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Background: The United States Chronic Thromboembolic Pulmonary Hypertension Registry (US-CTEPH-R) was designed to characterize the demographic characteristics, evaluation, clinical course, and outcomes of surgical and nonsurgical therapies for patients with chronic thromboembolic pulmonary hypertension., Research Question: What are the differences in baseline characteristics and 1-year outcomes between operated and nonoperated subjects?, Study Design and Methods: This study describes a multicenter, prospective, longitudinal, observational registry of patients newly diagnosed (< 6 months) with CTEPH. Inclusion criteria required a mean pulmonary artery pressure ≥ 25 mm Hg documented by right heart catheterization and radiologic confirmation of CTEPH. Between 2015 and 2018, a total of 750 patients were enrolled and followed up biannually until 2019., Results: Most patients with CTEPH (87.9%) reported a history of acute pulmonary embolism. CTEPH diagnosis delays were frequent (median, 10 months), and most patients reported World Health Organization functional class 3 status at enrollment with a median mean pulmonary artery pressure of 44 mm Hg. The registry cohort was subdivided into Operable patients undergoing pulmonary thromboendarterectomy (PTE) surgery (n = 566), Operable patients who did not undergo surgery (n = 88), and those who were Inoperable (n = 96). Inoperable patients were older than Operated patients; less likely to be obese; have a DVT history, non-type O blood group, or thrombophilia; and more likely to have COPD or a history of cancer. PTE resulted in a median pulmonary vascular resistance decline from 6.9 to 2.6 Wood units (P < .001) with a 3.9% in-hospital mortality. At 1-year follow-up, Operated patients were less likely treated with oxygen, diuretics, or pulmonary hypertension-targeted therapy compared with Inoperable patients. A larger percentage of Operated patients were World Health Organization functional class 1 or 2 at 1 year (82.9%) compared with the Inoperable (48.2%) and Operable/No Surgery (56%) groups (P < .001)., Interpretation: Differences exist in the clinical characteristics between patients who exhibited operable CTEPH and those who were inoperable, with the most favorable 1-year outcomes in those who underwent PTE surgery., Clinical Trial Registration: ClinicalTrials.gov; No.: NCT02429284; URL: www.clinicaltrials.gov., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Hypertension is often the primary presenting symptom of multiple renal pathologies. Overactivity of the Renin-Angiotensin-Aldosterone-System (RAAS) is a common cause and usually results from an induced physiologic response. However, conditions do exist that involve autonomous renin production. Juxtaglomerular cell tumors (JGCT), or reninomas, are renal lesions that cause refractory hypertension via this mechanism. Symptoms and lab abnormalities usually subside with surgical resection of these tumors. Here, we present a case of a 13-year old female with uncontrolled hypertension secondary to reninoma treated with partial nephrectomy, with focus on initial presentation, diagnostic evaluation, and surgical management of this uncommon tumor., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Tubulocystic renal cell carcinoma is a rare cancer that was not defined as a distinct entity until the early 2000s. Due to the recency of its classification, it remains poorly understood and leaves much room for future research. This report looks at a unique case of this rare subtype of renal cancer. This specific case is unique due to both the demographics of the affected patient and the finding of bone metaplasia within the tumor. We believe this is the first ever reported incidence of this phenomenon., (© 2021 The Authors. Published by Elsevier Inc.)

The enhanced heat resistance of Salmonella developed at low water activity makes it a serious challenge to eliminate them during thermal processing. The objectives of this research are to (i) investigate the effect of water activity on thermal inactivation of Salmonella cocktail (Agona, Tennessee, Mbandaka, Montevideo, and Reading) in dried basil leaves, and (ii) evaluate Enterococcus faecium NRRL B-2354 as an appropriate surrogate for Salmonella in dried basil leaves. Dried basil leaves, inoculated with a Salmonella cocktail and E. faecium separately, were equilibrated to different water activities (a w : 0.40, 0.55, and 0.70) in a humidity-controlled chamber. The basil samples were packed (1.6 ± 0.1 g) in aluminum pouches and thermally treated at 70, 75, and 80 °C using a dry heating method for 0-180 min to obtain the thermal death curve. The microbial survival data was fit using two primary models (Log-linear and Weibull model). Results from AIC c showed that the log-linear model fits well for thermal inactivation of both microorganisms. As the a w decreases from 0.70 to 0.40 at 75 °C, the D-value increases from 3.30 to 9.14 min for Salmonella and 6.53 to 14.07 min for E. faecium. Based on the AIC c values, the modified Bigelow model fits the D-values better than the response surface model for both the microorganisms. The kill ratio of surrogate to pathogen ranged from 1.4 to 2.8, indicating that it is a conservative surrogate for Salmonella for performing validation of the thermal pasteurization process. The identification of suitable surrogate and development of modified Bigelow model will help the spice industry in developing the thermal processes for improving the safety of basil leaves., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Nicotinic acetylcholine receptors (nAChRs) play a critical role in the neuropharmacology of learning and memory. As such, naturally occurring alkaloids that regulate nAChR activity have gained interest for understanding and potentially improving memory function. In this study, we tested the acute effects of three known nicotinic alkaloids, nicotine, cotinine, and anatabine, in suppressing scopolamine-induced memory deficit in rodents by using two classic memory paradigms, Y-maze and novel object recognition (NOR) in mice and rats, respectively. We found that all compounds were able to suppress scopolamine-induced spatial memory deficit in the Y-maze spontaneous alternation paradigm. However, only nicotine was able to suppress the short-term object memory deficit in NOR, despite the higher doses of cotinine and anatabine used to account for their potential differences in nAChR activity. These results indicate that cotinine and anatabine can uniquely regulate short-term spatial memory, while nicotine seems to have more robust and general role in memory regulation in rodents. Thus, nAChR-activating alkaloids may possess distinct procognitive properties in rodents, depending on the memory types examined.

Rodent models have facilitated major discoveries in neurobiology, however, the low success rate of novel medications in clinical trials have led to questions about their translational value in neuropsychiatric drug development research. For age-related disorders of cognition such as Alzheimer' disease (AD) there is interest in moving beyond transgenic amyloid-β and/or tau-expressing rodent models and focusing more on natural aging and dissociating "healthy" from "pathological" aging to identify new therapeutic targets and treatments. In complex disorders such as AD, it can also be argued that animals with closer neurobiology to humans (e.g., nonhuman primates) should be employed more often particularly in the later phases of drug development. The purpose of the work described here was to evaluate the cognitive capabilities of rhesus monkeys across a wide range of ages in different delayed response tasks, a computerized delayed match to sample (DMTS) task and a manual delayed match to position (DMTP) task. Based on specific performance criteria and comparisons to younger subjects, the older subjects were generally less proficient, however, some performed as well as young subjects, while other aged subjects were markedly impaired. Accordingly, the older subjects could be categorized as aged "cognitively-unimpaired" or aged "cognitively-impaired" with a third group (aged-other) falling in between. Finally, as a proof of principle, we demonstrated using the DMTP task that aged cognitively-impaired monkeys are sensitive to the pro-cognitive effects of a nicotinic acetylcholine receptor (nAChR) partial agonist, encenicline, suggesting that nAChR ligands remain viable as potential treatments for age-related disorders of cognition., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: For people with idiopathic generalized epilepsy, functional networks derived from their resting-state scalp electrophysiological recordings have shown an inherent higher propensity to generate seizures than those from healthy controls when assessed using the concept of brain network ictogenicity (BNI). Herein we tested whether the BNI framework is applicable to resting-state magnetoencephalography (MEG) from people with juvenile myoclonic epilepsy (JME)., Methods: The BNI framework consists in deriving a functional network from apparently normal brain activity, placing a mathematical model of ictogenicity into the network and then computing how often such network generates seizures in silico. We considered data from 26 people with JME and 26 healthy controls., Results: We found that resting-state MEG functional networks from people with JME are characterized by a higher propensity to generate seizures (i.e., higher BNI) than those from healthy controls. We found a classification accuracy of 73%., Conclusions: The BNI framework is applicable to MEG and was capable of differentiating people with epilepsy from healthy controls., Significance: The BNI framework may be applied to resting-state MEG to aid in epilepsy diagnosis., Competing Interests: Declaration of Competing Interest JT is co-founder and Director of Neuronostics., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

