Modulation of serotonin transporter expression by escitalopram under inflammation.

Selective serotonin reuptake inhibitors (SSRIs) are widely used for depression based on the monoamine deficiency hypothesis. However, the clinical use of these agents is controversial, in part because of their variable clinical efficacy and in part because of their delayed onset of action. Because of the complexities involved in replicating human disease and clinical dosing in animal models, the scientific community has not reached a consensus on the reasons for these phenomena. In this work, we create a theoretical hippocampal model incorporating escitalopram's pharmacokinetics, pharmacodynamics (competitive and non-competitive inhibition, and serotonin transporter (SERT) internalization), inflammation, and receptor dynamics. With this model, we simulate chronic oral escitalopram in mice showing that days to weeks are needed for serotonin levels to reach steady-state. We show escitalopram's chemical efficacy is diminished under inflammation. Our model thus offers mechanisms for how chronic escitalopram affects brain serotonin, emphasizing the importance of optimized dose and time for future antidepressant discoveries.

Enhancing yield and oil content in oilseed rape hybrids: Insights from line × tester and SIIG approaches.

Background: The production of high-oil-yielding hybrid varieties is a primary objective in oilseed rape (Brassica napus L.) breeding programs. Biometric genetic experiments such as line × tester provide valuable insights into the genetic structure of traits associated with high oil yield. Methods: In this study, 21 winter hybrids of oilseed rape were evaluated, which were generated by crossing three restorers with seven CMS lines. The experiment was conducted using a line × tester experiment based on a completely randomized block design. Phenological, agronomic, yield, and oil yield components were assessed in this study. The ideal genotype selection index (SIIG) methodology was also employed to identify superior hybrids based on all studied traits simultaneously. Results: Significant differences were observed between the obtained hybrids and the check cultivars. Heritability analysis revealed that phenological traits were primarily controlled by additive effects, while agronomic and qualitative traits were mainly influenced by non-additive gene effects. Both broad-sense and narrow-sense heritability exhibited a wide range, underscoring the importance of genetic variance. Notably, the hybrids T1 × L5, T1 × L6, and T3 × L1 showed significant specific combining ability values of 394.74, 541.73, and 1236.79, respectively, making them the top specific combinations for increasing seed yield. Based on the SIIG index, hybrids T3 × L1, T1 × L5, T1 × L3, and T2 × L3 emerged as high-oil-yielding hybrids with desirable agronomic traits. Conclusions: The identified superior hybrids by line × tester and SIIG approaches hold promise for the development of high-yielding oilseed rape cultivars with desirable agronomic traits in oilseed rape breeding programs.

SmartFSCV: An Artificial Intelligence Enabled Miniaturised FSCV Device Targeting Serotonin.

Goal: Dynamically monitoring serotonin in real-time within target brain regions would significantly improve the diagnostic and therapeutic approaches to a variety of neurological and psychiatric disorders. Current systems for measuring serotonin lack immediacy and portability and are bulky and expensive. Methods: We present a new miniaturised device, named SmartFSCV, designed to monitor dynamic changes of serotonin using fast-scan cyclic voltammetry (FSCV). This device outputs a precision voltage potential between -3 to +3 V, and measures current between -1.5 to +1.5 µA with nano-ampere accuracy. The device can output modifiable arbitrary waveforms for various measurements and uses an N-shaped waveform at a scan-rate of 1000 V/s for sensing serotonin. Results: Four experiments were conducted to validate SmartFSCV: static bench test, dynamic serotonin test and two artificial intelligence (AI) algorithm tests. Conclusions: These tests confirmed the ability of SmartFSCV to accurately sense and make informed decisions about the presence of serotonin using AI.

Serotonin as a biomarker of toxin-induced Parkinsonism.

