Chronic exposure to imipramine induces a switch from depression-like to mania-like behavior in female serotonin transporter knockout rats: Role of BDNF signaling in the infralimbic cortex.

BACKGROUND: Bipolar disorder (BD) is a highly burdensome psychiatric disorder characterized by alternating states of mania and depression. A major challenge in the clinic is the switch from depression to mania, which is often observed in female BD patients during antidepressant treatment such as imipramine. However, the underlying neural basis is unclear. METHODS: To investigate the potential neuronal pathways, serotonin transporter knockout (SERT KO) rats, an experimental model of female BD patients, were subjected to a battery of behavioral tests under chronic treatment of the antidepressant imipramine. In addition, the expression of brain-derived neurotrophic factor (BDNF) and its downstream signaling was examined in the prefrontal cortex. RESULTS: Chronic exposure to imipramine reduced anxiety and sociability and problem-solving capacity, and increased thigmotaxis and day/night activity in all animals, but specifically in female SERT KO rats, compared to female wild-type (WT) rats. Further, we found an activation of BDNF-TrkB-Akt pathway signaling in the infralimbic, but not prelimbic, cortex after chronic imipramine treatment in SERT KO, but not WT, rats. LIMITATIONS: Repeated testing behaviors could potentially affect the results. Additionally, the imipramine induced changes in behavior and in the BDNF system were measured in separate animals. CONCLUSIONS: Our study indicates that female SERT KO rats, which mirror the female BD patients with the 5-HTTLPR s-allele, are at higher risk of a switch to mania-like behaviors under imipramine treatment. Activation of the BDNF-TrkB-Akt pathway in the infralimbic cortex might contribute to this phenotype, but causal evidence remains to be provided.

Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives.

The reproducibility crisis (or replication crisis) in biomedical research is a particularly existential and under-addressed issue in the field of behavioral neuroscience, where, in spite of efforts to standardize testing and assay protocols, several known and unknown sources of confounding environmental factors add to variance. Human interference is a major contributor to variability both within and across laboratories, as well as novelty-induced anxiety. Attempts to reduce human interference and to measure more "natural" behaviors in subjects has led to the development of automated home-cage monitoring systems. These systems enable prolonged and longitudinal recordings, and provide large continuous measures of spontaneous behavior that can be analyzed across multiple time scales. In this review, a diverse team of neuroscientists and product developers share their experiences using such an automated monitoring system that combines Noldus PhenoTyper® home-cages and the video-based tracking software, EthoVision® XT, to extract digital biomarkers of motor, emotional, social and cognitive behavior. After presenting our working definition of a "home-cage", we compare home-cage testing with more conventional out-of-cage tests (e.g., the open field) and outline the various advantages of the former, including opportunities for within-subject analyses and assessments of circadian and ultradian activity. Next, we address technical issues pertaining to the acquisition of behavioral data, such as the fine-tuning of the tracking software and the potential for integration with biotelemetry and optogenetics. Finally, we provide guidance on which behavioral measures to emphasize, how to filter, segment, and analyze behavior, and how to use analysis scripts. We summarize how the PhenoTyper has applications to study neuropharmacology as well as animal models of neurodegenerative and neuropsychiatric illness. Looking forward, we examine current challenges and the impact of new developments. Examples include the automated recognition of specific behaviors, unambiguous tracking of individuals in a social context, the development of more animal-centered measures of behavior and ways of dealing with large datasets. Together, we advocate that by embracing standardized home-cage monitoring platforms like the PhenoTyper, we are poised to directly assess issues pertaining to reproducibility, and more importantly, measure features of rodent behavior under more ethologically relevant scenarios.

The cardiac effects of carbon nanotubes in rat.

INTRODUCTION: Carbon nanotubes (CNTs) are novel candidates in nanotechnology with a variety of increasing applications in medicine and biology. Therefore the investigation of nanomaterials' biocompatibility can be an important topic. The aim of present study was to investigate the CNTs impact on cardiac heart rate among rats. METHODS: Electrocardiogram (ECG) signals were recorded before and after injection of CNTs on a group with six rats. The heart rate variability (HRV) analysis was used for signals analysis. The rhythm-to-rhythm (RR) intervals in HRV method were computed and features of signals in time and frequency domains were extracted before and after injection. RESULTS: RESULTS of the HRV analysis showed that CNTs increased the heart rate but generally these nanomaterials did not cause serious problem in autonomic nervous system (ANS) normal activities. CONCLUSION: Injection of CNTs in rats resulted in increase of heart rate. The reason of phenomenon is that multiwall CNTs may block potassium channels. The suppressed and inhibited IK and potassium channels lead to increase of heart rate.

