Neuroinflammation and Neurometabolomic Profiling in Fentanyl Overdose Mouse Model Treated with Novel β-Lactam, MC-100093, and Ceftriaxone
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Metabolomics Analysis
2.3. Behavioral Tests
2.4. Western Blot Assay
2.5. Statistical Analysis
3. Results
3.1. Effects of Fentanyl Overdose and Beta-Lactams on Average Body Weight
3.2. Effects of Fentanyl Overdose and Beta-Lactams on Locomotor Activity and Spontaneous Alteration Performance
3.3. Effects of Fentanyl Overdose and Beta-Lactams on Metabolomic Profiling
3.4. Assessment of the Expression of GLT-1 and TLR4, and IL-6 in the Nucleus Accumbens
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Saunders, M.E.; Humphrey, J.L.; Lambdin, B.H. Spatiotemporal Trends in Three Smoothed Overdose Death Rates in US Counties, 2012–2020. Prev. Chronic Dis. 2023, 20, E16. [Google Scholar] [CrossRef]
- Centers for Disease Control and Prevention and Prevention. Mortality Data on CDC Wonder. Surveillance Summaries; National Center for Health Statistics: Hyattsville, MD, USA, 2021. [Google Scholar]
- Baldwin, G.T.; Seth, P.; Noonan, R.K. Continued Increases in Overdose Deaths Related to Synthetic Opioids: Implications for Clinical Practice. JAMA—J. Am. Med. Assoc. 2021, 325, 1151–1152. [Google Scholar] [CrossRef] [PubMed]
- Dolinak, D. Opioid Toxicity. Acad. Forensic Pathol. 2017, 7, 19–35. [Google Scholar] [CrossRef] [PubMed]
- Calarco, C.A.; Fox, M.E.; van Terheyden, S.; Turner, M.D.; Alipio, J.B.; Chandra, R.; Lobo, M.K. Mitochondria-Related Nuclear Gene Expression in the Nucleus Accumbens and Blood Mitochondrial Copy Number After Developmental Fentanyl Exposure in Adolescent Male and Female C57BL/6 Mice. Front. Psychiatry 2021, 12, 737389. [Google Scholar] [CrossRef] [PubMed]
- Parfenova, H.; Basuroy, S.; Bhattacharya, S.; Tcheranova, D.; Qu, Y.; Regan, R.F.; Leffler, C.W. Glutamate induces oxidative stress and apoptosis in cerebral vascular endothelial cells: Contributions of HO-1 and HO-2 to cytoprotection. Am. J. Physiol.-Cell Physiol. 2006, 290, C1399–C1410. [Google Scholar] [CrossRef] [PubMed]
- Abulseoud, O.A.; Alasmari, F.; Hussein, A.M.; Sari, Y. Ceftriaxone as a Novel Therapeutic Agent for Hyperglutamatergic States: Bridging the Gap Between Preclinical Results and Clinical Translation. Front. Neurosci. 2022, 16, 841036. [Google Scholar] [CrossRef]
- Liu, X.L.; Li, L.; Li, J.N.; Tang, J.H.; Rong, J.H.; Liu, B.; Hu, Z. Quantifying absolute glutamate concentrations in nucleus accumbens of prescription opioid addicts by using 1H MRS. Brain Behav. 2017, 7, e00769. [Google Scholar] [CrossRef]
- Tokuyama, S.; Takahashi, M.; Yamamoto, T. On the role of glutamate within the locus coeruleus during the development of opioid dependence and on the expression of withdrawal from dependence on opioids. Jpn. J. Psychopharmacol. 2000, 20, 141–147. [Google Scholar]
- Zhu, H.; Rockhold, R.W.; Ho, I.K. The role of glutamate in physical dependence on opioids. Jpn. J. Pharmacol. 1998, 76, 1–14. [Google Scholar] [CrossRef]
