Toxicokinetics of MDMA and Its Metabolite MDA in Rats.

OBJECTIVES: To investigate the toxicokinetic differences of 3,4-methylenedioxy-N-methylamphetamine (MDMA) and its metabolite 4,5-methylene dioxy amphetamine (MDA) in rats after single and continuous administration of MDMA, providing reference data for the forensic identification of MDMA. METHODS: A total of 24 rats in the single administration group were randomly divided into 5, 10 and 20 mg/kg experimental groups and the control group, with 6 rats in each group. The experimental group was given intraperitoneal injection of MDMA, and the control group was given intraperitoneal injection of the same volume of normal saline as the experimental group. The amount of 0.5 mL blood was collected from the medial canthus 5 min, 30 min, 1 h, 1.5 h, 2 h, 4 h, 6 h, 8 h, 10 h, 12 h after administration. In the continuous administration group, 24 rats were randomly divided into the experimental group (18 rats) and the control group (6 rats). The experimental group was given MDMA 7 d by continuous intraperitoneal injection in increments of 5, 7, 9, 11, 13, 15, 17 mg/kg per day, respectively, while the control group was given the same volume of normal saline as the experimental group by intraperitoneal injection. On the eighth day, the experimental rats were randomly divided into 5, 10 and 20 mg/kg dose groups, with 6 rats in each group. MDMA was injected intraperitoneally, and the control group was injected intraperitoneally with the same volume of normal saline as the experimental group. On the eighth day, 0.5 mL of blood was taken from the medial canthus 5 min, 30 min, 1 h, 1.5 h, 2 h, 4 h, 6 h, 8 h, 10 h, 12 h after administration. Liquid chromatography-triple quadrupole tandem mass spectrometry was used to detect MDMA and MDA levels, and statistical software was employed for data analysis. RESULTS: In the single-administration group, peak concentrations of MDMA and MDA were reached at 5 min and 1 h after administration, respectively, with the largest detection time limit of 12 h. In the continuous administration group, peak concentrations were reached at 30 min and 1.5 h after administration, respectively, with the largest detection time limit of 10 h. Nonlinear fitting equations for the concentration ratio of MDMA and MDA in plasma and administration time in the single-administration group and continuous administration group were as follows: T=10.362C-1.183, R2=0.974 6; T=7.397 3C-0.694, R2=0.961 5 (T: injection time; C: concentration ratio of MDMA to MDA in plasma). CONCLUSIONS: The toxicokinetic data of MDMA and its metabolite MDA in rats, obtained through single and continuous administration, including peak concentration, peak time, detection time limit, and the relationship between concentration ratio and administration time, provide a theoretical and data foundation for relevant forensic identification.

Targeting cAMP in D1-MSNs in the nucleus accumbens, a new rapid antidepressant strategy.

Studies have suggested that the nucleus accumbens (NAc) is implicated in the pathophysiology of major depression; however, the regulatory strategy that targets the NAc to achieve an exclusive and outstanding anti-depression benefit has not been elucidated. Here, we identified a specific reduction of cyclic adenosine monophosphate (cAMP) in the subset of dopamine D1 receptor medium spiny neurons (D1-MSNs) in the NAc that promoted stress susceptibility, while the stimulation of cAMP production in NAc D1-MSNs efficiently rescued depression-like behaviors. Ketamine treatment enhanced cAMP both in D1-MSNs and dopamine D2 receptor medium spiny neurons (D2-MSNs) of depressed mice, however, the rapid antidepressant effect of ketamine solely depended on elevating cAMP in NAc D1-MSNs. We discovered that a higher dose of crocin markedly increased cAMP in the NAc and consistently relieved depression 24 h after oral administration, but not a lower dose. The fast onset property of crocin was verified through multicenter studies. Moreover, crocin specifically targeted at D1-MSN cAMP signaling in the NAc to relieve depression and had no effect on D2-MSN. These findings characterize a new strategy to achieve an exclusive and outstanding anti-depression benefit by elevating cAMP in D1-MSNs in the NAc, and provide a potential rapid antidepressant drug candidate, crocin.

Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances.

Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depended on the similar chemical structures and pharmacological action with known drugs. Such approaches could not face the complicated circumstance of emerging new psychoactive substances. Herein, mass spectrometry imaging and convolutional neural networks (CNN) were used for preliminary screening and pre-classification of suspected psychoactive substances. Mass spectrometry imaging was performed simultaneously on two brain slices as one was from blank group and another one was from psychoactive substance-induced group. Then, fused neurotransmitter variation mass spectrometry images (Nv-MSIs) reflecting the difference of neurotransmitters between two slices were achieved through two homemade programs. A CNN model was developed to classify the Nv-MSIs. Compared with traditional classification methods, CNN achieved better estimation accuracy and required minimal data preprocessing. Also, the specific region on Nv-MSIs and weight of each neurotransmitter that affected the classification most could be unraveled by CNN. Finally, the method was successfully applied to assist the identification of a new psychoactive substance seized recently. This sample was identified as cannabinoids, which greatly promoted the screening process.

Three-dimensional rose-like zinc oxide fiber coating for simultaneous extraction of polychlorinated biphenyls and polycyclic aromatic hydrocarbons by headspace solid phase microextraction.

The three-dimensional (3D) rose-like zinc oxide (ZnO) material was prepared by a simple one-step CTAB-assisted hydrothermal strategy and used as a headspace solid-phase microextraction (HS-SPME) coating. Polychlorinated biphenyls (PCBs) and polycyclic aromatic hydrocarbons (PAHs) were analyzed by gas chromatography with flame ionization detector (GC-FID), and conclusively applied to ultrasensitive detection in lake and river water. Compared with one-dimensional (1D) pencil-like ZnO, the layer-by-layer petal-like structure could fully expose mass adsorption sites on the surface, which could significantly improve the adsorption. The enrichment factors with 7535-8595 for PCBs and 3855-7320 for PAHs were achieved. The established method provided a satisfactory linear range (0.005-30 ng·mL-1), coefficient (R2 > 0.9978), ultra-low limit detection (1-3 pg·mL-1), and long service life (≥ 150 times). The recoveries of 83.42-120.86 % were obtained in the real detection application of lake and river water. This work demonstrated that 3D rose-like ZnO with low cost, simple synthesis, fast extraction ability and high enrichment performance was an ideal coating material, which was hoped to enrich other compounds with similar structures with PCBs and PAHs.

Revealing Disparities in Porous Networks Between Yttria Aerogel Assemblies with Nanosheets and Nanoparticles and Their Ultrathermal Insulation and Optical Properties.

Recent advancements have introduced anisotropic structures, particularly 2D nanosheets, into aerogels, resulting in unique morphologies and exceptional properties that differ from those assembled by isotropic nanoparticles. However, exploration of the distinct porous networks and the resulting properties is limited. We focus on rare earth yttria (Y2O3) aerogels as a case in point and demonstrate the synthesis of aerogels with nanosheet and nanoparticle assemblies using elaborative sol-gel chemistry. With the aid of X-ray computed tomography, three-dimensional visualizations of the aerogels provide relative compressive views of the porous network, revealing that the Y2O3 aerogel assembled by nanosheets possesses a hierarchical pore structure characterized by uneven pore distribution, particularly the presence of macropores throughout; in contrast, these consist of nanoparticles exhibiting a relative uniform pore distribution. High-temperature examinations indicate that the nanosheet aerogels are much more stable with a specific surface area of 64 m2·g-1 after being exposed at 1300 °C; meanwhile, the aerogels present durable and efficient thermal insulation performances. The exceptional thermal properties are attributed to the synergistic effects of the nanosheets' crystalline nature and the hierarchical porous network. The nanosheet Y2O3 aerogel also exhibited superior luminescent emission characteristics, further enhancing its potential for various applications. Our findings provide further insights into optimization of the microstructures in nanoporous aerogels, particularly through the utilization of anisotropic nanosheets.

Cbf-14, a cationic peptide derived from cathelin-domain, exhibits anti-inflammation activity via inhibiting PI3K- Akt /ROS/ NF-κB signaling pathway.