BACKGROUND: Loss of dopaminergic neurons underlies the motor symptoms of Parkinson's disease (PD). However stereotypical PD symptoms only manifest after approximately 80% of dopamine neurons have died making dopamine-related motor phenotypes unreliable markers of the earlier stages of the disease. There are other non-motor symptoms, such as depression, that may present decades before motor symptoms. METHODS: Because serotonin is implicated in depression, here we use niche, fast electrochemistry paired with mathematical modelling and machine learning to, for the first time, robustly evaluate serotonin neurochemistry in vivo in real time in a toxicological model of Parkinsonism, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). RESULTS: Mice treated with acute MPTP had lower concentrations of in vivo, evoked and ambient serotonin in the hippocampus, consistent with the clinical comorbidity of depression with PD. These mice did not chemically respond to SSRI, as strongly as control animals did, following the clinical literature showing that antidepressant success during PD is highly variable. Following L-DOPA administration, using a novel machine learning analysis tool, we observed a dynamic shift from evoked serotonin release in the hippocampus to dopamine release. We hypothesize that this finding shows, in real time, that serotonergic neurons uptake L-DOPA and produce dopamine at the expense of serotonin, supporting the significant clinical correlation between L-DOPA and depression. Finally, we found that this post L-DOPA dopamine release was less regulated, staying in the synapse for longer. This finding is perhaps due to lack of autoreceptor control and may provide a ground from which to study L-DOPA induced dyskinesia. CONCLUSIONS: These results validate key prior hypotheses about the roles of serotonin during PD and open an avenue to study to potentially improve therapeutics for levodopa-induced dyskinesia and depression.

Serotonin is a common thread linking different classes of antidepressants.

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of escitalopram, fluoxetine, reboxetine, and ketamine. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking, and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis, and the monoamine hypothesis).

Mechanical stimulation of human hair follicle outer root sheath cultures activates adjacent sensory neurons.

Mechanical stimuli, such as stroking or pressing on the skin, activate mechanoreceptors transmitting information to the sensory nervous system and brain. It is well accepted that deflection of the hair fiber that occurs with a light breeze or touch directly activates the sensory neurons surrounding the hair follicle, facilitating transmission of mechanical information. Here, we hypothesized that hair follicle outer root sheath cells act as transducers of mechanical stimuli to sensory neurons surrounding the hair follicle. Using electrochemical analysis on human hair follicle preparations in vitro, we were able to show that outer root sheath cells release ATP and the neurotransmitters serotonin and histamine in response to mechanical stimulation. Using calcium imaging combined with pharmacology in a coculture of outer root sheath cells with sensory neurons, we found that the release of these three molecules from hair follicle cells leads to activation of sensory neurons.

A catena between psychiatric disorders and non-scarring alopecias-A systematic review.

For many years, clinical observations have suggested that there is an intrinsic connection between psychological state and skin diseases. Stress responses are typically mediated by several hormones, which are modulated via the hypothalamic-pituitary-adrenal axis. This typical stress response is not only one theory for psychiatry disorder pathophysiology, but it also modifies hair growth by altering the skin's inflammatory environment. Given that different forms of hair loss, such as androgenetic alopecia, alopecia areata, or telogen effluvium, and hair follicle cycling can be altered by immune cells within the follicle milieu, we hypothesized that specific forms of hair loss are correlated to psychiatric illnesses. To address this, we conducted a systematic review by searches in April and May 2021 through Ovid MEDLINE and PUBMED (ranging from 1951 to the present day), identifying 179 reports. A further 24 reports were identified through website and citation searches giving a total of 201 reports. After applying exclusion criteria, 21 papers were reviewed, and 17 were included for data analysis. It is undeniable that hair loss greatly affects Health-related Quality of Life (HrQol) and it is heavily associated with major depressive disorder and anxiety. The correlation between hair loss and mental health disorders was significant, however, due to the low number of publications with quantitative data we were not able to identify correlations between each hair loss type with each psychiatric disorder. Further studies to better connect specific hair loss diseases to specific disorders are therefore critical in bettering the way both psychiatric disease, and hair loss, are managed.

Novel Experimental and Analysis Strategies for Fast Voltammetry: 2. A Troubleshoot-Free Flow Cell for FSCV Calibrations.

Fast scan cyclic voltammetry (FSCV) at carbon fiber microelectrodes (CFMs) is a method traditionally used for real-time quantification of neurotransmitters in biological systems. Reliable calibration of CFMs is essential for converting FSCV signals to analyte concentrations and generally employs flow injection analysis (FIA) performed with flow cells fabricated in-house. Such FSCV FIA cells often require significant and ongoing troubleshooting with pulsing, leaking, flow inconsistencies and dead volume being major causes of common challenges. In this work, we address these issues by creating a robust, plug-and-play FSCV flow cell. This novel design permits reproducible, high-precision, and stable flow injection profiles using low-cost materials to improve FSCV calibration. The ready-to-print computer-aided designs and hardware list are provided.