- Anderson, C.M.; Swanson, R.A. Astrocyte glutamate transport: Review of properties, regulation, and physiological functions. Glia 2000, 32, 1–14. [Google Scholar] [CrossRef]
- Alasmari, M.S.; Almohammed, O.A.; Hammad, A.M.; Altulayhi, K.A.; Alkadi, B.K.; Alasmari, A.F.; Alqahtani, F.; Sari, Y.; Alasmari, F. Effects of Beta Lactams on Behavioral Outcomes of Substance Use Disorders: A Meta-Analysis of Preclinical Studies. Neuroscience 2024, 537, 58–83. [Google Scholar] [CrossRef]
- Kong, Q.; Chang, L.C.; Takahashi, K.; Liu, Q.; Schulte, D.A.; Lai, L.; Ibabao, B.; Lin, Y.; Stouffer, N.; Mukhopadhyay, C.D.; et al. Small-molecule activator of glutamate transporter EAAT2 translation provides neuroprotection. J. Clin. Investig. 2014, 124, 1255–1267. [Google Scholar] [CrossRef]
- Smaga, I.; Fierro, D.; Mesa, J.; Filip, M.; Knackstedt, L.A. Molecular changes evoked by the beta-lactam antibiotic ceftriaxone across rodent models of substance use disorder and neurological disease. Neurosci. Biobehav. Rev. 2020, 115, 116–130. [Google Scholar] [CrossRef]
- Lin, C.L.G.; Kong, Q.; Cuny, G.D.; Glicksman, M.A. Glutamate transporter EAAT2: A new target for the treatment of neurodegenerative diseases. Future Med. Chem. 2012, 4, 1689–1700. [Google Scholar] [CrossRef]
- Knackstedt, L.A.; Wu, L.; Rothstein, J.; Vidensky, S.; Gordon, J.; Ramanjulu, M.; Dunman, P.; Blass, B.; Childers, W.; Abou-Gharbia, M. MC-100093, a Novel β-Lactam Glutamate Transporter-1 Enhancer Devoid of Antimicrobial Properties, Attenuates Cocaine Relapse in Rats. J. Pharmacol. Exp. Ther. 2021, 378, 51–59. [Google Scholar] [CrossRef]
- Alhaddad, H.; Wong, W.; Abou-Gharbia, M.; Childers, W.; Melenski, E.; Bell, R.L.; Sari, Y. Effects of a Novel Beta Lactam Compound, MC-100093, on the Expression of Glutamate Transporters/Receptors and Ethanol Drinking Behavior of Alcohol-Preferring Rats. J. Pharmacol. Exp. Ther. 2022, 383, 208–216. [Google Scholar] [CrossRef]
- León, B.E.; Peyton, L.; Essa, H.; Wieden, T.; Marion, N.; Childers, W.E.; Abou-Gharbia, M.; Choi, D.-S. A novel monobactam lacking antimicrobial activity, MC-100093, reduces sex-specific ethanol preference and depressive-like behaviors in mice. Neuropharmacology 2023, 232, 109515. [Google Scholar] [CrossRef]
- Zaitsu, K.; Hayashi, Y.; Kusano, M.; Tsuchihashi, H.; Ishii, A. Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies. Drug Metab. Pharmacokinet. 2016, 31, 21–26. [Google Scholar] [CrossRef]
- Alasmari, F.; Alasmari, M.S.; Assiri, M.A.; Alswayyed, M.; Rizwan Ahamad, S.; Alhumaydhi, A.I.; Arif, B.I.; Aljumayi, S.R.; AlAsmari, A.F.; Ali, N.; et al. Liver Metabolomics and Inflammatory Profiles in Mouse Model of Fentanyl Overdose Treated with Beta-Lactams. Metabolites 2023, 13, 965. [Google Scholar] [CrossRef]
- Scofield, M.D.; Heinsbroek, J.A.; Gipson, C.D.; Kupchik, Y.M.; Spencer, S.; Smith, A.C.W.; Roberts-Wolfe, D.; Kalivas, P.W.; Witkin, J.M. The nucleus accumbens: Mechanisms of addiction across drug classes reflect the importance of glutamate homeostasis. Pharmacol. Rev. 2016, 68, 816–871. [Google Scholar] [CrossRef]
- Hearing, M.; Graziane, N.; Dong, Y.; Thomas, M.J. Opioid and Psychostimulant Plasticity: Targeting Overlap in Nucleus Accumbens Glutamate Signaling. Trends Pharmacol. Sci. 2018, 39, 276–294. [Google Scholar] [CrossRef]