The aggregation of amyloid β (Aβ) peptides and deposition of amyloid plaques are implicated in the pathogenesis of Alzheimer's disease (AD). Therefore, blocking Aβ aggregation with small molecules has been proposed as one therapeutic approach for AD. In the present study, a series of ranitidine analogs containing cyclic imide isosteres were synthesized and their inhibitory activities toward Aβ aggregation were evaluated using in vitro thioflavin T assays. The structure-activity relationship revealed that the 1,8-naphthalimide moiety provided profound inhibition of Aβ aggregation and structural modifications on the other parts of the parent molecule (compound 6 ) maintained similar efficacy. Some of these ranitidine analogs also possessed potent inhibitory activities of acetylcholinesterase (AChE), which is another therapeutic target in AD. These ranitidine analogs, by addressing both Aβ aggregation and AChE, offer insight into the key chemical features of a new type of multi-target directed ligands for the pharmaceutical treatment of AD.

Microglial surveillance is a key feature of brain physiology and disease. Here, we found that G i -dependent microglial dynamics prevent neuronal network hyperexcitability. By generating Mg PTX mice to genetically inhibit G i in microglia, we show that sustained reduction of microglia brain surveillance and directed process motility induced spontaneous seizures and increased hypersynchrony after physiologically evoked neuronal activity in awake adult mice. Thus, G i -dependent microglia dynamics may prevent hyperexcitability in neurological diseases.

Neuroendocrine axes display a remarkable diversity of dynamic signaling processes relaying information between the brain, endocrine glands, and peripheral target tissues. These dynamic processes include oscillations, elastic responses to perturbations, and plastic long term changes observed from the cellular to the systems level. While small transient dynamic changes can be considered physiological, larger and longer disruptions are common in pathological scenarios involving more than one neuroendocrine axes, suggesting that a robust control of hormone dynamics would require the coordination of multiple neuroendocrine clocks. The idea of apparently different axes being in fact exquisitely intertwined through neuroendocrine signals can be investigated in the regulation of stress and fertility. The stress response and the reproductive cycle are controlled by the Hypothalamic-Pituitary-Adrenal (HPA) axis and the Hypothalamic-Pituitary-Gonadal (HPG) axis, respectively. Despite the evidence surrounding the effects of stress on fertility, as well as of the reproductive cycle on stress hormone dynamics, there is a limited understanding on how perturbations in one neuroendocrine axis propagate to the other. We hypothesize that the links between stress and fertility can be better understood by considering the HPA and HPG axes as coupled systems. In this manuscript, we investigate neuroendocrine rhythms associated to the stress response and reproduction by mathematically modeling the HPA and HPG axes as a network of interlocked oscillators. We postulate a network architecture based on physiological data and use the model to predict responses to stress perturbations under different hormonal contexts: normal physiological, gonadectomy, hormone replacement with estradiol or corticosterone (CORT), and high excess CORT (hiCORT) similar to hypercortisolism in humans. We validate our model predictions against experiments in rodents, and show how the dynamic responses of these endocrine axes are consistent with our postulated network architecture. Importantly, our model also predicts the conditions that ensure robustness of fertility to stress perturbations, and how chronodisruptions in glucocorticoid hormones can affect the reproductive axis' ability to withstand stress. This insight is key to understand how chronodisruption leads to disease, and to design interventions to restore normal rhythmicity and health., (Copyright © 2020 Zavala, Voliotis, Zerenner, Tabak, Walker, Li, Terry, Lightman, O'Byrne and Tsaneva-Atanasova.)

Epilepsy is one of the most common neurological conditions affecting over 65 million people worldwide. Over one third of people with epilepsy are considered refractory: they do not respond to drug treatments. For this significant cohort of people, surgery is a potentially transformative treatment. However, only a small minority of people with refractory epilepsy are considered suitable for surgery, and long-term seizure freedom is only achieved in half the cases. Recently, several computational approaches have been proposed to support presurgical planning. Typically, these approaches use a dynamic network model to explore the potential impact of surgical resection in silico. The network component of the model is informed by clinical imaging data and is considered static thereafter. This assumption critically overlooks the plasticity of the brain and, therefore, how continued evolution of the brain network post-surgery may impact upon the success of a resection in the longer term. In this work, we use a simplified dynamic network model, which describes transitions to seizures, to systematically explore how the network structure influences seizure propensity, both before and after virtual resections. We illustrate key results in small networks, before extending our findings to larger networks. We demonstrate how the evolution of brain networks post resection can result in a return to increased seizure propensity. Our results effectively determine the robustness of a given resection to possible network reconfigurations and so provide a potential strategy for optimizing long-term seizure freedom.

Antipsychotic drugs (APDs) have a variety of important therapeutic applications for neuropsychiatric disorders. However, they are routinely prescribed off-label across all age categories, a controversial practice given their potential for producing metabolic and extrapyramidal side effects. Evidence also suggests that chronic treatment with some APDs may lead to impairments in cognition and decreases in brain volume, although these findings are controversial. The purpose of the studies described here was to evaluate one of the most commonly prescribed APDs, quetiapine, for chronic effects on recognition memory, brain-derived neurotrophic factor (BDNF), its precursor proBDNF, as well as relevant downstream signaling molecules that are known to influence neuronal plasticity and cognition. Multiple cohorts of adult rats were treated with quetiapine (25.0 mg/kg/day) for 30 or 90 days in their drinking water then evaluated for drug effects on motor function in a catalepsy assessment, recognition memory in a spontaneous novel object recognition (NOR) task, and BDNF-related signaling molecules in the post mortem hippocampus via Western Blot. The results indicated that oral quetiapine at a dose that did not induce catalepsy, led to time-dependent impairments in NOR performance, increases in the proBDNF/BDNF ratio, and decreases in Akt and CREB phosphorylation in the hippocampus. These results indicate that chronic treatment with quetiapine has the potential to adversely affect recognition memory and neurotrophin-related signaling molecules that support synaptic plasticity and cognitive function. Given the widespread use this APD across multiple conditions and patient populations, such long-term effects observed in animals should be considered., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The International League Against Epilepsy (ILAE) groups seizures into "focal", "generalized" and "unknown" based on whether the seizure onset is confined to a brain region in one hemisphere, arises in several brain region simultaneously, or is not known, respectively. This separation fails to account for the rich diversity of clinically and experimentally observed spatiotemporal patterns of seizure onset and even less so for the properties of the brain networks generating them. We consider three different patterns of domino-like seizure onset in Idiopathic Generalized Epilepsy (IGE) and present a novel approach to classification of seizures. To understand how these patterns are generated on networks requires understanding of the relationship between intrinsic node dynamics and coupling between nodes in the presence of noise, which currently is unknown. We investigate this interplay here in the framework of domino-like recruitment across a network. In particular, we use a phenomenological model of seizure onset with heterogeneous coupling and node properties, and show that in combination they generate a range of domino-like onset patterns observed in the IGE seizures. We further explore the individual contribution of heterogeneous node dynamics and coupling by interpreting in-vitro experimental data in which the speed of onset can be chemically modulated. This work contributes to a better understanding of possible drivers for the spatiotemporal patterns observed at seizure onset and may ultimately contribute to a more personalized approach to classification of seizure types in clinical practice., Competing Interests: The authors have declared that no competing interests exist.