Cbf-14 with the sequence RLLRKFFRKLKKSV, is an effective antimicrobial peptide derived from a cathelin-like domain. Previous reports have demonstrated that Cbf-14 not only exerts antimicrobial activity against penicillin-resistant bacteria but also alleviates bacterial-induced inflammation in E. coli BL21 (DE3)-NDM-1-infected mice. In this article, we demonstrated that Cbf-14 can effectively reduce RAW 264.7 intracellular infection caused by clinical strain E. coli and alleviate the inflammatory response of cells and improve cell survival after infection. Therefore, we established the LPS-stimulated RAW 264.7 cell inflammation model to uncover the molecular mechanisms of the peptide Cbf-14 in anti-inflammatory activity. The results reveal that Cbf-14 can decrease LPS-induced ROS secretion by blocking the membrane translocation of p47-phox subunits and suppressing p47-phox protein phosphorylation. Meanwhile, this peptide can down-regulate the over-expression of iNOS, and finally inhibit the NO excessive secretion from RAW 264.7 macrophages stimulated by LPS. Moreover, Cbf-14 also down-regulates the expression levels of p-IκB and p-p65 and inhibits the nuclear translocation of NF-κB through blocking MAPK- and/or PI3K-Akt signaling pathways. Overall, Cbf-14 exhibits anti-inflammatory activity through inhibiting NF-κB activity and ROS production via PI3K- Akt signaling pathway.

Preparation of poly(methacrylic acid-co-ethylene glycol dimethacrylate)-functionalized magnetic polydopamine nanoparticles for the extraction of six cannabinoids in wastewater followed by UHPLC-MS/MS.

Phytocannabinoids and their synthetic analogs (natural and synthetic cannabinoids) are illicit drugs that are widely abused worldwide. Wastewater-based epidemiology (WBE) is an objective approach for the estimation of population-level exposure to a wide range of substances, especially drugs of abuse. However, the concentrations of cannabinoids in wastewater are extremely low (frequently at the levels of nanograms per liter), and the existing pretreatment procedures for wastewater have the disadvantages of time-consumption or low extraction recoveries. This study aimed to propose a novel poly (methacrylic acid-co-ethylene glycol dimethacrylate)-functionalized polydopamine-coated Fe3O4 nanoparticle (Fe3O4@PDA@poly (MAA-co-EGDMA)) as an adsorbent, and provide a highly sensitive quantitative analytical technique for the detection of five synthetic cannabinoids (SCs: 5 F-EDMB-PINACA, FUB-APINACA, MDMB-4en-PINACA, MDMB-FUBINACA, and PB-22) and one cannabis-related human metabolite (THC-COOH) in wastewater. The magnetic adsorbents were fully characterized by transmission electron microscopy (TEM), infrared spectroscopy (IR), vibrating sample magnetometry (VSM) and X-ray photoelectron spectroscopy (XPS). Subsequently, an MSPE-UHPLC-MS/MS method was developed and validated for the determination of six trace analytes in wastewater. The validation results showed that the method has limits of quantification as low as 0.1-1.0 ng/L. Additionally, the recoveries ranged from 62.81 to 124.02%, and the relative standard deviations (RSDs) of intraday and interday precision were less than 15%. This MSPE-UHPLC-MS/MS method was successfully applied to real wastewater samples, and the whole analytical process of one sample from pretreatment to the obtained quantitative results was completed in less than 30 min. Thus, the proposed method based on Fe3O4@PDA@poly (MAA-co-EGDMA) is a convenient, rapid, sensitive and reliable method for the determination of trace psychoactive drugs in wastewater.

Construction of hierarchically porous metal-organic framework HP-UiO-66-30% for sensitive determination of benzoylurea insecticides.

Due to widespread application of benzoylurea insecticides (BUs) and its persistence in environment, the effective capture of benzoylurea insecticides residues in environment is an important issue of environmental safety monitoring. To obtain excellent adsorption performance, creating defective structure in metal-organic frameworks (MOFs) can be employed as the method for adjusting its properties. Zirconium(Ⅳ)-based MOF termed as UiO-66-30% was constructed with 2-aminoterephthalic acid (NH2-BDC) and terephthalic acid (H2BDC) as building blocks. After calcination and removal of thermal-sensitive ligand (NH2-BDC), hierarchically porous UiO-66-30% (HP-UiO-66-30%) with multistage pore structure and good stability was obtained. The unique structure of HP-UiO-66-30% endowed it to achieve instantaneous equilibrium (within 2 min) when it was used as a dispersed solid phase extraction (d-SPE) adsorbent to extract BUs from environmental samples, greatly reducing the operation time. A wide linear range (0.05-200 ng mL-1), good linearity (R2 ≥ 0.9980), low detection limits (0.01-0.03 ng mL-1) and quantification limits (0.05-0.1 ng mL-1) were obtained for BUs. In addition, the HP-UiO-66-30% material possessed the good reusability and the adsorption capacity did not change significantly over 16 adsorption-desorption cycles. Finally, the established dispersed solid phase extraction-high performance liquid chromatography-diode array detector (d-SPE-HPLC-DAD) method was successfully applied to determination of BUs residues in environmental soil samples. The results demonstrated that HP-UiO-66-30% was an excellent sorbent for extraction BUs from environmental samples.

