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Frontiers in Cellular Neuroscience 2021Astrocytes and microglia are the main cell population besides neurons in the central nervous system (CNS). Astrocytes support the neuronal network maintenance of... (Review)
Review
Astrocytes and microglia are the main cell population besides neurons in the central nervous system (CNS). Astrocytes support the neuronal network maintenance of transmitter and ion homeostasis. They are part of the tripartite synapse, composed of pre- and postsynaptic neurons and perisynaptic astrocytic processes as a functional unit. There is an increasing evidence that astroglia are involved in the pathophysiology of CNS disorders such as epilepsy, autoimmune CNS diseases or neuropsychiatric disorders, especially with regard to glia-mediated inflammation. In addition to astrocytes, investigations on microglial cells, the main immune cells of the CNS, offer a whole network approach leading to better understanding of non-neuronal cells and their pathological role in CNS diseases and treatment. An astrocyte-microglia co-culture model of inflammation was developed by Faustmann et al. (2003), which allows to study the endogenous inflammatory reaction and the cytokine expression under drugs in a differentiated manner. Commonly used antiepileptic drugs (e.g., levetiracetam, valproic acid, carbamazepine, phenytoin, and gabapentin), immunomodulatory drugs (e.g., dexamethasone and interferon-beta), hormones and psychotropic drugs (e.g., venlafaxine) were already investigated, contributing to better understanding mechanisms of actions of CNS drugs and their pro- or anti-inflammatory properties concerning glial cells. Furthermore, the effects of drugs on glial cell viability, proliferation and astrocytic network were demonstrated. The astrocyte-microglia co-culture model of inflammation proved to be suitable as unique model for pharmacological investigations on astrocytes and microglia with future potential (e.g., cancer drugs, antidementia drugs, and toxicologic studies).
PubMed: 34975415
DOI: 10.3389/fncel.2021.805755 -
Psychopharmacology Bulletin May 2022Bipolar II disorder (BD-II) has limited evidence-based treatment guidelines. The aim of this systematic review and meta-analysis was to estimate the efficacy and safety... (Meta-Analysis)
Meta-Analysis Review
PURPOSE
Bipolar II disorder (BD-II) has limited evidence-based treatment guidelines. The aim of this systematic review and meta-analysis was to estimate the efficacy and safety of second-generation antidepressant (SGAD) monotherapy in acute BD-II depression.
METHODS
A literature search was conducted from the database inception through March 2021. Only randomized controlled trials (RCTs) were included. Outcome measures included: response rates, treatment-emergent affective switch (TEAS) rates, discontinuation due to side-effects, and all-cause discontinuation. Risk ratio (RR) was calculated using the Mantel-Haenszel random effects model.
RESULTS
3301 studies were screened, and 15 articles were selected for full-text review. Five studies met the inclusion criteria: Four double-blind RCTs (n = 533) and one open-label RCT (n = 83) were included. Two double-blind RCTs [n = 223, SGAD = 110 (venlafaxine = 65, sertraline = 45), lithium/control = 113] were included for meta-analysis. The response rate for SGAD monotherapy compared to lithium monotherapy were similar (RR = 1.44, 95% CI 0.78, 2.66). The TEAS rate for SGAD monotherapy was not significantly different from lithium monotherapy (p = 0.76). The discontinuation rate due to side-effects for SGAD monotherapy was significantly lower than lithium monotherapy with a RR = 0.32, 95% CI 0.11, 0.96, p = 0.04 but all-cause discontinuation rates were similar in both groups.
CONCLUSIONS
Limited data suggests short-term efficacy of venlafaxine and sertraline monotherapy in patients with acute BD-II depression with good side effect tolerability and without significantly increased switch rate. There is an urgent need for RCTs investigating the role of SGAD monotherapy in short and long-term among patients with BD-II.
Topics: Antidepressive Agents, Second-Generation; Bipolar Disorder; Depression; Humans; Lithium; Randomized Controlled Trials as Topic; Sertraline; Venlafaxine Hydrochloride
PubMed: 35721812
DOI: No ID Found -
Birth Defects Research Aug 2021Some studies have reported associations between prenatal use of venlafaxine, a serotonin-norepinephrine reuptake inhibitor used for depressive and anxiety disorders, and...