NMDA receptors containing GluN2D subunits are expressed in the subthalamic nucleus and external globus pallidus, key nuclei of the indirect and hyperdirect pathways of the basal ganglia. This circuitry integrates cortical input with dopaminergic signaling to select advantageous behaviors among available choices. In the experiments described here, we characterized the effects of PTC-174, a novel positive allosteric modulator (PAM) of GluN2D subunit-containing NMDA receptors, on response control regulated by this circuitry. The indirect pathway suppresses less advantageous behavioral choices, a manifestation of which is suppression of locomotor activity in rats. Systemic administration of PTC-174 produced a dose-dependent reduction in activity in rats placed in a novel open field or administered the stimulants MK-801 or amphetamine. The hyperdirect pathway controls release of decisions from the basal ganglia to the cortex to optimize choice processing. Such response control was modeled in rats as premature responding in the 5-choice serial reaction time (5-CSRT) task. PTC-174 produced a dose-dependent reduction in premature responding in this task. These data suggest that potentiation of GluN2D receptor activity by PTC-174 facilitates the complex basal ganglia information processing that underlies response control. The behavioral effects occurred at estimated free PTC-174 brain concentrations predicted to induce 10-50% increases in GluN2D activity. The present findings suggest the potential of GluN2D PAMs to modulate basal ganglia function and to treat neurological disorders related to dysfunctional response control., Competing Interests: Declaration of competing interest Volkmann, and Menniti are co-inventors on patent applications that claim PTC-174. The intellectual property rights to PTC-174 are assigned to Cadent Pharmaceuticals and Volkmann and Menniti own stock in this company. All other authors have no commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Schizophrenia is a devastating mental illness and its effective treatment is among the most challenging issues in psychiatry. The symptoms of schizophrenia are heterogeneous ranging from positive symptoms (e.g., delusions, hallucinations) to negative symptoms (e.g., anhedonia, social withdrawal) to cognitive dysfunction. Antipsychotics are effective at ameliorating positive symptoms in some patients; however, they are not reliably effective at improving the negative symptoms or cognitive impairments. The inability to address the cognitive impairments is a particular concern since they have the greatest long-term impact on functional outcomes. While decades of research have been devoted to the development of pro-cognitive agents for schizophrenia, to date, no drug has been approved for clinical use. Converging behavioral, neurobiological, and genetic evidence led to the identification of the α7-nicotinic acetylcholine receptor (α7-nAChR) as a therapeutic target several years ago and there is now extensive preclinical evidence that α7-nAChR ligands have pro-cognitive effects and other properties that should be beneficial to schizophrenia patients. However, like the other pro-cognitive strategies, no α7-nAChR ligand has been approved for clinical use in schizophrenia thus far. In this review, several topics are discussed that may impact the success of α7-nAChR ligands as pro-cognitive agents for schizophrenia including the translational value of the animal models used, clinical trial design limitations, confounding effects of polypharmacy, dose-effect relationships, and chronic versus intermittent dosing considerations. Determining the most optimal pharmacologic strategy at α7-nAChRs: agonist, positive allosteric modulator, or potentially even receptor antagonist is also discussed. article is part of the special issue on 'Contemporary Advances in Nicotine Neuropharmacology'., Competing Interests: Declaration of competing interest The authors do not declare any conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

This brief report describes the rapid deployment of a real-time electronic tracking board for all hospitals in the state of Oregon. In preparation for the coronavirus disease 2019 surge on hospital resources, and in collaboration across health systems, with health authorities and an industry partner, we combined existing infrastructures to create the first automated tracking board for our entire state, including bed types by health system and geographic area, and with granularity to the individual unit level for each participating hospital. At the time of submission, we have a live snapshot of 87% of beds in the state, including real-time ventilator data across eight health systems. The tracking board allows for rapid assessment of available bed and ventilator resources and pulls electronic health record data that is created through normal care processes rather than relying upon manual entry. It is updated every 5 minutes and is drillable from state to unit level. Together these factors make the data actionable, which is essential in a crisis. The new tracking system integrates seamlessly with our preexisting statewide, manually updated tracking board via bidirectional data sharing to ensure existing processes across the state can continue. This new tool allows any health system in our state to visualize occupancy by type and location in real time. Amid pandemic uncertainty, having a reliable tool for tracking critical hospital resources will enhance our statewide ability to maintain healthcare functionality in a world with coronavirus disease 2019., Competing Interests: Mr. Terry is employed by GE Healthcare and owns stock options. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2020 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.)

Current explanatory concepts suggest seizures emerge from ongoing dynamics of brain networks. It is unclear how brain network properties determine focal or generalised seizure onset, or how network properties can be described in a clinically-useful manner. Understanding network properties would cast light on seizure-generating mechanisms and allow to quantify to which extent a seizure is focal or generalised. Functional brain networks were estimated in segments of scalp-EEG without interictal discharges (68 people with epilepsy, 38 controls). Simplified brain dynamics were simulated using a computer model. We introduce: Critical Coupling (C c ), the ability of a network to generate seizures; Onset Index (OI), the tendency of a region to generate seizures; and Participation Index (PI), the tendency of a region to become involved in seizures. C c was lower in both patient groups compared with controls. OI and PI were more variable in focal-onset than generalised-onset cases. In focal cases, the regions with highest OI and PI corresponded to the side of seizure onset. Properties of interictal functional networks from scalp EEG can be estimated using a computer model and used to predict seizure likelihood and onset patterns. This may offer potential to enhance diagnosis through quantification of seizure type using inter-ictal recordings.