Cucurbituril-protected dual-readout gold nanoclusters for sensitive fentanyl detection.

A large number of cases showed that fentanyl (FEN) has become the main cause of death from illegal drug overdose owing to its potent effect on respiratory depression, which has emerged as a grave threat to public health and safety. However, traditional analytical methods require cost-prohibitive equipment, complex pretreatment procedures, and technically trained experts, thus highlighting the urgent need to develop a cost-effective, straightforward, and highly sensitive method to detect FEN. This work demonstrated a dual-readout sensor FGGC-AuNCs@Q7 for FEN detection, which is based on the molecular recognition and self-assembly between the macrocycle cucurbit[7]uril (Q7) and FEN, accompanying spontaneous visual Tyndall effect and fluorescence optical responses of the gold nanoclusters within seconds. A detection limit of 1 ng mL-1 and a linear range of 9 to 148 000 ng mL-1 were achieved for fluorescence detection on FEN, with favorable selectivity in the presence of other illicit drugs or common interferents. The proposed method has been proved by its satisfactory application for the analysis of human urine.

Machine Learning-Assisted Rapid Screening of Four Types of New Psychoactive Substances in Drug Seizures.

Over the past few years, new psychoactive substances (NPS) have become a global health and social problem because of their wide variety, constant structural renewal, vague legal definitions, and rapid adaptation to legal restrictions. The rapid structural modifications of NPS have posed significant challenges for the screening and identification of these new substances using traditional mass spectrometric techniques based on reference substances or a mass spectral database. Here, we propose supervised machine learning (ML) classification models such as k-nearest neighbors, support vector machine, random forest, and multigrained cascade forest for the rapid screening of NPS using mass spectrometric data. This approach utilizes ML methods to learn the statistical probability distributions of mass spectral data for NPS and non-NPS. Four classification ML models were generated and evaluated using a data set comprising 567 LC-MS and 732 GC-MS spectra. Through cross validation, we achieved an F1 score of 0.35-0.97. These algorithms were applied in conjunction with mass spectrometry techniques for the detection of six seizures including electronic cigarette oil and suspected powdered substances netted in drug trafficking cases. The models provided warning signals for synthetic cannabinoids, synthetic cathinones, and fentanyl. Thus, an early warning system was successfully established, which provided a useful method for reliable and effective identifications of unknown NPS.

Supramolecular structure of microwave treated bamboo for production of lignin-containing nanocellulose by oxalic acid dihydrate.

Supramolecular structure of cellulosic materials from microwave treatment were throughly investigated for production of lignin-containing nanocellulose. The results revealed that both the intermolecular and intramolecular hydrogen bonds were altered by microwave irradiation. Cellulose Iß was the main component in microwave treated bamboo (MTB) with smaller interplanar spacing, and the cellulose molecules were loosely connected resulting in a loose structure. Thereafter, MTB was used to produce lignin-containing nanocellulose by using oxalic acid dihydrate (OAD) to test the feasibility on its efficiency. The chemical consumed for the preparation of lignin-containing nanocellulose (LCN) with a comparable yield (68.08-82.33 %) from MTB was merely 1/10 that from conventional cellulosic materials, indicating the supramolecular structural changes of bamboo cellulose induced by microwave treatment provided suitable conditions for the subsequent hydrolysis of OAD to prepare LCN. The LCN was further added into the polyvinyl alcohol (PVA) matrix endowed excellent UV shielding property and thermal stability for the PVA/LCN films. This study was aimed to provide an environmentally friendly method on the production and application of LCN from bamboo by employing microwave treatment from the perspective of supramolecular level.

A comparative study of postmortem distribution and postmortem diffusion of tramadol in rabbits.