BACKGROUND
Some studies have reported associations between prenatal use of venlafaxine, a serotonin-norepinephrine reuptake inhibitor used for depressive and anxiety disorders, and some birth defects. We described the prevalence of venlafaxine prescription claims among privately insured women of reproductive age and pregnant women.
METHODS
Venlafaxine prescription claims were examined using the IBM MarketScan Commercial Databases. We included women of reproductive age (15-44 years) who had ≤45 days of lapsed enrollment during the calendar year of interest (2011-2016) in a non-capitated healthcare plan sponsored by a large, self-insured employer with prescription drug coverage and no mental health service carve-out. Annual cohorts of pregnant women were identified among eligible women of reproductive age via pregnancy diagnosis and procedure codes. Venlafaxine prescriptions were identified via National Drug Codes in outpatient pharmacy claims and we estimated the annual proportion of women with venlafaxine claims by pregnancy trimester (pregnant women only), age, and Census division.
RESULTS
Each year during 2011-2016, approximately 1.2% of eligible reproductive-aged and 0.3% of eligible pregnant women filled a venlafaxine prescription. Among pregnant women, the proportion with venlafaxine claims was highest during the first trimester and decreased during the second and third trimesters. Small temporal increases in venlafaxine claims were observed for reproductive-aged and pregnant women, with the largest among women aged 15-19 years.
CONCLUSIONS
Venlafaxine prescription claims were low among women of reproductive age and pregnant women during 2011-2016, with some increasing use over time among women aged 15-19 years.
Topics: Adolescent; Adult; Female; Humans; Pregnancy; Pregnant Women; Prescription Drugs; Prescriptions; Selective Serotonin Reuptake Inhibitors; Venlafaxine Hydrochloride; Young Adult
PubMed: 33860984
DOI: 10.1002/bdr2.1897 -
Brazilian Journal of Biology = Revista... 2021The present research was made to determine the micronuclei and cytotoxic capacity of the antidepressant venlafaxine in an in vivo acute and subchronic assays in mouse....
The present research was made to determine the micronuclei and cytotoxic capacity of the antidepressant venlafaxine in an in vivo acute and subchronic assays in mouse. In the first study, we administered once 5, 50, and 250 mg/kg of the drug, and included a negative and a daunorubicin treated group. Observations were daily made during four days. The subchronic assay lasted 5 weeks with daily administration of venlafaxine (1, 5, and 10 mg/kg) plus a negative and an imipramine administered groups. Observations were made each week. In the first assay results showed no micronucleated polychromatic erythrocytes (MNPE) increase, except with the high dose at 72 h. The strongest cytotoxic effect was found with 250 mg/kg at 72 h (a 51% cytotoxic effect in comparison with the mean control level). In the subchronic assay no MNPE increase was found; however, with the highest dose a significant increase of micronucleated normochromatic erythrocytes was observed in the last three weeks (a mean of 51% respect to the mean control value). A cytotoxic effect with the two high doses in the last two weeks was observed (a polychromatic erythrocyte mean decrease of 52% respect to the mean control value). Results suggest caution with venlafaxine.
Topics: Animals; Antineoplastic Agents; DNA Damage; Dose-Response Relationship, Drug; Erythrocytes; Mice; Micronucleus Tests; Venlafaxine Hydrochloride
PubMed: 34932628
DOI: 10.1590/1519-6984.251289 -
Cureus Apr 2023Purpose At present, clinicians typically prescribe antidepressants based on the widely accepted "serotonin hypothesis." This study explores an alternative mechanism,...