Organophosphates (OPs) are valuable as pesticides in agriculture and for controlling deadly vector-borne illnesses; however, they are highly toxic and associated with many deleterious health effects in humans including long-term neurological impairments. Antidotal treatment regimens are available to combat the symptoms of acute OP toxicity, which result from the irreversible inhibition of acetylcholinesterase (AChE). However, there are no established treatments for the long-term neurological consequences of OP exposure. In addition to AChE, OPs can negatively affect multiple protein targets as well as biological processes such as axonal transport. Given the fundamental nature of axonal transport to neuronal health, we rationalized that this process might serve as a general focus area for novel therapeutic strategies against OP toxicity. In the studies described here, we employed a multi-target, phenotypic screening, and drug repurposing strategy for the evaluations of potential novel OP-treatments using a primary neuronal culture model and time-lapse live imaging microscopy. Two multi-target compounds, lithium chloride (LiCl) and methylene blue (MB), which are FDA-approved for other indications, were evaluated for their ability to prevent the negative effects of the OP, diisopropylfluorophosphate (DFP) on axonal transport. The results indicated that both LiCl and MB prevented DFP-induced impairments in anterograde and retrograde axonal transport velocities in a concentration dependent manner. While in vivo studies will be required to confirm our in vitro findings, these experiments support the potential of LiCl and MB as repurposed drugs for the treatment of the long-term neurological deficits associated with OP exposure (currently an unmet medical need)., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Epileptic seizures are generally classified as either focal or generalized. It had been traditionally assumed that focal seizures imply localized brain abnormalities, whereas generalized seizures involve widespread brain pathologies. However, recent evidence suggests that large-scale brain networks are involved in the generation of focal seizures, and generalized seizures can originate in localized brain regions. Herein we study how network structure and tissue heterogeneities underpin the emergence of focal and widespread seizure dynamics. Mathematical modeling of seizure emergence in brain networks enables the clarification of the characteristics responsible for focal and generalized seizures. We consider neural mass network dynamics of seizure generation in exemplar synthetic networks and we measure the variance in ictogenicity across the network. Ictogenicity is defined as the involvement of network nodes in seizure activity, and its variance is used to quantify whether seizure patterns are focal or widespread across the network. We address both the influence of network structure and different excitability distributions across the network on the ictogenic variance. We find that this variance depends on both network structure and excitability distribution. High variance, i.e., localized seizure activity, is observed in networks highly heterogeneous with regard to the distribution of connections or excitabilities. However, networks that are both heterogeneous in their structure and excitability can underlie the emergence of generalized seizures, depending on the interplay between structure and excitability. Thus, our results imply that the emergence of focal and generalized seizures is underpinned by an interplay between network structure and excitability distribution., (Copyright © 2020 Lopes, Junges, Woldman, Goodfellow and Terry.)

Antipsychotic drugs (APDs) are essential for the treatment of schizophrenia and other neuropsychiatric illnesses such as bipolar disease. However, they are also extensively prescribed off-label for many other conditions, a practice that is controversial given their potential for long-term side effects. There is clinical and preclinical evidence that chronic treatment with some APDs may lead to impairments in cognition and decreases in brain volume, although the molecular mechanisms of these effects are unknown. The purpose of the rodent studies described here was to evaluate a commonly prescribed APD, risperidone, for chronic effects on recognition memory, brain-derived neurotrophic factor (BDNF), its precursor proBDNF, as well as relevant downstream signaling molecules that are known to influence neuronal plasticity and cognition. Multiple cohorts of adult rats were treated with risperidone (2.5 mg/kg/day) or vehicle (dilute acetic acid solution) in their drinking water for 30 or 90 days. Subjects were then evaluated for drug effects on recognition memory in a spontaneous novel object recognition task and protein levels of BDNF-related signaling molecules in the hippocampus and prefrontal cortex. The results indicated that depending on the treatment period, a therapeutically relevant daily dose of risperidone impaired recognition memory and increased the proBDNF/BDNF ratio in the hippocampus and prefrontal cortex. Risperidone treatment also led to a decrease in Akt and CREB phosphorylation in the prefrontal cortex. These results indicate that chronic treatment with a commonly prescribed APD, risperidone, has the potential to adversely affect recognition memory and neurotrophin-related signaling molecules that support synaptic plasticity and cognitive function., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Objective: The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework to interrogate scalp EEG and determine epilepsy lateralization to aid in electrode implantation., Methods: We use eLORETA to map source activities from seizure epochs recorded from scalp EEG and consider 15 regions of interest (ROIs). Functional networks are then constructed using the phase-locking value and studied using a mathematical model. By removing different ROIs from the network and simulating their impact on the network's ability to generate seizures in silico, the framework provides predictions of epilepsy lateralization. We consider 15 individuals from the EPILEPSIAE database and study a total of 62 seizures. Results were assessed by taking into account actual intracranial implantations and surgical outcome., Results: The framework provided potentially useful information regarding epilepsy lateralization in 12 out of the 15 individuals (p=0.02, binomial test)., Conclusions: Our results show promise for the use of this framework to better interrogate scalp EEG to determine epilepsy lateralization., Significance: The framework may aid clinicians in the decision process to define where to implant electrodes for intracranial monitoring., (Copyright © 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Atomoxetine is a norepinephrine reuptake inhibitor and FDA-approved treatment for attention deficit/hyperactivity disorder (ADHD) in children, adolescents, and adults. While there is some evidence that atomoxetine may improve additional domains of cognition beyond attention in both young adults and aged individuals, this subject has not been extensively investigated. Here, we evaluated atomoxetine (in low mg/kg doses) in a variable stimulus duration (vSD) and a variable intertrial interval (vITI) version of the five choice-serial reaction time task (5C-SRTT), and an eight-arm radial arm maze (RAM) procedure in young-adult rats. The compound was further evaluated (in μg/kg-low mg/kg doses) along with nicotine (as a reference compound) and the Alzheimer's disease treatment donepezil in a distractor version of a delayed match to sample task (DMTS-D) in aged monkeys (mean age = 21.8 years). Atomoxetine (depending on the dose) improved accuracy (sustained attention) as well as behaviors related to impulsivity, compulsivity and cognitive inflexibility in both the vSD and vITI tasks and it improved spatial reference memory in the RAM. In the DMTS-D task, both nicotine and atomoxetine, but not donepezil attenuated the effects of the distractor on accuracy at short delays (non-spatial working/short term memory). However, combining sub-effective doses of atomoxetine and donepezil did enhance DMTS-D accuracy indicating the potential of using atomoxetine as an adjunctive treatment with donepezil. Collectively, these animal studies support the further evaluation of atomoxetine as a repurposed drug for younger adults as well older individuals who suffer from deficits in attention, memory and other components of executive function., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Large-scale brain networks are increasingly recognized as important for the generation of seizures in epilepsy. However, how a network evolves from a healthy state through the process of epileptogenesis remains unclear. To address this question, here, we study longitudinal epicranial background EEG recordings (30 electrodes, EEG free from epileptiform activity) of a mouse model of mesial temporal lobe epilepsy. We analyze functional connectivity networks and observe that over the time course of epileptogenesis the networks become increasingly asymmetric. Furthermore, computational modelling reveals that a set of nodes, located outside of the region of initial insult, emerges as particularly important for the network dynamics. These findings are consistent with experimental observations, thus demonstrating that ictogenic mechanisms can be revealed on the EEG, that computational models can be used to monitor unfolding epileptogenesis and that both the primary focus and epileptic network play a role in epileptogenesis., (Copyright © 2019 Słowiński et al.)

Seizure onset in epilepsy can usually be classified as focal or generalized, based on a combination of clinical phenomenology of the seizures, EEG recordings and MRI. This classification may be challenging when seizures and interictal epileptiform discharges are infrequent or discordant, and MRI does not reveal any apparent abnormalities. To address this challenge, we introduce the concept of Ictogenic Spread (IS) as a prediction of how pathological electrical activity associated with seizures will propagate throughout a brain network. This measure is defined using a person-specific computer representation of the functional network of the brain, constructed from interictal EEG, combined with a computer model of the transition from background to seizure-like activity within nodes of a distributed network. Applying this method to a dataset comprising scalp EEG from 38 people with epilepsy (17 with genetic generalized epilepsy (GGE), 21 with mesial temporal lobe epilepsy (mTLE)), we find that people with GGE display a higher IS in comparison to those with mTLE. We propose IS as a candidate computational biomarker to classify focal and generalized epilepsy using interictal EEG.