Serotonin is a Common Thread Linking Different Classes of Antidepressants.

Depression pathology remains elusive. The monoamine hypothesis has placed much focus on serotonin, but due to the variable clinical efficacy of monoamine reuptake inhibitors, the community is looking for alternative therapies such as ketamine (synaptic plasticity and neurogenesis theory of antidepressant action). There is evidence that different classes of antidepressants may affect serotonin levels; a notion we test here. We measure hippocampal serotonin in mice with voltammetry and study the effects of acute challenges of antidepressants. We find that pseudo-equivalent doses of these drugs similarly raise ambient serotonin levels, despite their differing pharmacodynamics because of differences in Uptake 1 and 2, rapid SERT trafficking and modulation of serotonin by histamine. These antidepressants have different pharmacodynamics but have strikingly similar effects on extracellular serotonin. Our findings suggest that serotonin is a common thread that links clinically effective antidepressants, synergizing different theories of depression (synaptic plasticity, neurogenesis and the monoamine hypothesis).

An In Vivo Definition of Brain Histamine Dynamics Reveals Critical Neuromodulatory Roles for This Elusive Messenger.

Histamine is well known for mediating peripheral inflammation; however, this amine is also found in high concentrations in the brain where its roles are much less known. In vivo chemical dynamics are difficult to measure, thus fundamental aspects of histamine's neurochemistry remain undefined. In this work, we undertake the first in-depth characterization of real time in vivo histamine dynamics using fast electrochemical tools. We find that histamine release is sensitive to pharmacological manipulation at the level of synthesis, packaging, autoreceptors and metabolism. We find two breakthrough aspects of histamine modulation. First, differences in H3 receptor regulation between sexes show that histamine release in female mice is much more tightly regulated than in male mice under H3 or inflammatory drug challenge. We hypothesize that this finding may contribute to hormone-mediated neuroprotection mechanisms in female mice. Second, a high dose of a commonly available antihistamine, the H1 receptor inverse agonist diphenhydramine, rapidly decreases serotonin levels. This finding highlights the sheer significance of pharmaceuticals on neuromodulation. Our study opens the path to better understanding and treating histamine related disorders of the brain (such as neuroinflammation), emphasizing that sex and modulation (of serotonin) are critical factors to consider when studying/designing new histamine targeting therapeutics.

A tale of two transmitters: serotonin and histamine as in vivo biomarkers of chronic stress in mice.

BACKGROUND: Stress-induced mental illnesses (mediated by neuroinflammation) pose one of the world's most urgent public health challenges. A reliable in vivo chemical biomarker of stress would significantly improve the clinical communities' diagnostic and therapeutic approaches to illnesses, such as depression. METHODS: Male and female C57BL/6J mice underwent a chronic stress paradigm. We paired innovative in vivo serotonin and histamine voltammetric measurement technologies, behavioral testing, and cutting-edge mathematical methods to correlate chemistry to stress and behavior. RESULTS: Inflammation-induced increases in hypothalamic histamine were co-measured with decreased in vivo extracellular hippocampal serotonin in mice that underwent a chronic stress paradigm, regardless of behavioral phenotype. In animals with depression phenotypes, correlations were found between serotonin and the extent of behavioral indices of depression. We created a high accuracy algorithm that could predict whether animals had been exposed to stress or not based solely on the serotonin measurement. We next developed a model of serotonin and histamine modulation, which predicted that stress-induced neuroinflammation increases histaminergic activity, serving to inhibit serotonin. Finally, we created a mathematical index of stress, Si and predicted that during chronic stress, where Si is high, simultaneously increasing serotonin and decreasing histamine is the most effective chemical strategy to restoring serotonin to pre-stress levels. When we pursued this idea pharmacologically, our experiments were nearly identical to the model's predictions. CONCLUSIONS: This work shines the light on two biomarkers of chronic stress, histamine and serotonin, and implies that both may be important in our future investigations of the pathology and treatment of inflammation-induced depression.