- Vasilopoulou, C.G.; Margarity, M.; Klapa, M.I. Metabolomic analysis in brain research: Opportunities and challenges. Front. Physiol. 2016, 7, 183. [Google Scholar] [CrossRef]
- Naz, S.; Moreira Dos Santos, D.C.; García, A.; Barbas, C. Analytical protocols based on LC-MS, GC-MS and CE-MS for nontargeted metabolomics of biological tissues. Bioanalysis 2014, 6, 1657–1677. [Google Scholar] [CrossRef]
- O’Donovan, S.M.; Sullivan, C.R.; McCullumsmith, R.E. The role of glutamate transporters in the pathophysiology of neuropsychiatric disorders. NPJ Schizophr. 2017, 3, 32. [Google Scholar] [CrossRef]
- Clark, K.H.; Wiley, C.A.; Bradberry, C.W. Psychostimulant abuse and neuroinflammation: Emerging evidence of their interconnection. Neurotox. Res. 2013, 23, 174–188. [Google Scholar] [CrossRef]
- Liu, J.; Li, J.X.; Wu, R. Toll-Like Receptor 4: A Novel Target to Tackle Drug Addiction? In Handbook of Experimental Pharmacology; Springer International Publishing: Cham, Switzerland, 2022; Volume 276. [Google Scholar]
- Esmaili-Shahzade-Ali-Akbari, P.; Ghaderi, A.; Hosseini, S.M.M.; Nejat, F.; Saeedi-Mofrad, M.; Karimi-Houyeh, M.; Ghattan, A.; Etemadi, A.; Rasoulian, E.; Khezri, A. β_lactam antibiotics against drug addiction: A novel therapeutic option. Drug Dev. Res. 2023, 84, 1411–1426. [Google Scholar] [CrossRef]
- Varshneya, N.B.; Walentiny, D.M.; Moisa, L.T.; Walker, T.D.; Akinfiresoye, L.R.; Beardsley, P.M. Fentanyl-related substances elicit antinociception and hyperlocomotion in mice via opioid receptors. Pharmacol. Biochem. Behav. 2021, 208, 173242. [Google Scholar] [CrossRef]
- Falconnier, C.; Caparros-Roissard, A.; Decraene, C.; Lutz, P.E. Functional genomic mechanisms of opioid action and opioid use disorder: A systematic review of animal models and human studies. Mol. Psychiatry. 2023, 28, 4568–4584. [Google Scholar] [CrossRef]
- Lefevre, E.M.; Pisansky, M.T.; Toddes, C.; Baruffaldi, F.; Pravetoni, M.; Tian, L.; Kono, T.J.Y.; Rothwell, P.E. Interruption of continuous opioid exposure exacerbates drug-evoked adaptations in the mesolimbic dopamine system. Neuropsychopharmacology 2020, 45, 1781–1792. [Google Scholar] [CrossRef]
- Gaulden, A.D.; Burson, N.; Sadik, N.; Ghosh, I.; Khan, S.J.; Brummelte, S.; Kallakuri, S.; Perrine, S.A. Effects of fentanyl on acute locomotor activity, behavioral sensitization, and contextual reward in female and male rats. Drug Alcohol Depend. 2021, 229, 109101. [Google Scholar] [CrossRef]
- Uddin, O.; Jenne, C.; Fox, M.E.; Arakawa, K.; Keller, A.; Cramer, N. Divergent profiles of fentanyl withdrawal and associated pain in mice and rats. Pharmacol. Biochem. Behav. 2021, 200, 173077. [Google Scholar] [CrossRef] [PubMed]
- Cowan, A.; Kehner, G.B.; Inan, S. Targeting Itch With Ligands Selective for κ Opioid Receptors. In Handbook of Experimental Pharmacology; Springer International Publishing: Cham, Switzerland, 2015; Volume 226. [Google Scholar]
