Amyloid pathology disrupts gliotransmitter release in astrocytes.

Accumulation of amyloid-beta (Aß) is associated with synaptic dysfunction and destabilization of astrocytic calcium homeostasis. A growing body of evidence support astrocytes as active modulators of synaptic transmission via calcium-mediated gliotransmission. However, the details of mechanisms linking Aß signaling, astrocytic calcium dynamics, and gliotransmission are not known. We developed a biophysical model that describes calcium signaling and the ensuing gliotransmitter release from a single astrocytic process when stimulated by glutamate release from hippocampal neurons. The model accurately captures the temporal dynamics of microdomain calcium signaling and glutamate release via both kiss-and-run and full-fusion exocytosis. We investigate the roles of two crucial calcium regulating machineries affected by Aß: plasma-membrane calcium pumps (PMCA) and metabotropic glutamate receptors (mGluRs). When we implemented these Aß-affected molecular changes in our astrocyte model, it led to an increase in the rate and synchrony of calcium events. Our model also reproduces several previous findings of Aß associated aberrant calcium activity, such as increased intracellular calcium level and increased spontaneous calcium activity, and synchronous calcium events. The study establishes a causal link between previous observations of hyperactive astrocytes in Alzheimer's disease (AD) and Aß-induced modifications in mGluR and PMCA functions. Analogous to neurotransmitter release, gliotransmitter exocytosis closely tracks calcium changes in astrocyte processes, thereby guaranteeing tight control of synaptic signaling by astrocytes. However, the downstream effects of AD-related calcium changes in astrocytes on gliotransmitter release are not known. Our results show that enhanced rate of exocytosis resulting from modified calcium signaling in astrocytes leads to a rapid depletion of docked vesicles that disrupts the crucial temporal correspondence between a calcium event and vesicular release. We propose that the loss of temporal correspondence between calcium events and gliotransmission in astrocytes pathologically alters astrocytic modulation of synaptic transmission in the presence of Aß accumulation.

Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents.

Importance: Chest radiography is the most common diagnostic imaging examination performed in emergency departments (EDs). Augmenting clinicians with automated preliminary read assistants could help expedite their workflows, improve accuracy, and reduce the cost of care. Objective: To assess the performance of artificial intelligence (AI) algorithms in realistic radiology workflows by performing an objective comparative evaluation of the preliminary reads of anteroposterior (AP) frontal chest radiographs performed by an AI algorithm and radiology residents. Design, Setting, and Participants: This diagnostic study included a set of 72 findings assembled by clinical experts to constitute a full-fledged preliminary read of AP frontal chest radiographs. A novel deep learning architecture was designed for an AI algorithm to estimate the findings per image. The AI algorithm was trained using a multihospital training data set of 342 126 frontal chest radiographs captured in ED and urgent care settings. The training data were labeled from their associated reports. Image-based F1 score was chosen to optimize the operating point on the receiver operating characteristics (ROC) curve so as to minimize the number of missed findings and overcalls per image read. The performance of the model was compared with that of 5 radiology residents recruited from multiple institutions in the US in an objective study in which a separate data set of 1998 AP frontal chest radiographs was drawn from a hospital source representative of realistic preliminary reads in inpatient and ED settings. A triple consensus with adjudication process was used to derive the ground truth labels for the study data set. The performance of AI algorithm and radiology residents was assessed by comparing their reads with ground truth findings. All studies were conducted through a web-based clinical study application system. The triple consensus data set was collected between February and October 2018. The comparison study was preformed between January and October 2019. Data were analyzed from October to February 2020. After the first round of reviews, further analysis of the data was performed from March to July 2020. Main Outcomes and Measures: The learning performance of the AI algorithm was judged using the conventional ROC curve and the area under the curve (AUC) during training and field testing on the study data set. For the AI algorithm and radiology residents, the individual finding label performance was measured using the conventional measures of label-based sensitivity, specificity, and positive predictive value (PPV). In addition, the agreement with the ground truth on the assignment of findings to images was measured using the pooled κ statistic. The preliminary read performance was recorded for AI algorithm and radiology residents using new measures of mean image-based sensitivity, specificity, and PPV designed for recording the fraction of misses and overcalls on a per image basis. The 1-sided analysis of variance test was used to compare the means of each group (AI algorithm vs radiology residents) using the F distribution, and the null hypothesis was that the groups would have similar means. Results: The trained AI algorithm achieved a mean AUC across labels of 0.807 (weighted mean AUC, 0.841) after training. On the study data set, which had a different prevalence distribution, the mean AUC achieved was 0.772 (weighted mean AUC, 0.865). The interrater agreement with ground truth finding labels for AI algorithm predictions had pooled κ value of 0.544, and the pooled κ for radiology residents was 0.585. For the preliminary read performance, the analysis of variance test was used to compare the distributions of AI algorithm and radiology residents' mean image-based sensitivity, PPV, and specificity. The mean image-based sensitivity for AI algorithm was 0.716 (95% CI, 0.704-0.729) and for radiology residents was 0.720 (95% CI, 0.709-0.732) (P = .66), while the PPV was 0.730 (95% CI, 0.718-0.742) for the AI algorithm and 0.682 (95% CI, 0.670-0.694) for the radiology residents (P < .001), and specificity was 0.980 (95% CI, 0.980-0.981) for the AI algorithm and 0.973 (95% CI, 0.971-0.974) for the radiology residents (P < .001). Conclusions and Relevance: These findings suggest that it is possible to build AI algorithms that reach and exceed the mean level of performance of third-year radiology residents for full-fledged preliminary read of AP frontal chest radiographs. This diagnostic study also found that while the more complex findings would still benefit from expert overreads, the performance of AI algorithms was associated with the amount of data available for training rather than the level of difficulty of interpretation of the finding. Integrating such AI systems in radiology workflows for preliminary interpretations has the potential to expedite existing radiology workflows and address resource scarcity while improving overall accuracy and reducing the cost of care.