Mathematical modelling has been widely used to predict the effects of perturbations to brain networks. An important example is epilepsy surgery, where the perturbation in question is the removal of brain tissue in order to render the patient free of seizures. Different dynamical models have been proposed to represent transitions to ictal states in this context. However, our choice of which mathematical model to use to address this question relies on making assumptions regarding the mechanism that defines the transition from background to the seizure state. Since these mechanisms are unknown, it is important to understand how predictions from alternative dynamical descriptions compare. Herein we evaluate to what extent three different dynamical models provide consistent predictions for the effect of removing nodes from networks. We show that for small, directed, connected networks the three considered models provide consistent predictions. For larger networks, predictions are shown to be less consistent. However consistency is higher in networks that have sufficiently large differences in ictogenicity between nodes. We further demonstrate that heterogeneity in ictogenicity across nodes correlates with variability in the number of connections for each node.

At least one-third of all people with epilepsy have seizures that remain poorly controlled despite an increasing number of available anti-epileptic drugs (AEDs). Often, there is an initial good response to a newly introduced AED, which may last up to months, eventually followed by the return of seizures thought to be due to the development of tolerance. We introduce a framework within which the interplay between AED response and brain networks can be explored to understand the development of tolerance. We use a computer model for seizure generation in the context of dynamic networks, which allows us to generate an 'in silico' electroencephalogram (EEG). This allows us to study the effect of changes in excitability network structure and intrinsic model properties on the overall seizure likelihood. Within this framework, tolerance to AEDs - return of seizure-like activity - may occur in 3 different scenarios: 1) the efficacy of the drug diminishes while the brain network remains relatively constant; 2) the efficacy of the drug remains constant, but connections between brain regions change; 3) the efficacy of the drug remains constant, but the intrinsic excitability within brain regions varies dynamically. We argue that these latter scenarios may contribute to a deeper understanding of how drug resistance to AEDs may occur., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Epilepsy surgery is a clinical procedure that aims to remove the brain tissue responsible for the emergence of seizures, the epileptogenic zone (EZ). It is preceded by an evaluation to determine the brain tissue that must be resected. The identification of the seizure onset zone (SOZ) from intracranial EEG recordings stands as one of the key proxies for the EZ. In this study we used computational models of epilepsy to assess to what extent the SOZ may or may not represent the EZ. We considered a set of different synthetic networks (e.g., regular, small-world, random, and scale-free networks) to represent large-scale brain networks and a phenomenological network model of seizure generation. In the model, the SOZ was inferred from the seizure likelihood (SL), a measure of the propensity of single nodes to produce epileptiform dynamics, whilst a surgery corresponded to the removal of nodes and connections from the network. We used the concept of node ictogenicity (NI) to quantify the effectiveness of each node removal on reducing the network's propensity to generate seizures. This framework enabled us to systematically compare the SOZ and the seizure control achieved by each considered surgery. Specifically, we compared the distributions of SL and NI across different networks. We found that SL and NI were concordant when all nodes were similarly ictogenic, whereas when there was a small fraction of nodes with high NI, the SL was not specific at identifying these nodes. We further considered networks with heterogeneous node excitabilities, i.e., nodes with different susceptibilities of being engaged in seizure activity, to understand how such heterogeneity may affect the relationship between SL and NI. We found that while SL and NI are concordant when there is a small fraction of hyper-excitable nodes in a network that is otherwise homogeneous, they do diverge if the network is heterogeneous, such as in scale-free networks. We observe that SL is highly dependent on node excitabilities, whilst the effect of surgical resections as revealed by NI is mostly determined by network structure. Together our results suggest that the SOZ is not always a good marker of the EZ.

The bed nucleus of the stria terminalis (BNST) is a sexually dimorphic brain region which plays a key role in stress, anxiety, and anxiety-related disorders. Human females have an increased susceptibility to anxiety-related disorders, however the physiological basis of this is not fully understood. Here we examined the effect of the oestrous cycle and sex on the electrophysiological properties of Type I and Type II cells in the anterolateral area of the BNST (BNST ALG ) in unstressed animals. There was no significant effect of oestrous cycle on any of the parameters examined in either cell type. Compared to males, the female cohort had lower capacitance in Type I cells while having a higher capacitance in Type II cells. Type II cells also displayed decreased excitability in the female cohort. In order to confirm the effect of these populations on stress and anxiety, a correlation with behaviour on the elevated zero maze was carried out. We observed that increased excitability in Type II neurons correlated with a decrease in anxiety-like behaviour. These sex-specific differences in excitability may contribute to altered susceptibility to anxiety-related disorders.

Impaired social interaction is a key feature of several major psychiatric disorders including depression, autism, and schizophrenia. While, anatomically, the prefrontal cortex (PFC) is known as a key regulator of social behavior, little is known about the cellular mechanisms that underlie impairments of social interaction. One etiological mechanism implicated in the pathophysiology of the aforementioned psychiatric disorders is cellular stress and consequent adaptive responses in the endoplasmic reticulum (ER) that can result from a variety of environmental and physical factors. The ER is an organelle that serves essential roles in protein modification, folding, and maturation of proteins; however, the specific role of ER stress in altered social behavior is unknown. In this study, treatment with tunicamycin, an ER stress inducer, enhanced the phosphorylation level of inositol-requiring ER-to-nucleus signal kinase 1 (IRE1) and increased X-box-binding protein 1 (XBP1) mRNA splicing activity in the mouse PFC, whereas inhibition of IRE1/XBP1 pathway in PFC by a viral particle approach attenuated social behavioral deficits caused by tunicamycin treatment. Reduced estrogen receptor beta (ERβ) protein levels were found in the PFC of male mice following tunicamycin treatment. Pretreatment with an ERβ specific agonist, ERB-041 significantly attenuated tunicamycin-induced deficits in social behavior, and activation of IRE1/XBP1 pathway in mouse PFC. Moreover, ERB-041 inhibited tunicamycin-induced increases in functional connectivity between PFC and hippocampus in male mice. Together, these results show that ERβ agonist attenuates ER stress-induced deficits in social behavior through the IRE-1/XBP1 pathway.