In recent years, the cases of tramadol intoxication have become more frequent in many countries. However, most of the previous studies have been based on cases of tramadol intoxication, and the detailed information on the differences between postmortem distribution and diffusion of tramadol remains unclear. To investigate this issue systematically, we established a postmortem distribution model and two postmortem diffusion models. Then, gas chromatography-mass spectrometry (GC/MS) was used to measure the concentrations of tramadol in various biological specimens of fluids and tissues. In postmortem distribution, the results showed an uneven distribution of tramadol in various biological specimens, and the concentrations of tramadol in urine were significantly higher than those in other fluids. In postmortem diffusion, the results showed a dosage-dependent increase of tramadol concentration in most specimens; at all time points from 0.25 to 6 h after postmortem administration, the concentrations of tramadol in fluids were not significantly different from those in tissues, and the concentrations of tramadol in urine were lower than those in both tissues and other fluids in most time points. We recommend a quantitative examination of the specimens of both fluids and tissues to provide more evidence for the forensic identification, and the realization that there is a correlation between the concentrations of fluids and tissues is important for determining antemortem and postmortem administration of tramadol. This information can serve as ancillary data in inferring the contribution of a drug to death in cases of suspected tramadol poisoning.

Estimating the prevalence of hypertension in 164 cities in China by wastewater-based epidemiology.

Hypertension is the most common chronic non-infectious disease and a severe problem for public health in China. There were 244.5 million people aged over 18 years in China who had hypertension in 2015, and hypertension-related death accounted for more than 25 % of all causes of death in China every year. To monitor the hypertension prevalence in near real-time, a wastewater-based epidemiology (WBE) approach by using metoprolol acid as a biomarker was conducted in 164 cities in China. LC-MS/MS was utilized to quantify metoprolol acid in sewage, and satisfactory method validation results were achieved. The average concentration of metoprolol acid in sewage was 943.1 ± 671.1 ng/L, and the back-calculated consumption of metoprolol based on metoprolol acid was 932.0 ± 390.5 mg/day/1000inh on average, ranging from 76.7 to 3275.7 mg/day/1000inh. The prevalence of metoprolol was estimated to be 0.83 % ± 0.35 %, and the estimated hypertension prevalence in the population aged over 15 years was ultimately assessed to be 28.56 % ± 10.44 % ranging from 14.28 % to 44.28 % and was consistent with the China Hypertension Survey result of 27.9 %. This research demonstrated that estimating hypertension prevalence by WBE with metoprolol acid as a biomarker is feasible in Chinese cities.

Intermittent ultrasound retains cellulases unlock for enhanced cellulosic ethanol with high-porosity biochar for dye adsorption using desirable rice mutant straw.

In this study, optimal ultrasound pretreatment was performed with recalcitrance-reduced rice mutant straw to effectively extract lignin and hemicellulose for improved cellulose accessibility. Intermittent ultrasound-assistant enzymatic hydrolyses were followed to maintain more cellulases unlock and less cellulose surface block with lignin for raised hexose yield at 81 % (% cellulose) and bioethanol concentration at 9.9 g/L, which was higher than those of other mechanical pretreatments as previously conducted. Using all enzyme-undigestible lignocellulose residues, this work generated the biochar with the highest porosity (SBET at 2971 m2/g) among all biomass-based biochar obtained from previous studies. Furthermore, the biochar were respectively examined with high adsorption capacity for Congo red and methylene blue at 7946 mg/g and 861 mg/g. Therefore, this study has demonstrated a green-like process technology for high-yield bioethanol and high-porosity biochar with full biomass utilization by integrating optimal ultrasound pretreatment with intermittent ultrasound-assistant enzymatic hydrolyses of recalcitrance-reduced lignocellulose in crop straws.

Identification of Biomarkers for Methamphetamine Exposure Time Prediction in Mice Using Metabolomics and Machine Learning Approaches.

