-consuming, especially if research protocols change or new data types are added. Here, we introduce Begonia, a MATLAB-based data management and analysis toolbox tailored for the analyses of astrocytic Ca2+ signals in conjunction with behavioral data. The analysis suite includes an automatic, event-based algorithm with few input parameters that can capture a high level of spatiotemporal complexity of astrocytic Ca2+ signals. The toolbox enables the experimentalist to quantify astrocytic Ca2+ signals in a precise and unbiased way and combine them with other types of time series data.

Astrocytic Ca2+ signaling is reduced during sleep and is involved in the regulation of slow wave sleep.

Astrocytic Ca2+ signaling has been intensively studied in health and disease but has not been quantified during natural sleep. Here, we employ an activity-based algorithm to assess astrocytic Ca2+ signals in the neocortex of awake and naturally sleeping mice while monitoring neuronal Ca2+ activity, brain rhythms and behavior. We show that astrocytic Ca2+ signals exhibit distinct features across the sleep-wake cycle and are reduced during sleep compared to wakefulness. Moreover, an increase in astrocytic Ca2+ signaling precedes transitions from slow wave sleep to wakefulness, with a peak upon awakening exceeding the levels during whisking and locomotion. Finally, genetic ablation of an important astrocytic Ca2+ signaling pathway impairs slow wave sleep and results in an increased number of microarousals, abnormal brain rhythms, and an increased frequency of slow wave sleep state transitions and sleep spindles. Our findings demonstrate an essential role for astrocytic Ca2+ signaling in regulating slow wave sleep.