Purpose At present, clinicians typically prescribe antidepressants based on the widely accepted "serotonin hypothesis." This study explores an alternative mechanism, the stress mechanism, for selecting antidepressants based on patients' medical history. Methods This study investigated clinicians' prescribing patterns for the 15 most common antidepressants, including amitriptyline, bupropion, citalopram, desvenlafaxine, doxepin, duloxetine, escitalopram, fluoxetine, mirtazapine, nortriptyline, paroxetine, ropinirole, sertraline, trazodone, and Venlafaxine. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to identify factors that affect the remission of depression symptoms after receiving an antidepressant. Results The study found that a wide range of factors influenced the propensity of clinicians to prescribe antidepressants, with the number of predictors ranging from 51 to 206 variables. The prevalence of prescribing an antidepressant ranged from 0.5% for doxepin to 24% for the combination of more than one antidepressant. The area under the receiver operating curves (AROC) ranged from 77.2% for venlafaxine to 90.5% for ropinirole, with an average AROC of 82% for predicting the propensity of medications. A variety of diagnoses and prior medications affected remission, in agreement that the central mechanism for the impact of medications on the brain is through stress reduction. For example, psychotherapy, whether done individually or in a group, whether done for a short or long time, and whether done with evaluation/assessment or not, had an impact on remission. Specifically, teenagers and octogenarians were less likely to benefit from bupropion, citalopram, escitalopram, fluoxetine, and sertraline compared to patients between 40 and 65 years old. The findings of this study suggest that considering a patient's medical history and individual characteristics is crucial for selecting the most effective antidepressant treatment. Conclusions Many studies have raised doubt about the serotonin hypothesis as the central mechanism for depression treatment. The identification of a wide range of predictors for prescribing antidepressants highlights the complexity of depression treatment and the need for individualized approaches that consider patients' comorbidities and previous treatments. The significant impact of comorbidities on the response to treatment makes it improbable that the mechanism of action of antidepressants is solely based on the serotonin hypothesis. It is hard to explain how comorbidities lead to the depletion of serotonin. These findings open up a variety of courses of action for the clinical treatment of depression, each addressing a different source of chronic stress in the brain. Overall, this study contributes to a better understanding of depression treatment and provides valuable insights for clinicians in selecting antidepressants based on patients' medical history.
PubMed: 37168173
DOI: 10.7759/cureus.37117 -
Journal of Biomedical Informatics Apr 2023Pharmacokinetic natural product-drug interactions (NPDIs) occur when botanical or other natural products are co-consumed with pharmaceutical drugs. With the growing use...
BACKGROUND
Pharmacokinetic natural product-drug interactions (NPDIs) occur when botanical or other natural products are co-consumed with pharmaceutical drugs. With the growing use of natural products, the risk for potential NPDIs and consequent adverse events has increased. Understanding mechanisms of NPDIs is key to preventing or minimizing adverse events. Although biomedical knowledge graphs (KGs) have been widely used for drug-drug interaction applications, computational investigation of NPDIs is novel. We constructed NP-KG as a first step toward computational discovery of plausible mechanistic explanations for pharmacokinetic NPDIs that can be used to guide scientific research.
METHODS
We developed a large-scale, heterogeneous KG with biomedical ontologies, linked data, and full texts of the scientific literature. To construct the KG, biomedical ontologies and drug databases were integrated with the Phenotype Knowledge Translator framework. The semantic relation extraction systems, SemRep and Integrated Network and Dynamic Reasoning Assembler, were used to extract semantic predications (subject-relation-object triples) from full texts of the scientific literature related to the exemplar natural products green tea and kratom. A literature-based graph constructed from the predications was integrated into the ontology-grounded KG to create NP-KG. NP-KG was evaluated with case studies of pharmacokinetic green tea- and kratom-drug interactions through KG path searches and meta-path discovery to determine congruent and contradictory information in NP-KG compared to ground truth data. We also conducted an error analysis to identify knowledge gaps and incorrect predications in the KG.
RESULTS
The fully integrated NP-KG consisted of 745,512 nodes and 7,249,576 edges. Evaluation of NP-KG resulted in congruent (38.98% for green tea, 50% for kratom), contradictory (15.25% for green tea, 21.43% for kratom), and both congruent and contradictory (15.25% for green tea, 21.43% for kratom) information compared to ground truth data. Potential pharmacokinetic mechanisms for several purported NPDIs, including the green tea-raloxifene, green tea-nadolol, kratom-midazolam, kratom-quetiapine, and kratom-venlafaxine interactions were congruent with the published literature.
CONCLUSION
NP-KG is the first KG to integrate biomedical ontologies with full texts of the scientific literature focused on natural products. We demonstrate the application of NP-KG to identify known pharmacokinetic interactions between natural products and pharmaceutical drugs mediated by drug metabolizing enzymes and transporters. Future work will incorporate context, contradiction analysis, and embedding-based methods to enrich NP-KG. NP-KG is publicly available at https://doi.org/10.5281/zenodo.6814507. The code for relation extraction, KG construction, and hypothesis generation is available at https://github.com/sanyabt/np-kg.