Methamphetamine (METH) abuse has become a global public health and safety problem. More information is needed to identify the time of drug abuse. In this study, methamphetamine was administered to male C57BL/6J mice with increasing doses from 5 to 30 mg kg-1 (once a day, i.p.) for 20 days. Serum and urine samples were collected for metabolomics studies using gas chromatography-mass spectrometry (GC-MS). Six machine learning models were used to infer the time of drug abuse and the best model was selected to predict administration time preliminarily. The metabolic changes caused by methamphetamine were explored. As results, the metabolic patterns of methamphetamine exposure mice were quite different from the control group and changed over time. Specifically, serum metabolomics showed enhanced amino acid metabolism and increased fatty acid consumption, while urine metabolomics showed slowed metabolism of the tricarboxylic acid (TCA) cycle, increased organic acid excretion, and abnormal purine metabolism. Phenylalanine in serum and glutamine in urine increased, while palmitic acid, 5-HT, and monopalmitin in serum and gamma-aminobutyric acid in urine decreased significantly. Among the six machine learning models, the random forest model was the best to predict the exposure time (serum: MAE = 1.482, RMSE = 1.69, R squared = 0.981; urine: MAE = 2.369, RMSE = 1.926, R squared = 0.946). The potential biomarker set containing four metabolites in the serum (palmitic acid, 5-hydroxytryptamine, monopalmitin, and phenylalanine) facilitated the identification of methamphetamine exposure. The random forest model helped predict the methamphetamine exposure time based on these potential biomarkers.

The metaverse in education: Definition, framework, features, potential applications, challenges, and future research topics.

The declaration of the COVID-19 pandemic forced humanity to rethink how we teach and learn. The metaverse, a 3D digital space mixed with the real world and the virtual world, has been heralded as a trend of future education with great potential. However, as an emerging item, rarely did the existing study discuss the metaverse from the perspective of education. In this paper, we first introduce the visions of the metaverse, including its origin, definitions, and shared features. Then, the metaverse in education is clearly defined, and a detailed framework of the metaverse in education is proposed, along with in-depth discussions of its features. In addition, four potential applications of the metaverse in education are described with reasons and cases: blended learning, language learning, competence-based education, and inclusive education. Moreover, challenges of the metaverse for educational purposes are also presented. Finally, a range of research topics related to the metaverse in education is proposed for future studies. We hope that, via this research paper, researchers with both computer science and educational technology backgrounds could have a clear vision of the metaverse in education and provide a stepping stone for future studies. We also expect more researchers interested in this topic can commence their studies inspired by this paper.

Simultaneous quantification of 106 drugs or their metabolites in nail samples by UPLC-MS/MS with high-throughput sample preparation: Application to 294 real cases.

The nail is an alternative matrix to complement hair analysis in proving drug intake over several months in forensic toxicology investigations. However, because of the high hardness and toughness of nails, the existing pretreatment procedures for nails have the disadvantages of either a high degree of time consumption (from hours to days), or low extraction recoveries. This study aims to propose a high-throughput nail sample preparation method and provide a quantitative analytical method for 106 drugs and their metabolites present in nail. We developed cryogenic grinding, coupled with high-speed grinding in the extraction solvent method, which could improve the extraction recovery by thoroughly destroying the nail keratin for approximately 18 min. Subsequently, an ultra-high-performance liquid chromatography-tandem mass spectrometry method was developed for the identification and quantification of 34 synthetic cannabinoids, 26 fentanyls, 18 synthetic cathinones, 10 phenylethylamines, eight opioids, three phencyclidine, two tryptamines, two piperazine, cocaine, benzoylecgonine, and tetrahydrocannabinol (THC). Nail samples were collected from people with a history of drug abuse from five different regions of China. The analysis of 294 authentic samples resulted in 213 detected samples, and showed a broad concentration range including 5.04-67.26 pg/mg for nine synthetic cannabinoids, 109.29-250.29 pg/mg for a synthetic cathinone, 5.06-434291 pg/mg for four phenylethylamines, 5.06-464278 pg/mg for three phencyclidine, 5.50-192195 pg/mg for six opioids, 19.44-36.11 pg/mg for cocaine, and 50.53 pg/mg for THC in nail. Furthermore, up to 10 different compounds were detected in a single nail sample. This nail analysis method serves as a useful tool for the large-scale surveillance of illicit drugs abuse.

A comparison of reinforcing effectiveness and drug-seeking reinstatement of 2-fluorodeschloroketamine and ketamine in self-administered rats.