DAT and TH expression marks human Parkinson's disease in peripheral immune cells.

Parkinson's disease (PD) is marked by a loss of dopamine neurons, decreased dopamine transporter (DAT) and tyrosine hydroxylase (TH) expression. However, this validation approach cannot be used for diagnostic, drug effectiveness or investigational purposes in human patients because midbrain tissue is accessible postmortem. PD pathology affects both the central nervous and peripheral immune systems. Therefore, we immunophenotyped blood samples of PD patients for the presence of myeloid derived suppressor cells (MDSCs) and discovered that DAT+/TH+ monocytic MDSCs, but not granulocytic MDSCs are increased, suggesting a targeted immune response to PD. Because in peripheral immune cells DAT activity underlies an immune suppressive mechanism, we investigated whether expression levels of DAT and TH in the peripheral immune cells marks PD. We found drug naïve PD patients exhibit differential DAT+/TH+ expression in peripheral blood mononuclear cells (PBMCs) compared to aged/sex matched healthy subjects. While total PBMCs are not different between the groups, the percentage of DAT+/TH+ PBMCs was significantly higher in drug naïve PD patients compared to healthy controls irrespective of age, gender, disease duration, disease severity or treatment type. Importantly, treatment for PD negatively modulates DAT+/TH+ expressing PBMCs. Neither total nor the percentage of DAT+/TH+ PBMCs were altered in the Alzheimer's disease cohort. The mechanistic underpinning of this discovery in human PD was revealed when these findings were recapitulated in animal models of PD. The reverse translational experimental strategy revealed that alterations in dopaminergic markers in peripheral immune cells are due to the disease associated changes in the CNS. Our study demonstrates that the dopaminergic machinery on peripheral immune cells displays an association with human PD, with exciting implications in facilitating diagnosis and investigation of human PD pathophysiology.

Voltammetric Approach for Characterizing the Biophysical and Chemical Functionality of Human Induced Pluripotent Stem Cell-Derived Serotonin Neurons.

Depression is quickly becoming one of the world's most pressing public health crises, and there is an urgent need for better diagnostics and therapeutics. Behavioral models in animals and humans have not adequately addressed the diagnosis and treatment of depression, and biomarkers of mental illnesses remain ill-defined. It has been very difficult to identify biomarkers of depression because of in vivo measurement challenges. While our group has made important strides in developing in vivo tools to measure such biomarkers (e.g., serotonin) in mice using voltammetry, these tools cannot be easily applied for depression diagnosis and drug screening in humans due to the inaccessibility of the human brain. In this work, we take a chemical approach, ex vivo, to introduce a human-derived system to investigate brain serotonin. We utilize human induced pluripotent stem cells differentiated into serotonin neurons and establish a new ex vivo model of real-time serotonin neurotransmission measurements. We show that evoked serotonin release responds to stimulation intensity and tryptophan preloading, and that serotonin release and reuptake kinetics resemble those found in vivo in rodents. Finally, after selective serotonin reuptake inhibitor (SSRI) exposure, we find dose-dependent internalization of the serotonin reuptake transporters (a signature of the in vivo response to SSRI). Our new human-derived chemical model has great potential to provide an ex vivo chemical platform as a translational tool for in vivo neuropsychopharmacology.

Novel, User-Friendly Experimental and Analysis Strategies for Fast Voltammetry: Next Generation FSCAV with Artificial Neural Networks.

Fast-scan adsorption-controlled voltammetry (FSCAV) was recently derived from fast-scan cyclic voltammetry to estimate the absolute concentrations of neurotransmitters by using the innate adsorption properties of carbon fiber microelectrodes. This technique has improved our knowledge of serotonin dynamics in vivo. However, the analysis of FSCAV data is laborious and technically challenging. First, each electrode requires post-experimental in vitro calibration. Second, current analysis methods are semi-manual and time-consuming and require a steep learning curve. Finally, the calibration methods used do not adapt to nonlinear electrode responses. In this work, we provide freely accessible computational solutions to these issues. First, we design an artificial neural network (ANN) and train it with a large data set (calibrations from 140 electrodes by six different researchers) to achieve calibration-free estimations and improve predictive error. We discuss the power of the ANN to obtain a low predictive error without electrode-specific calibrations as a function of being able to predict the sensitivity of the electrode. We use the ANN to successfully predict the absolute serotonin concentrations of real in vivo data. Finally, we create a fast and user-friendly, fully automated analysis web platform to simplify and reduce the expertise required for the postanalysis of FSCAV signals.