Topics: Pattern Recognition, Automated; Drug Interactions; Biological Ontologies; Semantics; Biological Products; Pharmaceutical Preparations
PubMed: 36933632
DOI: 10.1016/j.jbi.2023.104341 -
Translational Psychiatry Feb 2020Antidepressants exhibit similar efficacy, but varying tolerability, in randomized controlled trials. Predicting tolerability in real-world clinical populations may...
Antidepressants exhibit similar efficacy, but varying tolerability, in randomized controlled trials. Predicting tolerability in real-world clinical populations may facilitate personalization of treatment and maximize adherence. This retrospective longitudinal cohort study aimed to determine the extent to which incorporating patient history from electronic health records improved prediction of unplanned treatment discontinuation at index antidepressant prescription. Clinical data were analyzed from individuals from health networks affiliated with two large academic medical centers between March 1, 2008 and December 31, 2014. In total, the study cohorts included 51,683 patients with at least one International Classification of Diseases diagnostic code for major depressive disorder or depressive disorder not otherwise specified who initiated antidepressant treatment. Among 70,121 total medication changes, 16,665 (23.77%) of them were followed by failure to return; maximum risk was observed with paroxetine (27.71% discontinuation), and minimum with venlafaxine (20.78% discontinuation); Mantel-Haenzel χ (8 df) = 126.44, p = 1.54e-23 <1e-6. Models incorporating diagnostic and procedure codes and medication prescriptions improved per-medication Areas Under the Curve (AUCs) to a mean of 0.69 [0.64-0.73] (ranging from 0.62 for paroxetine to 0.80 for escitalopram), with similar performance in the second, replication health system. Machine learning applied to coded electronic health records facilitates identification of individuals at high-risk for treatment dropout following change in antidepressant medication. Such methods may assist primary care physicians and psychiatrists in the clinic to personalize antidepressant treatment on the basis not solely of efficacy, but of tolerability.
Topics: Antidepressive Agents; Depressive Disorder, Major; Humans; Longitudinal Studies; Paroxetine; Retrospective Studies
PubMed: 32066733
DOI: 10.1038/s41398-020-0716-y -
Journal of Diabetes Research 2022Diabetes is the 4 most common disease affecting the world's population. It is accompanied by many complications that deteriorate the quality of life. Painful diabetic... (Review)
Review
Diabetes is the 4 most common disease affecting the world's population. It is accompanied by many complications that deteriorate the quality of life. Painful diabetic neuropathy (PDN) is one of the debilitating consequences of diabetes that effects one-third of diabetic patients. Unfortunately, there is no internationally recommended drug that directly hinders the pathological mechanisms that result in painful diabetic neuropathy. Clinical studies have shown that anticonvulsant and antidepressant therapies have proven fruitful in management of pain associated with PDN. Currently, the FDA approved medications for painful diabetic neuropathies include duloxetine, pregabalin, tapentadol extended release, and capsaicin (for foot PDN only). The FDA has also approved the use of spinal cord stimulation system for the treatment of diabetic neuropathy pain. The drugs recommended by other regulatory bodies include gabapentin, amitriptyline, dextromethorphan, tramadol, venlafaxine, sodium valproate, and 5 % lidocaine patch. These drugs are only partially effective and have adverse effects associated with their use. Treating painful symptoms in diabetic patient can be frustrating not only for the patients but also for health care workers, so additional clinical trials for novel and conventional treatments are required to devise more effective treatment for PDN with minimal side effects. This review gives an insight on the pathways involved in the pathogenesis of PDN and the potential pharmacotherapeutic agents. This will be followed by an overview on the FDA-approved drugs for PDN and commercially available topical analgesic and their effects on painful diabetic neuropathies.
Topics: Analgesics; Diabetic Neuropathies; Humans; Pain Management; Quality of Life
PubMed: 35127954
DOI: 10.1155/2022/9989272 -
Cell Communication and Signaling : CCS Mar 2024The impact of antidepressants on Inflammatory bowel diseases (IBD) has been extensively studied. However, the biological effects and molecular mechanisms of...
BACKGROUND
The impact of antidepressants on Inflammatory bowel diseases (IBD) has been extensively studied. However, the biological effects and molecular mechanisms of antidepressants in alleviating colitis remain unclear.
