Background: Xylazine, also called “tranq”, is a veterinary sedative increasingly present in illicit fentanyl supplies across the U.S. Unlike opioids, its effects are not reversed by naloxone leading to increased overdose risks. Chronic xylazine use has been associated with necrotic wounds raising public health and regulatory concerns. In this study, we have investigated the trends in xylazine positivity from the first reported identification in our clinical laboratory in 2020, and its co-occurrence with other drugs in urine drug screens performed at a large academic institution in the U.S.

Methods: Retrospective analysis of untargeted urine drug screens results over five years (2020-2024) included patient testing performed for both acute exposure and compliance monitoring. Presence of xylazine and other drugs and metabolites was determined by gas chromatography – mass spectrometry (GCMS). Overall positivity was calculated as a percentage of total reported results.

Results: Of the 25,580 urine drug screens analyzed, 0.44% of the specimens were positive for xylazine. Positivity increased over time from 0.06% in 2020 to 1% in 2024. Specimens containing xylazine were also positive for fentanyl (100%), cocaine (44.6%), methamphetamine (29.5%), 6-monacetylmorphine/heroin (10.7%). In specimens positive for fentanyl, co-positivity with xylazine increased from 1.55% in 2020 to 25.19% in 2024.

Conclusions: Untargeted drug screens are critical for detection of emerging drugs and adulterants. Our data reveals that fentanyl mixed with xylazine accounted for ~25% of the fentanyl positive specimens in 2024, despite a slight decrease in overall fentanyl positivity.

Key words: Xylazine, Fentanyl, Adulterants, Urine Drug Screens, Clinical Toxicology

Background: Immunoassay (IA) remains the primary method for urine drugs of abuse (DOA) screening (UDS) despite significant limitations including false positives (FP) and false negatives (FN). Our laboratories offer IA UDS reflexed to LC-MS/MS, as well as IA paired with LC-QTOF MS (QTOF) for patients in the US South region.

Aims: To understand clinical needs for UDS in opiate/opioid and amphetamine classes 2020-2024.

Methods: IA UDS (Siemens Emit on Beckman AU) reflexed to LC-MS/MS and IA UDS (Siemens Atelicca or Abbott Alinity) paired with QTOF (Sciex 4600 or 5600) were analyzed. IA reporting followed SAMHSA cutoff guidelines. Opiate/opioid class on QTOF mainly includes opiates, oxycodone, fentanyl, levorphanol, methadone (reporting cutoffs 2.5 to 50 ng/mL). IA FP and FN rates were derived using MS methods as reference.

Results: Among 114731 IA UDS, positive rate was 10% for opiate/opioid and amphetamine with a FP rate of 23.5%. In 13612 paired IA/QTOF, 840 (6.2%) were positive for amphetamine and 1102 (8.1%) for opiate/opioid on QTOF. FN rates were 79.3, 67.3, 67.9,57.9 and 64.0% for amphetamine class, 83.9, 83.2, 85.8, 76.5 and 67.1% for opiate/opioid in year 2020-2024, respectively. The lab implemented fentanyl IA in 2024 which reduced FN rates while other major opioids contributing to FN IA were levorphanol and methadone.

Conclusions: Our study demonstrates limitations of IA UDS with the well-known FP and the alarmingly high FN rates in common drug classes, underscoring the need for comprehensive and sensitive UDS, including broader adoption of MS methods.

Keywords: UDS, DOA, fentanyl, opioid, amphetamine

Background:
Metabolic disturbances in glucose metabolism, induced by atypical antipsychotic drugs, are linked to the accumulation of advanced glycation end products (AGEs) in tissues. In the brain, AGEs accumulation impairs mitochondrial function, disrupts energy metabolism, and contributes to cognitive decline.

Aims:
This study aims to explore the relationship between atypical antipsychotics, particularly clozapine, and AGEs accumulation, with a focus on their toxicological impact on brain metabolism and cognitive function.