Low-Frequency Oscillations of In Vivo Ambient Extracellular Brain Serotonin.

Serotonin is an important neurotransmitter that plays a major role in many aspects of neuroscience. Fast-scan cyclic voltammetry measures fast in vivo serotonin dynamics using carbon fiber microelectrodes. More recently, fast-scan controlled-adsorption voltammetry (FSCAV) has been developed to measure slower, minute-to-minute changes in ambient extracellular serotonin. We have previously demonstrated that FSCAV measurements of basal serotonin levels give critical information regarding brain physiology and disease. In this work, we revealed the presence of low-periodicity fluctuations in serotonin levels in mouse hippocampi, measured in vivo with FSCAV. Using correlation analyses, we found robust evidence of oscillations in the basal serotonin levels, which had a period of 10 min and were not present in vitro. Under control conditions, the oscillations did not differ between male and female mice, nor do they differ between mice that underwent a chronic stress paradigm and those in the control group. After the acute administration of a selective serotonin reuptake inhibitor, we observed a shift in the frequency of the oscillations, leading us to hypothesize that the newly observed fluctuations were transporter regulated. Finally, we optimized the experimental parameters of the FSCAV to measure at a higher temporal resolution and found more pronounced shifts in the oscillation frequency, along with a decreased oscillation amplitude. We postulate that this work may serve as a potential bridge for studying serotonin/endocrine interactions that occur on the same time scale.

ROS-Scavenging Selenofluoxetine Derivatives Inhibit In Vivo Serotonin Reuptake.

While the neurochemistry that underpins the behavioral phenotypes of depression is the subject of many studies, oxidative stress caused by the inflammation comorbid with depression has not adequately been addressed. In this study, we described novel antidepressant-antioxidant agents consisting of selenium-modified fluoxetine derivatives to simultaneously target serotonin reuptake (antidepressant action) and oxidative stress. Excitingly, we show that one of these agents (1-F) carries the ability to inhibit serotonin reuptake in vivo in mice. We therefore present a frontier dual strategy that paves the way for the future of antidepressant therapies.

Integrating the monoamine and cytokine hypotheses of depression: Is histamine the missing link?

Psychiatric diseases, like depression, largely affect the central nervous system (CNS). While the underlying neuropathology of depressive illness remains to be elucidated, several hypotheses have been proposed as molecular underpinnings for major depressive disorder, including the monoamine hypothesis and the cytokine hypothesis. The monoamine hypothesis has been largely supported by the pharmaceuticals that target monoamine neurotransmitters as a treatment for depression. However, these antidepressants have come under scrutiny due to their limited clinical efficacy, side effects, and delayed onset of action. The more recent, cytokine hypothesis of depression is supported by the ability of immune-active agents to induce "sickness behaviour" akin to that seen with depression. However, treatments that more selectively target inflammation have yielded inconsistent antidepressive results. As such, neither of these hypotheses can fully explain depressive illness pathology, implying that the underlying neuropathological mechanisms may encompass aspects of both theories. The goal of the current review is to integrate these two well-studied hypotheses and to propose a role for histamine as a potential unifying factor that links monoamines to cytokines. Additionally, we will focus on stress-induced depression, to provide an updated perspective of depressive illness research and thereby identify new potential targets for the treatment of major depressive disorder.

Experimental Methods for Investigating Uptake 2 Processes In Vivo.