- Varshneya, N.B.; Hassanien, S.H.; Holt, M.C.; Stevens, D.L.; Layle, N.K.; Bassman, J.R.; Iula, D.M.; Beardsley, P.M. Respiratory depressant effects of fentanyl analogs are opioid receptor-mediated. Biochem. Pharmacol. 2022, 195, 114805. [Google Scholar] [CrossRef] [PubMed]
- Hill, R.; Santhakumar, R.; Dewey, W.; Kelly, E.; Henderson, G. Fentanyl depression of respiration: Comparison with heroin and morphine. Br. J. Pharmacol. 2020, 177, 254–265. [Google Scholar] [CrossRef]
- Bowery, N.G.; Smart, T.G. GABA and glycine as neurotransmitters: A brief history. Br. J. Pharmacol. 2006, 147, S109–S119. [Google Scholar] [CrossRef] [PubMed]
- Caspani, G.; Sebők, V.; Sultana, N.; Swann, J.R.; Bailey, A. Metabolic phenotyping of opioid and psychostimulant addiction: A novel approach for biomarker discovery and biochemical understanding of the disorder. Br. J. Pharmacol. 2022, 179, 1578–1606. [Google Scholar] [CrossRef] [PubMed]
- Meng, J.; Zhang, X.; Wu, H.; Bu, J.; Shi, C.; Deng, C.; Mao, Y. Morphine-induced conditioned place preference in mice: Metabolomic profiling of brain tissue to find ‘molecular switch’ of drug abuse by gas chromatography/mass spectrometry. Anal. Chim. Acta 2012, 710, 125–130. [Google Scholar] [CrossRef]
- Liu, R.; Cheng, J.; Yang, J.; Ding, X.; Yang, S.; Dong, F.; Guo, N.; Liu, S. GC-MS-based plasma metabolomic investigations of morphine dependent rats at different states of euphoria, tolerance and naloxone-precipitated withdrawal. Metab. Brain Dis. 2015, 30, 767–776. [Google Scholar] [CrossRef] [PubMed]
- Zaitsu, K.; Miyawaki, I.; Bando, K.; Horie, H.; Shima, N.; Katagi, M.; Tatsuno, M.; Bamba, T.; Sato, T.; Ishii, A.; et al. Metabolic profiling of urine and blood plasma in rat models of drug addiction on the basis of morphine, methamphetamine, and cocaine-induced conditioned place preference. Anal. Bioanal. Chem. 2013, 406, 1339–1354. [Google Scholar] [CrossRef] [PubMed]
- Lin, M.; Xu, J.; Liu, X.; Dai, Z.; Liu, Z.; Zhao, X.; Sun, Y.; Pu, X. Metabolomics profiling of methamphetamine addicted human serum and three rat brain areas. RSC Adv. 2019, 9, 41107–41119. [Google Scholar] [CrossRef]
- Zheng, T.; Liu, L.; Shi, J.; Yu, X.; Xiao, W.; Sun, R.; Zhou, Y.; Aa, J.; Wang, G. The metabolic impact of methamphetamine on the systemic metabolism of rats and potential markers of methamphetamine abuse. Mol. Biosyst. 2014, 10, 1968–1977. [Google Scholar] [CrossRef]
- Kaplan, K.A.; Chiu, V.M.; Lukus, P.A.; Zhang, X.; Siems, W.F.; Schenk, J.O.; Hill, H.H. Neuronal metabolomics by ion mobility mass spectrometry: Cocaine effects on glucose and selected biogenic amine metabolites in the frontal cortex, striatum, and thalamus of the rat. Anal. Bioanal. Chem. 2013, 405, 1959–1968. [Google Scholar] [CrossRef]
- Wishart, D.S.; Guo, A.C.; Oler, E.; Wang, F.; Anjum, A.; Peters, H.; Dizon, R.; Sayeeda, Z.; Tian, S.; Lee, B.L.; et al. HMDB 5.0: The Human Metabolome Database for 2022. Nucleic Acids Res. 2022, 50, D622–D631. [Google Scholar]
- Shetty, H.U.; Holloway, H.W.; Schapiro, M.B. Cerebrospinal fluid and plasma distribution of myo-inositol and other polyols in Alzheimer disease. Clin. Chem. 1996, 42, 298–302. [Google Scholar] [CrossRef]