The term organophosphate (OP) refers to a diverse group of chemicals that are found in hundreds of products worldwide. As pesticides, their most common use, OPs are clearly beneficial for agricultural productivity and the control of deadly vector-borne illnesses. However, as a consequence of their widespread use, OPs are now among the most common synthetic chemicals detected in the environment as well as in animal and human tissues. This is an increasing environmental concern because many OPs are highly toxic and both accidental and intentional exposures to OPs resulting in deleterious health effects have been documented for decades. Some of these deleterious health effects include a variety of long-term neurological and psychiatric disturbances including impairments in attention, memory, and other domains of cognition. Moreover, some chronic illnesses that manifest these symptoms such as Gulf War Illness and Aerotoxic Syndrome have (at least in part) been attributed to OP exposure. In addition to acute acetylcholinesterase inhibition, OPs may affect a number of additional targets that lead to oxidative stress, axonal transport deficits, neuroinflammation, and autoimmunity. Some of these targets could be exploited for therapeutic purposes. The purpose of this review is thus to: 1) describe the important uses of organophosphate (OP)-based compounds worldwide, 2) provide an overview of the various risks and toxicology associated with OP exposure, particularly long-term neurologic and psychiatric symptoms, 3) discuss mechanisms of OP toxicity beyond cholinesterase inhibition, 4) review potential therapeutic strategies to reverse the acute toxicity and long term deleterious effects of OPs., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Organophosphates (OPs) are found in hundreds of valuable agricultural, industrial, and commercial compounds; however, they have also been associated with a variety of harmful effects in humans. The acute toxicity of OPs is attributed to the inhibition of the enzyme acetylcholinesterase (AChE); however, this mechanism may not account for all of the deleterious neurologic effects of OPs, especially at doses that produce no overt signs of acute toxicity. In this study, the effects of two weeks of daily subcutaneous exposure to the OP-nerve agent diisopropylfluorophosphate (DFP) in doses ranging from 0.125-0.500 mg/kg on whole brain volume, white matter, and gray matter integrity were evaluated in post mortem tissues using histology and magnetic resonance imaging (MRI) methods. The effects of DFP on axonal transport in the brains of living rats were evaluated using a manganese-enhanced MRI (MEMRI) method. DFP was associated with dose-dependent impairments in red blood cell and brain AChE (down to 29 and 18% of control, respectively at the highest dose), 24 h after the last injection. However, there were no visible signs of cholinergic toxicity noted in any portion of the study. Moreover, histological and MRI analysis of post mortem brains did not reveal any pronounced alterations of whole brain, white matter, or gray matter volumes associated with DFP. Electron microscopy did reveal a DFP-related increase in structural disruptions of myelinated axons (i.e., decompactions) in the fimbria region on the corpus callosum. MEMRI indicated that DFP was also associated with dose-dependent decreases in axonal transport in the brains of living rats, an effect that was also present after a 30-day (DFP-free) washout period, when AChE was not significantly inhibited. These results indicate that repeated exposures to the nerve agent, DFP at doses that are below the threshold for acute toxicity, can result in alterations in myelin structure and persistent decreases in axonal transport in the rodent brain. These observations could explain some of the long-term neurological deficits that have been observed in humans who have been repeatedly exposed to OPs., (Copyright © 2018 Elsevier B.V. All rights reserved.)

While impairments of cognition in schizophrenia have the greatest impact on long-term functional outcome, the currently prescribed treatments, antipsychotic drugs (APDs), do not effectively improve cognition. Moreover, while more than 20 years have been devoted to the development of new drugs to treat cognitive deficits in schizophrenia, none have been approved to date. One area that has not been given proper attention at the preclinical or clinical stage of drug development is the chronic medication history of the test subject. Hence, very little is known about how chronic treatment with drugs that affect multiple receptors like APDs influence the response to a potential pro-cognitive agent. Therefore, the purpose of this study was to evaluate the α7 nicotinic acetylcholine receptor (α7 nAChR) partial agonist, tropisetron in rats chronically treated with APDs with distinct pharmacological profiles. Rats were treated orally with either risperidone (2.5 mg/kg/day) or quetiapine (25.0 mg/kg/day) for 30 or 90 days and then an acute injection of vehicle or tropisetron (3.0 mg/kg) was administered before training in a novel object recognition (NOR) task. After a 48 h delay (when recollection of the familiar object was impaired in vehicle-treated animals) neither 30 nor 90 days of risperidone or quetiapine treatment improved NOR performance. In contrast, tropisetron markedly improved NOR performance in rats treated with either APD for 30 or 90 days. These animal data reinforce the argument that two commonly prescribed APDs are not pro-cognitive agents and that α7 nAChR ligands like tropisetron have potential as adjunctive treatments in schizophrenia., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Nearly 30 years of experimental evidence supports the argument that ligands of nicotinic acetylcholine receptors (nAChRs) have potential as therapeutic agents. However, as in the famous Lewis Carroll novel "Alice in Wonderland", there have been many unexpected adventures along the pathway of development, and few nAChR ligands have been approved for any clinical condition to date with the exception of nicotine dependence. The recent failures of nAChR ligands in AD and schizophrenia clinical trials have reduced enthusiasm for this therapeutic strategy and many pharmaceutical companies have now abandoned this field of research. As with other clinical failures, multiple questions arise as to the basis for the failure. More generic questions focus on a potential translational gap between the animal models used and the human clinical condition they are meant to simulate, or the clinical trial mindset that large Ns have to be achieved for statistical power (often requiring multiple trial sites) as opposed to smaller patient cohorts at limited sites where conditions can be better controlled and replicated. More specific to the nAChR field are questions about subtype selectivity, dose selection, whether an agonist, antagonist, or allosteric modulator strategy is best, etc. The purpose of this review is to discuss each of these questions, but also to provide a brief overview of the remarkable progress that has been made over the last three decades in our understanding of this unique ligand-gated ion channel and how this new knowledge may help us improve drug development successes in the future., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understand how dynamics change when parameters are varied. Despite being considered low dimensional in comparison to micro-scale, neuronal network models, with regards to understanding the relationship between parameters and dynamics, NMMs are still prohibitively high dimensional for classical approaches such as numerical continuation. Therefore, we need alternative methods to characterise dynamics of NMMs in high dimensional parameter spaces. Here, we introduce a statistical framework that enables the efficient exploration of the relationship between model parameters and selected features of the simulated, emergent model dynamics of NMMs. We combine the classical machine learning approaches of trees and random forests to enable studying the effect that varying multiple parameters has on the dynamics of a model. The method proceeds by using simulations to transform the mathematical model into a database. This database is then used to partition parameter space with respect to dynamic features of interest, using random forests. This allows us to rapidly explore dynamics in high dimensional parameter space, capture the approximate location of qualitative transitions in dynamics and assess the relative importance of all parameters in the model in all dimensions simultaneously. We apply this method to a commonly used NMM in the context of transitions to seizure dynamics. We find that the inhibitory sub-system is most crucial for the generation of seizure dynamics, confirm and expand previous findings regarding the ratio of excitation and inhibition, and demonstrate that previously overlooked parameters can have a significant impact on model dynamics. We advocate the use of this method in future to constrain high dimensional parameter spaces enabling more efficient, person-specific, model calibration.

Recent studies have shown that mathematical models can be used to analyze brain networks by quantifying how likely they are to generate seizures. In particular, we have introduced the quantity termed brain network ictogenicity (BNI), which was demonstrated to have the capability of differentiating between functional connectivity (FC) of healthy individuals and those with epilepsy. Furthermore, BNI has also been used to quantify and predict the outcome of epilepsy surgery based on FC extracted from pre-operative ictal intracranial electroencephalography (iEEG). This modeling framework is based on the assumption that the inferred FC provides an appropriate representation of an ictogenic network, i.e., a brain network responsible for the generation of seizures. However, FC networks have been shown to change their topology depending on the state of the brain. For example, topologies during seizure are different to those pre- and post-seizure. We therefore sought to understand how these changes affect BNI. We studied peri-ictal iEEG recordings from a cohort of 16 epilepsy patients who underwent surgery and found that, on average, ictal FC yield higher BNI relative to pre- and post-ictal FC. However, elevated ictal BNI was not observed in every individual, rather it was typically observed in those who had good post-operative seizure control. We therefore hypothesize that elevated ictal BNI is indicative of an ictogenic network being appropriately represented in the FC. We evidence this by demonstrating superior model predictions for post-operative seizure control in patients with elevated ictal BNI.