METHODS
We systematically assessed how antidepressants (fluoxetine, fluvoxamine and venlafaxine) affected IBD and chose fluoxetine, the most effective one, for mechanism studies. We treated the C56BL/6 mice of the IBD model with fluoxetine and their controls. We initially assessed the severity of intestinal inflammation in mice by body weight loss, disease Activity Index scores and the length of the colon. The H&E staining and immunohistochemical staining of MUC2 of colon sections were performed to observe the pathological changes. RT-qPCR and western blot were conducted to assess the expression level of the barrier and inflammation-associated genes. Then, single-cell RNA sequencing was performed on mouse intestinal mucosa. Seurat was used to visualize the data. Uniform Manifold Approximation and Projection (UMAP) was used to perform the dimensionality reduction. Cell Chat package was used to perform cell-cell communication analysis. Monocle was used to conduct developmental pseudotime analysis. Last, RT-qPCR, western blot and immunofluorescence staining were conducted to test the phenomenon discovered by single-cell RNA sequencing in vitro.
RESULTS
We found that fluoxetine treatment significantly alleviated colon inflammation. Notably, single-cell RNA sequencing analysis revealed that fluoxetine affected the distribution of different cell clusters, cell-cell communication and KEGG pathway enrichment. Under the treatment of fluoxetine, enterocytes, Goblet cells and stem cells became the dominating cells. The pseudotime analysis showed that there was a trend for M1 macrophages to differentiate into M2 macrophages. Lastly, we tested this phenomenon in vitro, which exhibited anti-inflammatory effects on enterocytes.
CONCLUSIONS
Fluoxetine exhibited anti-inflammatory effects on intestinal mucosa via remodeling of the intestinal cells and macrophages, which reveals that fluoxetine is a promising therapeutic drug for the treatment of IBD and psychiatric comorbidities.
Topics: Animals; Mice; Fluoxetine; Cytokines; Colitis; Inflammatory Bowel Diseases; Inflammation; Intestinal Mucosa; Antidepressive Agents; Anti-Inflammatory Agents; Mice, Inbred C57BL
PubMed: 38475799
DOI: 10.1186/s12964-024-01538-5 -
The Science of the Total Environment Nov 2022Ozonation has been used to effectively remove micropollutants from the secondary effluent in several wastewater treatment plants. It is known that ozonation transforms...
Ozonation has been used to effectively remove micropollutants from the secondary effluent in several wastewater treatment plants. It is known that ozonation transforms tertiary amine compounds into their respective N-oxides, however in an earlier study a mass balance could not be closed at elevated ozone concentrations, leading to the assumption that more ozonation products are possible. This study was conducted to elucidate which (hitherto unknown) ozonation products can be formed from venlafaxine and tramadol when ozonating wastewater. Ozonation experiments were performed with tramadol and venlafaxine N-oxide in two different set-ups. Both tramadol- and venlafaxine N-oxide degraded during ozonation in pure (deionized) water in both semi-continuous and batch mode ozonation set-ups. 13 and 17 new transformation products were detected from tramadol- and venlafaxine N-oxide respectively, using high resolution mass spectrometry with ESI(+) ionization. Empirical chemical formulas were proposed based on the determination of the exact masses and interpretation of the product ion spectra. These transformation products result from the addition of one to three oxygen atoms and removal of C, -CH, CH, CH, etc., from the parent molecule, respectively. Quenching experiments suggested that most of the transformation products originated from the direct reaction with ozone (eight for tramadol N-oxide and ten for venlafaxine N-oxide), whereas fewer products originated from the reaction with OH radicals (three for tramadol N-oxide and three for venlafaxine N-oxide). Reaction mechanisms and chemical structures of products are proposed, based on the available active sites and past literature on ozone reaction mechanisms. The experimental results are compared to theory and literature on ozone reactive sites and ozone reaction mechanisms. All in all this shows that there can be multiple ozonation products, and ozonation pathways can be complex, even if initially only one ozonation product is formed.
Topics: Organic Chemicals; Oxides; Ozone; Tramadol; Venlafaxine Hydrochloride; Waste Disposal, Fluid; Wastewater; Water Pollutants, Chemical; Water Purification
PubMed: 35817117
DOI: 10.1016/j.scitotenv.2022.157259