- Haris, M.; Cai, K.; Singh, A.; Hariharan, H.; Reddy, R. In vivo mapping of brain myo-inositol. Neuroimage 2011, 54, 298–302. [Google Scholar] [CrossRef] [PubMed]
- Xuan, J.; Pan, G.; Qiu, Y.; Yang, L.; Su, M.; Liu, Y.; Chen, J.; Feng, G.; Fang, Y.; Jia, W.; et al. Metabolomic profiling to identify potential serum biomarkers for schizophrenia and risperidone action. J. Proteome Res. 2011, 10, 5433–5443. [Google Scholar] [CrossRef]
- Deng, Y.; Bu, Q.; Hu, Z.; Deng, P.; Yan, G.; Duan, J.; Hu, C.; Zhou, J.; Shao, X.; Zhao, J.; et al. 1H-nuclear magnetic resonance-based metabonomic analysis of brain in rhesus monkeys with morphine treatment and withdrawal intervention. J. Neurosci. Res. 2012, 90, 2154–2162. [Google Scholar] [CrossRef]
- Hu, Z.; Deng, Y.; Hu, C.; Deng, P.; Bu, Q.; Yan, G.; Zhou, J.; Shao, X.; Zhao, J.; Li, Y.; et al. 1H NMR-based metabonomic analysis of brain in rats of morphine dependence and withdrawal intervention. Behav. Brain Res. 2012, 231, 11–19. [Google Scholar] [CrossRef]
- Li, Y.; Yan, G.Y.; Zhou, J.Q.; Bu, Q.; Deng, P.C.; Yang, Y.Z.; Lv, L.; Deng, Y.; Zhao, J.-X.; Shao, X.; et al. 1H NMR-based metabonomics in brain nucleus accumbens and striatum following repeated cocaine treatment in rats. Neuroscience 2012, 218, 196–205. [Google Scholar] [CrossRef] [PubMed]
- Wishart, D.S. Metabolomics for investigating physiological and pathophysiological processes. Physiol. Rev. 2019, 99, 1819–1875. [Google Scholar] [CrossRef] [PubMed]
- Chen, X.; Xie, C.; Sun, L.; Ding, J.; Cai, H. Longitudinal metabolomics profiling of Parkinson’s disease-related α-synuclein A53T transgenic mice. PLoS ONE 2015, 10, e0136612. [Google Scholar] [CrossRef]
- Adkins, D.E.; Mcclay, J.L.; Vunck, S.A.; Batman, A.M.; Vann, R.E.; Clark, S.L.; Souza, R.P.; Crowley, J.J.; Sullivan, P.F.; van den Oord, E.J.C.G.; et al. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization. Genes Brain Behav. 2013, 12, 780–791. [Google Scholar] [CrossRef] [PubMed]
- McClay, J.L.; Adkins, D.E.; Vunck, S.A.; Batman, A.M.; Vann, R.E.; Clark, S.L.; Beardsley, P.M.; van den Oord, E.J.C.G. Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure. Metabolomics 2013, 9, 392–402. [Google Scholar] [CrossRef] [PubMed]
- Costa, T.B.B.C.; Lacerda, A.L.T.; Mas, C.D.; Brietzke, E.; Pontes, J.G.M.; Marins, L.A.N.; Martins, L.G.; Nunes, M.V.; Pedrini, M.; Carvalho, M.S.C.; et al. Insights into the Effects of Crack Abuse on the Human Metabolome Using a NMR Approach. J. Proteome Res. 2019, 18, 341–348. [Google Scholar] [CrossRef]
- Simons, K.; Toomre, D. Lipid rafts and signal transduction. Nat. Rev. Mol. Cell Biol. 2000, 1, 31–39. [Google Scholar] [CrossRef] [PubMed]
- Liu, K.; Czaja, M.J. Regulation of lipid stores and metabolism by lipophagy. Cell Death Differ. 2013, 20, 3–11. [Google Scholar] [CrossRef]
- Bennett, M.; Gilroy, D.W. Lipid Mediators in Inflammation. Microbiol. Spectr. 2016, 4, 343–366. [Google Scholar] [CrossRef]
- Zheng, T.; Liu, L.; Aa, J.; Wang, G.; Cao, B.; Li, M.; Shi, J.; Wang, X.; Zhao, C.; Gu, R.; et al. Metabolic phenotype of rats exposed to heroin and potential markers of heroin abuse. Drug Alcohol Depend. 2013, 127, 177–186. [Google Scholar] [CrossRef]