Methods:
Clinical part: Plasma AGEs levels were measured in 57 antipsychotic-naive first-episode schizophrenia (FE-SZ) patients and 54 healthy controls (HC). Additionally, 66 chronic relapsing schizophrenia (RE-SZ) patients on clozapine and 85 HC were enrolled. Plasma AGEs levels were measured before and after 4 weeks of clozapine treatment, alongside PANSS scores. In vivo: 18F-FDG-PET imaging assessed brain glucose uptake in rats, and mitochondrial ATP production, Krebs cycle intermediates, and related enzyme expression were analyzed.

Results:
No significant difference in plasma AGEs was found between FE-SZ and HC. However, baseline AGEs levels were higher in RE-SZ patients, and these levels increased after 4 weeks of clozapine treatment, correlating with cognitive decline. 18F-FDG-PET imaging revealed reduced glucose uptake in the prefrontal cortex, accompanied by increased AGEs accumulation, reduced ATP production, and altered Krebs cycle intermediates and enzymes.

Conclusions:
Chronic clozapine exposure disrupts brain glucose metabolism and mitochondrial function, leading to AGEs accumulation. AGEs and Krebs cycle biomarkers could help monitor metabolic side effects of antipsychotics and improve cognitive outcomes in schizophrenia.

Key Words:
AGEs, clozapine, schizophrenia, mitochondrial dysfunction, glucose metabolism, cognitive impairment.

Background: Prolintane (1-(1-phenylpentan-2-yl)pyrrolidine), a synthetic central nervous system stimulant, was used for the treatment of several diseases in the past. Due to its close structural relationship with pyrrolidinophenones and the previous detection of prolintane on the drugs of abuse market, the future emergence of prolintane derivatives as new psychoactive substances cannot be excluded.

Aims: Investigation of the in vitro metabolic fate of 2-, 3-, and 4-fluorprolintane and 2-, 3-, and 4-methylprolintane.

Methods: Metabolites were tentatively identified in incubations with pooled human liver S9 fraction after 1h and 6h containing cofactors for most phase I and II reactions and 25 µM of the prolintane derivative. Individual incubations with 11 human phase I isozymes were included in a monooxygenases activity screening. Analyses were performed by reversed-phase liquid chromatography-high-resolution tandem mass spectrometry.

Results: Hydroxylations were identified as most frequent phase I reactions. Subsequent oxidation led to the formation of oxo metabolites. Combination and multiple-reactions metabolites were also observed. Only few phase II metabolites were identified in vitro and included glucuronidation and sulfation of hydroxy metabolites. The isozyme mapping revealed the contribution of various isozymes including CYP1A2, CYP2B6, CYP2C19, CYP2D6, and CYP3A4.

Conclusions: All compounds showed metabolic reactions similar to those observed for related compounds including prolintane. The contribution of several isozymes to their metabolism minimizes the risk of drug-drug interactions. The identified metabolites should be considered as analytical targets in human biosamples, especially in urine screening procedures frequently used in clinical and forensic toxicology.

Keywords: Toxicokinetics, drugs of abuse, screening targets, isozyme mapping

Background: Crizotinib, as first-line treatment for advanced ALK-positive NSCLC, induces liver injury through ferroptosis, an iron-dependent form of cell death. Magnesium isoglycyrrhizinate (MgIG), a bioactive compound derived from licorice, has shown hepatoprotective effects. However, its protective role and mechanism in crizotinib-induced liver injury remains unclear.

Aims: This study aims to investigate the protective effects of MgIG against crizotinib-induced liver injury, focusing on the modulation of the FOXO3/LPCAT3 signaling pathway.

Methods: In vitro hepatocyte models and in vivo crizotinib-induced liver injury models were used. Cell survival, lipid peroxidation, and ferroptosis-related markers were assessed. The expression of FOXO3 and LPCAT3 was analyzed using Western blotting, qPCR, and immunofluorescence. FOXO3 phosphorylation and nuclear translocation were also evaluated to examine the regulatory effect of MgIG.

Results: MgIG treatment significantly alleviated crizotinib-induced liver injury, reduced lipid peroxidation, and promoted hepatocyte survival. Mechanistically, MgIG inhibited the phosphorylation level of FOXO3 and the expression of LPCAT3. In the absence of MgIG, FOXO3 activated LPCAT3 expression, but following MgIG treatment, FOXO3's suppressive effect on LPCAT3 transcription was amplified, contributing to ferroptosis inhibition.