Intrinsic neuronal excitability has been reported to change during normal aging. The bed nucleus of the stria terminalis (BNST), a limbic forebrain structure, is involved in fear, stress and anxiety; behavioral features that exhibit age-dependent properties. To examine the effect of aging on intrinsic neuronal properties in BNST we compared patch clamp recordings from cohorts of female mice at two ages, 3-4 months (Young) and 29-30 months (Aged) focusing on 2 types of BNST neurons. Aged Type I neurons exhibited a hyperpolarized resting membrane potential (RMP) of circa -80 mV compared to circa -70 mV in the Young. A key finding in this study is a hyper-excitability of Type II neurons with age reflected in an increase in firing frequency in response to depolarizing current injections; activation of Type II neurons is believed to dampen anxiety like responses. Such age-related changes in intrinsic neurophysiological function are likely to modulate how the limbic system, acting via BNST, shapes function in the HPA-axis.

Acetylcholine in the neocortex is critical for executive function [1-3]. Degeneration of cholinergic neurons in aging and Alzheimer's dementia is commonly treated with cholinesterase inhibitors [4-7]; however, these are modestly effective and are associated with side effects that preclude effective dosing in many patients [8]. Electrical activation of the nucleus basalis (NB) of Meynert, the source of neocortical acetylcholine [9, 10], provides a potential method of improving cholinergic activation [11, 12]. Here we tested whether NB stimulation would improve performance of a working memory task in a nonhuman primate model. Unexpectedly, intermittent stimulation proved to be most beneficial (60 pulses per second, for 20 s every minute), whereas continuous stimulation often impaired performance. Pharmacological experiments confirmed that the effects depended on cholinergic activation. Donepezil, a cholinesterase inhibitor, restored performance in animals impaired by continuous stimulation but did not improve performance further during intermittent stimulation. Intermittent stimulation was rendered ineffective by either nicotinic or muscarinic receptor antagonists. In the months after stimulation began, performance also improved in sessions without stimulation. Our results reveal that intermittent NB stimulation can improve working memory, a finding that has implications for restoring cognitive function in aging and Alzheimer's dementia., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Chlorpyrifos (CPF) is an extensively used organophosphorus pesticide that has recently come under increasing scrutiny due to environmental health concerns particularly its association with neurodevelopmental defects. While the insecticidal actions and acute toxicity of CPF are attributed to its oxon metabolite (CPO) which potently inhibits the cholinergic enzyme acetylcholinesterase (AChE), there is significant evidence that CPF, CPO, and other organophosphates may affect a variety of neuronal targets and processes that are not directly related to AChE. Previously, in adult rat sciatic nerves ex vivo and postnatal neurons from rats in vitro we observed that CPF and CPO impaired the movements of vesicles and mitochondria in axons. Here, in embryonic neurons from rats in culture, we evaluated 24h exposures to CPF and CPO across picomolar to micromolar concentrations for effects on fast axonal transport of membrane bound organelles (MBOs) that contained the amyloid precursor protein (APP) tagged with the fluorescent marker, Dendra2 (APPDendra2). The most notable observations of this study were concentration-dependent decreases in the velocity and percentage of MBOs moving in the anterograde direction, an increase in the number of stationary MBOs, and an increased frequency of pauses associated with both CPF and CPO. These effects occurred at concentrations that did not significantly inhibit AChE activity, they were not blocked by cholinergic receptor antagonists, and they were not associated with compromised cell viability. These effects of CPF and CPO may be significant given the importance of axonal transport to neuronal development as well the function of fully developed neurons., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Surgery is a therapeutic option for people with epilepsy whose seizures are not controlled by anti-epilepsy drugs. In pre-surgical planning, an array of data modalities, often including intra-cranial EEG, is used in an attempt to map regions of the brain thought to be crucial for the generation of seizures. These regions are then resected with the hope that the individual is rendered seizure free as a consequence. However, post-operative seizure freedom is currently sub-optimal, suggesting that the pre-surgical assessment may be improved by taking advantage of a mechanistic understanding of seizure generation in large brain networks. Herein we use mathematical models to uncover the relative contribution of regions of the brain to seizure generation and consequently which brain regions should be considered for resection. A critical advantage of this modeling approach is that the effect of different surgical strategies can be predicted and quantitatively compared in advance of surgery. Herein we seek to understand seizure generation in networks with different topologies and study how the removal of different nodes in these networks reduces the occurrence of seizures. Since this a computationally demanding problem, a first step for this aim is to facilitate tractability of this approach for large networks. To do this, we demonstrate that predictions arising from a neural mass model are preserved in a lower dimensional, canonical model that is quicker to simulate. We then use this simpler model to study the emergence of seizures in artificial networks with different topologies, and calculate which nodes should be removed to render the network seizure free. We find that for scale-free and rich-club networks there exist specific nodes that are critical for seizure generation and should therefore be removed, whereas for small-world networks the strategy should instead focus on removing sufficient brain tissue. We demonstrate the validity of our approach by analysing intra-cranial EEG recordings from a database comprising 16 patients who have undergone epilepsy surgery, revealing rich-club structures within the obtained functional networks. We show that the postsurgical outcome for these patients was better when a greater proportion of the rich club was removed, in agreement with our theoretical predictions.

The hypothalamic-pituitary-adrenal axis is a dynamic system regulating glucocorticoid hormone synthesis in the adrenal glands. Many key factors within the adrenal steroidogenic pathway have been identified and studied, but little is known about how these factors function collectively as a dynamic network of interacting components. To investigate this, we developed a mathematical model of the adrenal steroidogenic regulatory network that accounts for key regulatory processes occurring at different timescales. We used our model to predict the time evolution of steroidogenesis in response to physiological adrenocorticotropic hormone (ACTH) perturbations, ranging from basal pulses to larger stress-like stimulations (e.g., inflammatory stress). Testing these predictions experimentally in the rat, our results show that the steroidogenic regulatory network architecture is sufficient to respond to both small and large ACTH perturbations, but coupling this regulatory network with the immune pathway is necessary to explain the dissociated dynamics between ACTH and glucocorticoids observed under conditions of inflammatory stress., Competing Interests: The authors declare no conflict of interest.

Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is commonly initiated by ectopic beats originating from a small myocardial sleeve extending over the pulmonary veins. Pulmonary vein isolation therapy attempts to isolate the pulmonary veins from the left atrium by ablating tissue, commonly by using radiofrequency ablation. During this procedure, the cardiologist records electrical activity using a lasso catheter, and the activation pattern recorded is used as a guide toward which regions to ablate. However, poor contact between electrode and tissue can lead to important regions of electrical activity not being recorded in clinic. We reproduce these signals through the use of a phenomenological model of the cardiac action potential on a cylinder, which we fit to post-AF atrial cells, and model the bipolar electrodes of the lasso catheter by an approximation of the surface potential. The resulting activation pattern is validated by direct comparison with those of clinical recordings. A potential application of the model is to reconstruct the missing electrical activity, minimizing the impact of the information loss on the clinical procedure, and we present results to demonstrate this.