- Xie, P.; Wang, T.-J.; Yin, G.; Yan, Y.; Xiao, L.-H.; Li, Q.; Bi, K.-S. Metabonomic Study of Biochemical Changes in Human Hair of Heroin Abusers by Liquid Chromatography Coupled with Ion Trap-Time of Flight Mass Spectrometry. J. Mol. Neurosci. 2016, 58, 93–101. [Google Scholar] [CrossRef]
- Fukushima, T.; Iizuka, H.; Yokota, A.; Suzuki, T.; Ohno, C.; Kono, Y.; Nishikiori, M.; Seki, A.; Ichiba, H.; Watanabe, Y.; et al. Quantitative analyses of schizophrenia-associated metabolites in serum: Serum D-lactate levels are negatively correlated with gamma-glutamylcysteine in medicated schizophrenia patients. PLoS ONE 2014, 9, e101652. [Google Scholar] [CrossRef]
- Al Awam, K.; Haußleiter, I.S.; Dudley, E.; Donev, R.; Brüne, M.; Juckel, G.; Thome, J. Multiplatform metabolome and proteome profiling identifies serum metabolite and protein signatures as prospective biomarkers for schizophrenia. J. Neural Transm. 2015, 122, 111–122. [Google Scholar] [CrossRef]
- Lee, J.Y.; Jin, H.K.; Bae, J.S. Sphingolipids in neuroinflammation: A potential target for diagnosis and therapy. BMB Rep. 2020, 53, 28–34. [Google Scholar] [CrossRef] [PubMed]
- Virmani, M.A.; Cirulli, M. The Role of L-Carnitine in Mitochondria, Prevention of Metabolic Inflexibility and Disease Initiation. Int. J. Mol. Sci. 2022, 23, 2717. [Google Scholar] [CrossRef] [PubMed]
- Little, K.M.; Kosten, T.A. Focus on fentanyl in females: Sex and gender differences in the physiological and behavioral effects of fentanyl. Front. Neuroendocrinol. 2023, 71, 101096. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Alasmari, M.S.; Alasmari, F.; Alsharari, S.D.; Alasmari, A.F.; Ali, N.; Ahamad, S.R.; Alghamdi, A.M.; Kadi, A.A.; Hammad, A.M.; Ali, Y.S.M.; et al. Neuroinflammation and Neurometabolomic Profiling in Fentanyl Overdose Mouse Model Treated with Novel β-Lactam, MC-100093, and Ceftriaxone. Toxics 2024, 12, 604. https://doi.org/10.3390/toxics12080604
Alasmari MS, Alasmari F, Alsharari SD, Alasmari AF, Ali N, Ahamad SR, Alghamdi AM, Kadi AA, Hammad AM, Ali YSM, et al. Neuroinflammation and Neurometabolomic Profiling in Fentanyl Overdose Mouse Model Treated with Novel β-Lactam, MC-100093, and Ceftriaxone. Toxics. 2024; 12(8):604. https://doi.org/10.3390/toxics12080604
Chicago/Turabian StyleAlasmari, Mohammed S., Fawaz Alasmari, Shakir D. Alsharari, Abdullah F. Alasmari, Nemat Ali, Syed Rizwan Ahamad, Abdullah M. Alghamdi, Aban A. Kadi, Alaa M. Hammad, Yousif S. Mohamed Ali, and et al. 2024. "Neuroinflammation and Neurometabolomic Profiling in Fentanyl Overdose Mouse Model Treated with Novel β-Lactam, MC-100093, and Ceftriaxone" Toxics 12, no. 8: 604. https://doi.org/10.3390/toxics12080604
APA StyleAlasmari, M. S., Alasmari, F., Alsharari, S. D., Alasmari, A. F., Ali, N., Ahamad, S. R., Alghamdi, A. M., Kadi, A. A., Hammad, A. M., Ali, Y. S. M., Childers, W. E., Abou-Gharbia, M., & Sari, Y. (2024). Neuroinflammation and Neurometabolomic Profiling in Fentanyl Overdose Mouse Model Treated with Novel β-Lactam, MC-100093, and Ceftriaxone. Toxics, 12(8), 604. https://doi.org/10.3390/toxics12080604