Neuromodulators are critical regulators of the brain's signaling processes, and thus they are popular pharmacological targets for psychoactive therapies. It is clear that monoamine uptake mechanisms are complicated and subject to multiple uptake mechanisms. Uptake 1 describes uptake of the monoamine via its designated transporter (SERT for serotonin, NET for norepinephrine, and DAT for dopamine), whereas Uptake 2 details multiple transporter types on neurons and glia taking up different types of modulators, not necessarily specific to the monoamine. While Uptake 1 processes have been well-studied over the past few decades, Uptake 2 mechanisms have remained more difficult to study because of the limitations in methods that have the sensitivity and spatiotemporal resolution to look at the subtleties in uptake profiles. In this chapter we review the different experimental approaches that have yielded important information about Uptake 2 mechanisms in vivo. The techniques (scintillation microspectrophotometry, microdialysis, chronoamperometry, and voltammetry) are described in detail, and pivotal studies associated with each method are highlighted. It is clear from these reviewed works that Uptake 2 processes are critical to consider to advance our understanding of the brain and develop effective neuropsychiatric therapies.

Glutamate Electropolymerization on Carbon Increases Analytical Sensitivity to Dopamine and Serotonin: An Auspicious In Vivo Phenomenon in Mice?

Carbon is the material of choice for electroanalysis of biological systems, being particularly applicable to neurotransmitter analysis as carbon fiber microelectrodes (CFMs). CFMs are most often applied to dopamine detection; however, the scope of CFM analysis has rapidly expanded over the last decade with our laboratory's focus being on improving serotonin detection at CFMs, which we achieved in the past via Nafion modification. We began this present work by seeking to optimize this modification to gain increased analytical sensitivity toward serotonin under the assumption that exposure of bare carbon to the in vivo environment rapidly deteriorates analytical performance. However, we were unable to experimentally verify this assumption and found that electrodes that had been exposed to the in vivo environment were more sensitive to evoked and ambient dopamine. We hypothesized that high in vivo concentrations of ambient extracellular glutamate could polymerize with a negative charge onto CFMs and facilitate response to dopamine. We verified this polymerization electrochemically and characterized the mechanisms of deposition with micro- and nano-imaging. Importantly, we identified that the application of 1.3 V as a positive upper waveform limit is a crucial factor for facilitating glutamate polymerization, thus improving analytical performance. Critically, information gained from these dopamine studies were extended to an in vivo environment where a 2-fold increase in sensitivity to evoked serotonin was achieved. Thus, we present here the novel finding that innate aspects of the in vivo environment are auspicious for detection of dopamine and serotonin at carbon fibers, offering a solution to our goal of an improved fast-scan cyclic voltammetry serotonin detection paradigm.

Inflammation-Induced Histamine Impairs the Capacity of Escitalopram to Increase Hippocampal Extracellular Serotonin.

Commonly prescribed selective serotonin reuptake inhibitors (SSRIs) inhibit the serotonin transporter to correct a presumed deficit in extracellular serotonin signaling during depression. These agents bring clinical relief to many who take them; however, a significant and growing number of individuals are resistant to SSRIs. There is emerging evidence that inflammation plays a significant role in the clinical variability of SSRIs, though how SSRIs and inflammation intersect with synaptic serotonin modulation remains unknown. In this work, we use fast in vivo serotonin measurement tools to investigate the nexus between serotonin, inflammation, and SSRIs. Upon acute systemic lipopolysaccharide (LPS) administration in male and female mice, we find robust decreases in extracellular serotonin in the mouse hippocampus. We show that these decreased serotonin levels are supported by increased histamine activity (because of inflammation), acting on inhibitory histamine H3 heteroreceptors on serotonin terminals. Importantly, under LPS-induced histamine increase, the ability of escitalopram to augment extracellular serotonin is impaired because of an off-target action of escitalopram to inhibit histamine reuptake. Finally, we show that a functional decrease in histamine synthesis boosts the ability of escitalopram to increase extracellular serotonin levels following LPS. This work reveals a profound effect of inflammation on brain chemistry, specifically the rapidity of inflammation-induced decreased extracellular serotonin, and points the spotlight at a potentially critical player in the pathology of depression, histamine. The serotonin/histamine homeostasis thus, may be a crucial new avenue in improving serotonin-based treatments for depression.SIGNIFICANCE STATEMENT Acute LPS-induced inflammation (1) increases CNS histamine, (2) decreases CNS serotonin (via inhibitory histamine receptors), and (3) prevents a selective serotonin reuptake inhibitor (SSRI) from effectively increasing extracellular serotonin. A targeted depletion of histamine recovers SSRI-induced increases in extracellular hippocampal serotonin.