Conclusions: MgIG protects against crizotinib-induced liver injury by enhancing FOXO3-mediated suppression of LPCAT3 expression, thereby inhibiting ferroptosis. These findings highlight MgIG as a potential therapeutic approach for treating drug-induced liver toxicity.

Keywords: Magnesium isoglycyrrhizinate, crizotinib, liver injury, ferroptosis, FOXO3, LPCAT3

Background: Alcohol consumption can lead to serious health consequences, including motor impairments and organ failure. Testing for short-term alcohol use is typically done using blood ethanol. Gamma-glutamyl transferase (GGT), though nonspecific, is used to indicate liver disease and can serve as an indirect alcohol marker. However, more reliable biomarkers are needed, especially for transplant patients. Phosphatidyl ethanol (PEth), a group of abnormal phospholipids formed in cell membranes, has emerged as a more sensitive and specific marker for detecting heavy alcohol use.

Aims: We aimed to compare ethanol, GGT, and PEth results over three years in both general and transplant populations, focusing on transplant patients’ adherence to pre- and post-surgery abstinence.

Methods: We retrospectively analyzed the positive rates of ethanol, GGT, and PEth (18:1 and 18:2) to assess alcohol use patterns. Additionally, we compared PEth 18:1 and PEth 18:2 to determine if PEth 18:2 provides additional diagnostic value.

Results: Among the three markers, PEth identified chronic alcohol use more accurately (28% positivity) than ethanol (19%) and GGT (48%). All samples that tested positive for PEth 18:2 also had positive PEth 18:1 results, but the reverse was not true, indicating that PEth 18:1 is a more sensitive marker. Although PEth 18:1 and PEth 18:2 showed a fair correlation, no fixed percentage ratio was observed between them.

Conclusions: PEth 18:1 alone may be sufficient for detecting alcohol consumption. These findings highlight PEth’s clinical utility over ethanol and GGT, particularly for monitoring transplant patients.

Key Words: alcohol consumption, biomarkers, phosphatidyl ethanol, gamma-glutamyl transferase, transplant.

Background: Analysts face challenging problems in toxicology that lead to clinical issues. LC-MS/MS screening is difficult due to the number of molecules to be detected and the lack of MS/MS databases.

Aims: in silico DrugBank® database creation using CFM-ID_v2_v4 for clinical toxicology.

Methods: A python script was used to create an in-silico database of DrugBank® (www.go.drugbank.com, ver.5.1.12). Biotech drugs were excluded. Molecules with molecular weight, molecular formula, and Inchi structure were retained. MS/MS spectra were generated with Competitive_Fragmentation_Modeling_for_Metabolite_IDentification (CFM-ID) 2.0 or 4.0. Standards, patients or databases were queried using Metgem®, with cosine ≥ 0.2and 3 common fragments.

Results: Of the 11’928 molecules listed in DrugBank®, around 94% could be generated by CFM-ID 2.0 and 4.0. Ionized molecules or MS/MS spectra taking too long to generate are the main reasons for failure. The v.2.0 database was queried with v.4.0, 8648(77%) molecules were recognized; 10%(1195) incorrectly annotated and 13%(1387) unrecognized. Using different GNPS databases and querying DrugBank®v2/4, annotations remained similar or v4 had more hits. v2 annotated 49% of the 377 molecules in "nih_part_1" while v4 53%. v2 annotated 27% of the 1460 molecules in "small_molecules_pharmacologically_active" and v4 annotated 40%. The two training algorithms ensure the two databases remain useful and complementary.

Conclusions: Databases are a bottleneck in drug identification. The 11’000 in-silico DrugBank® database generated with CFM-ID v2 and v4 can help expand drug annotation. The two training algorithms ensure that both databases are useful to fully annotate unknown molecules in polyintoxicated patients.

Keywords: in-silico database, CFM-ID, clinical toxicology, Untargeted screening