Tropisetron, a 5-HT 3 receptor antagonist commonly prescribed for chemotherapy-induced nausea and vomiting also exhibits high affinity, partial agonist activity at α7 nicotinic acetylcholine receptors (α7 nAChRs). α7 nAChRs are considered viable therapeutic targets for neuropsychiatric disorders such as Alzheimer's disease (AD). Here we further explored the nAChR pharmacology of tropisetron to include the homomeric α7 nAChR and recently characterized heteromeric α7β2 nAChR (1:10 ratio) and we evaluated its cognitive effects in young and aged animals. Electrophysiological studies on human nAChRs expressed in Xenopus oocytes confirmed the partial agonist activity of tropisetron at α7 nAChRs (EC 50 ∼2.4 μM) with a similar effect at α7β2 nAChRs (EC 50 ∼1.5 μM). Moreover, currents evoked by irregular pulses of acetylcholine (40 μM) at α7 and α7β2 nAChRs were enhanced during sustained exposure to low concentrations of tropisetron (10 and 30 nM) indicative of a "priming" or co-agonist effect. Tropisetron (0.1-10 mg/kg) improved novel object recognition performance in young Sprague-Dawley rats and in aged Fischer rats. In aged male and female rhesus monkeys, tropisetron (0.03-1 mg/kg) produced a 17% increase from baseline levels in delayed match to sample long delay accuracy while combination of non-effective doses of donepezil (0.1 mg/kg) and tropisetron (0.03 and 0.1 mg/kg) produced a 24% change in accuracy. Collectively, these animal experiments indicate that tropisetron enhances cognition and has the ability to improve the effective dose range of currently prescribed AD therapy (donepezil). Moreover, these effects may be explained by tropisetron's ability to sensitize α7 containing nAChRs to low levels of acetylcholine., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Epilepsy is one of the most common serious neurologic conditions. It is characterized by the tendency to have recurrent seizures, which arise against a backdrop of apparently normal brain activity. At present, clinical diagnosis relies on the following: (1) case history, which can be unreliable; (2) observation of transient abnormal activity during electroencephalography (EEG), which may not be present during clinical evaluation; and (3) if diagnostic uncertainty occurs, undertaking prolonged monitoring in an attempt to observe EEG abnormalities, which is costly. Herein, we describe the discovery and validation of an epilepsy biomarker based on computational analysis of a short segment of resting-state (interictal) EEG. Our method utilizes a computer model of dynamic networks, where the network is inferred from the extent of synchrony between EEG channels (functional networks) and the normalized power spectrum of the clinical data. We optimize model parameters using a leave-one-out classification on a dataset comprising 30 people with idiopathic generalized epilepsy (IGE) and 38 normal controls. Applying this scheme to all 68 subjects we find 100% specificity at 56.7% sensitivity, and 100% sensitivity at 65.8% specificity. We believe this biomarker could readily provide additional support to the diagnostic process., (© 2016 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.)

Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.

The extensive use of organophosphates (OPs) is an ongoing environmental health concern due to multiple reports of OP-related neurologic abnormalities. The mechanism of the acute toxicity of OPs has been attributed to inhibition of acetylcholinesterase (AChE), but there is growing evidence that this may not account for all the long-term neurotoxic effects of OPs. In previous experiments (using ex vivo and in vitro model systems) we observed that the insecticide OP chlorpyrifos impaired the movements of vesicles and mitochondria in axons. Here, using a time-lapse imaging technique, we evaluated the OP-nerve agent diisopropylfluorophosphate (DFP) across a wide range of concentrations (subnanomolar to micromolar) for effects on fast axonal transport of membrane-bound organelles (MBOs) that contain the amyloid precursor protein (APP) tagged with the fluorescent marker Dendra2 (APPDendra2). Both 1 and 24 hours of exposure to DFP and a positive control compound, colchicine, resulted in a decrease in the velocity of anterograde and retrograde movements of MBOs and an increase in the number of stationary MBOs. These effects occurred at picomolar (100 pM) to low nanomolar (0.1 nM) concentrations that were not associated with compromised cell viability or cytoskeletal damage. Moreover, the effects of DFP on axonal transport occurred at concentrations that did not inhibit AChE activity, and they were not blocked by cholinergic receptor antagonists. Given the fundamental importance of axonal transport to neuronal function, these observations may explain some of the long-term neurologic deficits that have been observed in humans who have been exposed to OPs., (Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.)

Rationale: Due to the rising costs of drug development especially in the field of neuropsychiatry, there is increasing interest in efforts to identify new clinical uses for existing approved drugs (i.e., drug repurposing)., Objectives: The purpose of this work was to evaluate in animals the smoking cessation agent, varenicline, a partial agonist at α4β2 and full agonist at α7 nicotinic acetylcholine receptors, for its potential as a repurposed drug for disorders of cognition., Methods: Oral doses of varenicline ranging from 0.01 to 0.3 mg/kg were evaluated in aged and middle-aged monkeys for effects on the following: working/short-term memory in a delayed match to sample (DMTS) task, distractibility in a distractor version of the DMTS (DMTS-D), and cognitive flexibility in a ketamine-impaired reversal learning task., Results: In dose-effect studies in the DMTS and DMTS-D tasks, varenicline was not associated with statistically significant effects on performance. However, individualized "optimal doses" were effective when repeated on a separate occasion (i.e., improving DMTS accuracy at long delays and DMTS-D accuracy at short delays by approximately 13.6 and 19.6 percentage points above baseline, respectively). In reversal learning studies, ketamine impaired accuracy and increased perseverative responding, effects that were attenuated by all three doses of varenicline that were evaluated., Conclusions: While the effects of varenicline across the different behavioral tasks were modest, these data suggest that varenicline may have potential as a repurposed drug for disorders of cognition associated with aging (e.g., Alzheimer's disease), as well as those not necessarily associated with advanced age (e.g., schizophrenia).

The challenges associated with developing more effective treatments for neurologic and psychiatric illness such as Alzheimer's disease and schizophrenia are considerable. Both the symptoms and the pathophysiology of these conditions are complex and poorly understood and the clinical presentations across different patients can be very heterogeneous. Moreover, it has become apparent that the reductionist approach to drug discovery for these illnesses that has dominated the field for decades (i.e., the development of highly selective compounds or other treatment modalities focused on a very specific pathophysiologic target) has not been widely successful. Accordingly, a variety of new strategies have emerged including the development of "multitarget-directed ligands" (MTDLs), the development and/or identification of compounds that exhibit "multifunctional" activity (e.g., pro-cognitive plus neuroprotective, pro-cognitive plus antipsychotic activity), "repurposing" strategies for existing compounds that have other clinical indications, and novel "adjunctive" treatment strategies that might enhance the efficacy of the currently available treatments. Interestingly, a variety of ligands at nicotinic acetylcholine receptors (nAChRs) appear to have the potential to fulfill one or more of these desirable properties (i.e., multifunctional, repurposing, or adjunctive treatment potential). The purpose of this review (while not all-inclusive) is to provide an overview of a variety of nAChR ligands that demonstrate potential in these categories, particularly, "multifunctional" properties. Due to their densities in the mammalian brain and the amount of literature available, the review will focus on ligands of the high affinity α4β2 nAChR and the low affinity α7 nAChR., (Copyright © 2015 Elsevier Inc. All rights reserved.)

A sensitive method to simultaneously quantitate quetiapine and norquetiapine in rat plasma and brain tissue was developed using a one-step liquid-liquid extraction for sample preparation and LC-MS/MS for detection. The method provided a linear range of 1.0-500.0ng/mL for each analyte in plasma and 3.0-1500.0ng/g in brain tissue. The method was validated with precision within 15% relative standard deviation (RSD), accuracy within 15% relative error (RE), matrix effects within 10% and a consistent recovery. This method has been successfully applied in a preclinical study of quetiapine and norquetiapine to simultaneously determine their concentrations in rat plasma and brain tissue., (Copyright © 2015 Elsevier B.V. All rights reserved.)