AI Accelerated Human-in-the-loop Structuring of Radiology Reports.

Rule-based Natural Language Processing (NLP) pipelines depend on robust domain knowledge. Given the long tail of important terminology in radiology reports, it is not uncommon for standard approaches to miss items critical for understanding the image. AI techniques can accelerate the concept expansion and phrasal grouping tasks to efficiently create a domain specific lexicon ontology for structuring reports. Using Chest X-ray (CXR) reports as an example, we demonstrate that with robust vocabulary, even a simple NLP pipeline can extract 83 directly mentioned abnormalities (Ave. recall=93.83%, precision=94.87%) and 47 abnormality/normality descriptions of key anatomies. The richer vocabulary enables identification of additional label mentions in 10 out of 13 labels (compared to baseline methods). Furthermore, it captures expert insight into critical differences between observed and inferred descriptions, and image quality issues in reports. Finally, we show how the CXR ontology can be used to anatomically structure labeled output.

Early life stress determines the effects of glucocorticoids and stress on hippocampal function: Electrophysiological and behavioral evidence respectively.

Exposure to early-life adversity may program brain function to prepare individuals for adaptation to matching environmental contexts. In this study we tested this hypothesis in more detail by examining the effects of early-life stress - induced by raising offspring with limited nesting and bedding material from postnatal days 2-9 - in various behavioral tasks and on synaptic function in adult mice. Early-life stress impaired adult performance in the hippocampal dependent low-arousing object-in-context recognition memory task. This effect was absent when animals were exposed to a single stressor before training. Early-life stress did not alter high-arousing context and auditory fear conditioning. Early-life stress-induced behavioral modifications were not associated with alterations in the dendritic architecture of hippocampal CA1 pyramidal neurons or principal neurons of the basolateral amygdala. However, early-life stress reduced the ratio of NMDA to AMPA receptor-mediated excitatory postsynaptic currents and glutamate release probability specifically in hippocampal CA1 neurons, but not in the basolateral amygdala. These ex vivo effects in the hippocampus were abolished by acute glucocorticoid treatment. Our findings support that early-life stress can hamper object-in-context learning via pre- and postsynaptic mechanisms that affect hippocampal function but these effects are counteracted by acute stress or elevated glucocorticoid levels.