An autonomous real-time single-channel detection of absence seizures in WAG/Rij rats.

This paper presents a real-time, completely automated and patient independent algorithm for detection of absence seizures in WAG/Rij rats as a valid animal model of human absence epilepsy. Single-channel EEG recordings containing totally 488 seizures from 8 WAG/Rij rats were analyzed using the real-time SWD detection algorithm. The proposed algorithms based on the variation of wavelet power to the background power in two specific frequency bands whose spectral power are highly correlated with SWDs. The wavelet powers of two specific frequency bands are calculated with a pattern-adapted mother wavelet and compared with an adaptive ratio of background power of each frequency band. The results indicate used algorithm is able to detect the whole 488 seizures within less than 1 s with sensitivity of 100%. The average precision for 1200, 1400 and 1600 point of window size was 95.2%, 98.3% and 99.17%, respectively. The present algorithm, with its high sensitivity and specificity, could be used for further studies of absence seizures in humans and rats and could be implemented as real-time system for closed loop deep brain stimulation systems.

Investigation of ECG Changes in Absence Epilepsy on WAG/Rij Rats.

INTRODUCTION: Seizures are symptoms associated with abnormal electrical activity in electroencephalogram (EEG). The present study was designed to determine the effect of absence seizure on heart rate (HR) changes in electrocardiogram (ECG). METHODS: HR alterations were recorded simultaneous with spike and wave discharges (SWD) by EEG in 6 WAG/Rij rats as a well characterized and validated genetic animal epilepsy model. Moreover, 6 control rats were used to distinguish the differences of HR changes between various groups. Electrodes were placed on the skull and under the chest skin, minimizing time delay and signal attenuation. HR was calculated by an adaptable algorithm based on continues wavelet transform (CWT) particular for this study. Three main features of HR; minimum, maximum, and mean values were estimated for pre-ictal and ictal intervals for all seizures. RESULTS: ECG beats detected with sensitivity of 99.9% and positive predictability of 99.8% based on CWT. HR deceleration was found in 86% of the seizures. There were statistically significant (P<0.001) reductions of these values from pre-ictal to ictal intervals. Interictal HR acceleration and ictal deceleration were the major feature of alterations and in 23% of seizures, this decrease had priority to the onsets. DISCUSSION: These findings may lead to design a seizure alarm system based on HR and to obtain new insights about sudden unexpected death in epilepsy (SUDEP) phenomenon and side-effects of antiepileptic drugs (AED).

Effect of low frequency electrical stimulation on spike and wave discharges of perioral somatosensory cortex in WAG/Rij rats.

Low frequency electrical stimulation has been revealed that as a potential cure in patient with drug resistant to epilepsy. This study tries to evaluate the effect of low frequency electrical stimulation (LFS) on absence seizure of perioral region primary somatosensory cortex (S1po). Eighteen male WAG/Rij rats were received LFS (3Hz, square wave, monophasic, 200µs, and 400µA) for 25min into S1po for a period of five days. There is 6 animals per group .The stimulating electrodes were implanted according to stereotaxic landmarks and EEG recording was obtained 30min before and after LFS to analyse frequency, number and duration of spike-wave discharges (SWD). The results showed that in animals with unilateral stimulating electrodes (Exp1) in first and second days and also in animals with bilateral stimulating electrodes (Exp2) in days 3rd and 4th. LFS had significant decrease effects (p<0.05) on mean number of SWD between pre-LFS. In comparison pre-LFS to post-LFS, mean of duration in Exp2 decreased significantly. In continuous application of LFS (5 days) only the data of first day was differently significant (p<0.05) but data of other days had no difference. Comparison of data between Exp1, Exp2 and control groups showed that the mean number of Exp1 was significantly different (p<0.05) and mean pick frequency in Exp2 was significantly decreased in comparison with Exp1 group (p<0.05). The LFS of S1po produces significant antiepileptic effect on absence seizure but it was not persistent till the next day and shows a short time effect.