2-Fluorodeschloroketamine (2F-DCK), a structural analog of ketamine, has been reported to cause impaired consciousness, agitation, and hallucination in abuse cases. It has similar reinforcing and discriminative effects as ketamine. However, the reinforcing efficacy and drug-seeking reinstatement of this analog have not been clarified to date. In this study, the effectiveness of 2F-DCK and ketamine was compared using a behavioral economics demand curve. The reinstatement of 2F-DCK- and ketamine-seeking behaviors induced by either conditioned cues or self-priming was also analyzed. Rats were intravenously self-administered 2F-DCK and ketamine at a dose of 0.5 mg/kg/infusion under a reinforcing schedule of fixed ratio 1 (FR1) with 4 h of daily training for at least 10 consecutive days. The elasticity coefficient parameter α and the essential value of the demand curve in the two groups were similar. Both groups of rats showed significant drug-seeking behavior induced either by conditional cues or by 2F-DCK and ketamine priming. Moreover, the α parameter was inversely related to the degree of reinstatement induced by cues or drug priming in both groups. In total, the expression levels of brain-derived neurotrophic factor (BDNF) and phosphorylated cAMP response element-binding protein (p-CREB) in the nucleus accumbens in both extinguished and reinstated rats were significantly lower than those in the control. The expression of total Akt, glycogen synthase kinase (GSK)-3ß, mammalian target of rapamycin (mTOR), and extracellular signal-related kinase (ERK) also decreased, but p-Akt, p-GSK-3ß, p-mTOR, and p-ERK levels increased in both extinguished and reinstated rats. This is the first study to demonstrate that 2F-DCK has similar reinforcing efficacy, effectiveness, and post-withdrawal cravings as ketamine after repeated use. These data suggest that the downregulation of CREB/BDNF and the upregulation of the Akt/mTOR/GSK-3ß signaling pathway in the nucleus accumbens may be involved in ketamine or 2F-DCK relapse.

N-isopropylbenzylamine, a methamphetamine mimics, produces toxicity via increasing nitric oxide in vitro.

N-isopropylbenzylamine, an isomer of methamphetamine, has been used to adulterate methamphetamine, and distributed as fake "Ice" methamphetamine by illicit manufacturers, leading to a world problem of N-isopropylbenzylamine exposure. Though it is unclear whether N-isopropylbenzylamine has addictive potential like methamphetamine, N-isopropylbenzylamine users reported side effects such as headaches and confusion. However, the pharmacological targets and cytotoxicity of this chemical remained unknown. In this study, in vitro toxicity of N-isopropylbenzylamine and its toxicity-related targets were investigated in SN4741, SH-SY5Y or PC12 cell lines that model neurons. The cell viability was analyzed by using MTT assay after incubation with N-isopropylbenzylamine for 24 h in cells. N-isopropylbenzylamine caused cell death with IC50 values at around 1-3 mM in these cell lines. N-isopropylbenzylamine time- and concentration-dependently facilitated the expression of neuronal nitric oxide synthase (nNOS), and increased intracellular nitric oxide (NO) in SN4741 cells. Furthermore, 7-nitroindazole, a specific inhibitor of nNOS, significantly prevented N-isopropylbenzylamine-induced toxicity in vitro. These results suggested that N-isopropylbenzylamine-induced toxicity is at least partially related to the increased intracellular NO levels and the activated nNOS. Considering the circumstances that N-isopropylbenzylamine was used to adulterate and mimic methamphetamine, and the side effects associated with N-isopropylbenzylamine in abusers, our findings sounded an alarm for abuser and warn the dangerousness of N-isopropylbenzylamine for public health.

Induction of CYP450 by illicit drugs: Studies using an in vitro 3D spheroidal model in comparison to animals.

Information regarding the metabolism of illicit drugs is under urgent need for toxicological assessment. Its development, however, is limited by the currently available animal models. To this end, we proposed three-dimensional (3D) HepaRG spheroids as an in vitro model to study the effects of illicit drugs on hepatic cytochrome P450 (CYP450) enzymes and potential drug-drug interactions (DDIs). By comparing the results from animal and cell experiments, we confirmed the significant impact of heroin, morphine, tetrahydrocannabinol, and fentanyl on CYP450 enzymes, and the 3D spheroids results were in good agreement with the animal results for 2B6, 2C19, 2D6. Using 3D HepaRG spheroids, we demonstrated DDIs between heroin as a 2B6 perpetrator and clinical medicine for cancer, depression, and illicit drug withdrawal. Specifically, the clearance rate of 5.4 µM bupropion was increased by 214 % under DDI with 5 µM heroin, highlighting the importance of DDI pre-screening and individualized medication guidance for illicit drug users. This research contributes to the growing body of evidence regarding the metabolic toxicity of illicit drugs and suggests 3D HepaRG spheroids as a high-throughput and cost-efficient platform for DDI analysis.