Stress-induced alterations in large-scale functional networks of the rodent brain.

Stress-related psychopathology is associated with altered functioning of large-scale brain networks. Animal research into chronic stress, one of the most prominent environmental risk factors for development of psychopathology, has revealed molecular and cellular mechanisms potentially contributing to human mental disease. However, so far, these studies have not addressed the system-level changes in extended brain networks, thought to critically contribute to mental disorders. We here tested the effects of chronic stress exposure (10 days immobilization) on the structural integrity and functional connectivity patterns in the brain, using high-resolution structural MRI, diffusion kurtosis imaging, and resting-state functional MRI, while confirming the expected changes in neuronal dendritic morphology using Golgi-staining. Stress effectiveness was confirmed by a significantly lower body weight and increased adrenal weight. In line with previous research, stressed animals displayed neuronal dendritic hypertrophy in the amygdala and hypotrophy in the hippocampal and medial prefrontal cortex. Using independent component analysis of resting-state fMRI data, we identified ten functional connectivity networks in the rodent brain. Chronic stress appeared to increase connectivity within the somatosensory, visual, and default mode networks. Moreover, chronic stress exposure was associated with an increased volume and diffusivity of the lateral ventricles, whereas no other volumetric changes were observed. This study shows that chronic stress exposure in rodents induces alterations in functional network connectivity strength which partly resemble those observed in stress-related psychopathology. Moreover, these functional consequences of stress seem to be more prominent than the effects on gross volumetric change, indicating their significance for future research.

Delayed effects of corticosterone on slow after-hyperpolarization potentials in mouse hippocampal versus prefrontal cortical pyramidal neurons.

The rodent stress hormone corticosterone changes neuronal activity in a slow and persistent manner through transcriptional regulation. In the rat dorsal hippocampus, corticosterone enhances the amplitude of calcium-dependent potassium currents that cause a lingering slow after-hyperpolarization (sAHP) at the end of depolarizing events. In this study we compared the putative region-dependency of the delayed effects of corticosterone (approximately 5 hrs after treatment) on sAHP as well as other active and passive properties of layer 2/3 pyramidal neurons from three prefrontal areas, i.e. the lateral orbitofrontal, prelimbic and infralimbic cortex, with the hippocampus of adult mice. In agreement with previous studies, corticosterone increased sAHP amplitude in the dorsal hippocampus with depolarizing steps of increasing amplitude. However, in the lateral orbitofrontal, prelimbic and infralimbic cortices we did not observe any modifications of sAHP amplitude after corticosterone treatment. Properties of single action potentials or % ratio of the last spike interval with respect to the first spike interval, an indicator of accommodation in an action potential train, were not significantly affected by corticosterone in all brain regions examined. Lastly, corticosterone treatment did not induce any lasting changes in passive membrane properties of hippocampal or cortical neurons. Overall, the data indicate that corticosterone slowly and very persistently increases the sAHP amplitude in hippocampal pyramidal neurons, while this is not the case in the cortical regions examined. This implies that changes in excitability across brain regions reached by corticosterone may vary over a prolonged period of time after stress.

The same antidepressant elicits contrasting patterns of synaptic changes in the amygdala vs hippocampus.

As depression-like symptoms are often precipitated by some form of stress, animal models of stress have been used extensively to investigate cellular mechanisms of depression. Despite being implicated in the emotional symptoms of depression, the amygdala has received little attention compared to the hippocampus in the past studies of antidepressant action. Further, these investigations have not taken into account the contrasting effects of chronic stress on the hippocampus vs amygdala. If an antidepressant is to be equally effective in countering the differential effects of stress on both brain areas, then it is faced with the challenge of eliciting contrasting effects in these two structures. We tested this prediction by examining the impact of tianeptine, an antidepressant with proven clinical efficacy, on neurons of the lateral amygdala (LA) and hippocampal area CA1. Tianeptine reduces N-methyl-D-aspartate (NMDA)-receptor-mediated synaptic currents, without affecting α-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) currents, in LA neurons. By contrast, tianeptine enhances both NMDA and AMPA currents in area CA1. Tianeptine also lowers action potential firing in LA neurons. As tianeptine modulates cellular metrics that, in addition to mediating amygdalar behavioral output, are also affected by stress, we tested if tianeptine succeeds in countering stress effects in the intact animal. We find that tianeptine prevents two important functional consequences of chronic stress-induced plasticity in the amygdala--dendritic growth and enhanced anxiety-like behavior. These results provide evidence for antidepressant action on amygdalar neurons that are not only distinct from the hippocampus, but also protect against the debilitating impact of stress on amygdalar structure and function.

Dendritic morphology of hippocampal and amygdalar neurons in adolescent mice is resilient to genetic differences in stress reactivity.

Many studies have shown that chronic stress or corticosterone over-exposure in rodents leads to extensive dendritic remodeling, particularly of principal neurons in the CA3 hippocampal area and the basolateral amygdala. We here investigated to what extent genetic predisposition of mice to high versus low stress reactivity, achieved through selective breeding of CD-1 mice, is also associated with structural plasticity in Golgi-stained neurons. Earlier, it was shown that the highly stress reactive (HR) compared to the intermediate (IR) and low (LR) stress reactive mice line presents a phenotype, with respect to neuroendocrine parameters, sleep architecture, emotional behavior and cognition, that recapitulates some of the features observed in patients suffering from major depression. In late adolescent males of the HR, IR, and LR mouse lines, we observed no significant differences in total dendritic length, number of branch points and branch tips, summated tip order, number of primary dendrites or dendritic complexity of either CA3 pyramidal neurons (apical as well as basal dendrites) or principal neurons in the basolateral amygdala. Apical dendrites of CA1 pyramidal neurons were also unaffected by the differences in stress reactivity of the animals; marginally higher length and complexity of the basal dendrites were found in LR compared to IR but not HR mice. In the same CA1 pyramidal neurons, spine density of distal apical tertiary dendrites was significantly higher in LR compared to IR or HR animals. We tentatively conclude that the dendritic complexity of principal hippocampal and amygdala neurons is remarkably stable in the light of a genetic predisposition to high versus low stress reactivity, while spine density seems more plastic. The latter possibly contributes to the behavioral phenotype of LR versus HR animals.

Cellular correlates of enhanced anxiety caused by acute treatment with the selective serotonin reuptake inhibitor fluoxetine in rats.

Selective serotonin reuptake inhibitors (SSRIs) are used extensively in the treatment of depression and anxiety disorders. The therapeutic benefits of SSRIs typically require several weeks of continuous treatment. Intriguingly, according to clinical reports, symptoms of anxiety may actually increase during the early stages of treatment although more prolonged treatment alleviates affective symptoms. Consistent with earlier studies that have used animal models to capture this paradoxical effect of SSRIs, we find that rats exhibit enhanced anxiety-like behavior on the elevated plus-maze 1 h after a single injection of the SSRI fluoxetine. Next we investigated the potential neural substrates underlying the acute anxiogenic effects by analyzing the morphological and physiological impact of acute fluoxetine treatment on principal neurons of the basolateral amygdala (BLA), a brain area that plays a pivotal role in fear and anxiety. Although earlier studies have shown that behavioral or genetic perturbations that are anxiogenic for rodents also increase dendritic spine density in the BLA, we find that a single injection of fluoxetine does not cause spinogenesis on proximal apical dendritic segments on BLA principal neurons an hour later. However, at the same time point when a single dose of fluoxetine caused enhanced anxiety, it also enhanced action potential firing in BLA neurons in ex vivo slices. Consistent with this finding, in vitro bath application of fluoxetine caused higher spiking frequency and this increase in excitability was correlated with an increase in the input resistance of these neurons. Our results suggest that enhanced excitability of amygdala neurons may contribute to the increase in anxiety-like behavior observed following acute fluoxetine treatment.