Acute myocardial infarction (AMI) remains the leading cause of death worldwide, with myocardial ischemia/reperfusion injury (MIRI) emerging as a significant factor influencing patient outcomes despite timely reperfusion therapy. MIRI refers to paradoxical myocardial damage that occurs upon restoration of coronary blood flow and is driven by complex inflammatory, oxidative, and metabolic mechanisms, which can exacerbate infarct size (IS), contributing to adverse outcomes. This review explores the molecular and cellular pathophysiology of MIRI, emphasizing both its clinical and forensic relevance. The principal mechanisms discussed include oxidative stress and mitochondrial dysfunction, calcium overload and ion homeostasis imbalance, inflammatory responses, with particular focus on the NLRP3 inflammasome and cytokine pathways, and multiple forms of cell death (apoptosis, necroptosis, pyroptosis, and autophagy). Additionally, the authors present original immunohistochemical findings from autopsy cases of patients who suffered ST-segment elevation myocardial infarction (STEMI) and underwent percutaneous coronary intervention (PCI), but subsequently died. These findings underscore that successful reperfusion does not completely prevent delayed complications, like arrhythmias, ventricular fibrillation (VF), and sudden cardiac death (SCD), often caused by secondary MIRI-related mechanisms. Moreover, the case series highlight the diagnostic value of inflammatory markers for pathologists in identifying MIRI as a contributing factor in such fatalities. Finally, immunotherapeutic strategies—including IL-1 and IL-6 inhibitors such as Canakinumab and Tocilizumab—are reviewed for their potential to reduce cardiovascular events and mitigate the effects of MIRI. The review advocates for continued multidisciplinary research aimed at improving our understanding of MIRI, developing effective treatments, and informing forensic investigations of reperfusion-related deaths.

In 2023, hexahydrocannabinol (HHC) attracted the attention of international agencies due to its rapid spread in the illegal market. Although it was discovered in 1940, less is known about the pharmacology of its two naturally occurring epimers, 9(R)-HHC and 9(S)-HHC. Thus, we aimed to investigate the disposition of hexahydrocannabinol epimers and their metabolites in whole blood, urine and oral fluid following a single controlled administration of a 50:50 mixture of 9(R)-HHC and 9(S)-HHC smoked with tobacco. To this end, six non-user volunteers smoked 25 mg of the HHC mixture in 500 mg of tobacco. Blood and oral fluid were sampled at different time points up to 3 h after the intake, while urine was collected between 0 and 2 h and between 2 and 6 h. The samples were analyzed with a validated HPLC-MS/MS method to quantify 9(R)-HHC, 9(S)-HHC and eight metabolites. 9(R)-HHC showed the highest C_max and AUC_0–3h in all the investigated matrices, with an average concentration 3-fold higher than that of 9(S)-HHC. In oral fluid, no metabolites were detected, while they were observed as glucuronides in urine and blood, but with different profiles. Indeed, 11nor-9(R)-HHC was the most abundant metabolite in blood, while 8(R)OH-9(R) HHC was the most prevalent in urine. Interestingly, 11nor 9(S) COOH HHC was detected only in blood, whereas 8(S)OH-9(S) HHC was detected only in urine.

Recently, hexahydrocannabinol (HHC) was posed under strict control in Europe due to the increasing HHC-containing material seizures. The lack of analytical methods in clinical laboratories to detect HHC and its metabolites in biological matrices may result in related intoxication underreporting. We developed and validated a comprehensive GC-MS/MS method to quantify 9(R)-HHC, 9(S)-HHC, 9αOH-HHC, 9βOH-HHC, 8(R)OH-9(R)-HHC, 8(S)OH-9(S)HHC, 11OH-9(R)HHC, 11OH-9(S)HHC, 11nor-carboxy-9(R)-HHC, and 11nor-carboxy-9(S)-HHC in whole blood, urine, and oral fluid. A novel QuEChERS extraction protocol was optimized selecting the best extraction conditions suitable for all the three matrices. Urine and blood were incubated with β-glucuronidase at 60 °C for 2 h. QuEChERS extraction was developed assessing different ratios of Na₂SO₄:NaCl (4:1, 2:1, 1:1, w/w) to be added to 200 µL of any matrix added with acetonitrile. The chromatographic separation was achieved on a 7890B GC with an HP-5ms column, (30 m, 0.25 mm × 0.25 µm) in 12.50 min. The analytes were detected with a triple-quadrupole mass spectrometer in the MRM mode. The method was fully validated following OSAC guidelines. The method showed good validation parameters in all the matrices. The method was applied to ten real samples of whole blood (n = 4), urine (n = 3), and oral fluid (n = 3). 9(R)-HHC was the prevalent epimer in all the samples (9(R)/9(S) = 2.26). As reported, hydroxylated metabolites are proposed as urinary biomarkers, while carboxylated metabolites are hematic biomarkers. Furthermore, 8(R)OH-9(R)HHC was confirmed as the most abundant metabolite in all urine samples.

Background: Oxycodone is a widely prescribed semi-synthetic opioid central to pain management. However, establishing its role in death when detected in postmortem toxicology is challenging. Quantitative evidence to support forensic interpretation remains limited. Methods: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines. PubMed and Scopus were searched through 3 March 2026, for studies reporting quantitative postmortem oxycodone concentrations in human biological matrices. Peripheral blood was predefined as the primary matrix for quantitative synthesis. Random-effects meta-analysis with restricted maximum likelihood estimation was performed on logarithmically transformed concentrations to compare fatal intoxications versus non-intoxication deaths and mono- versus mixed-intoxication cases. Pooled estimates were reported as geometric mean concentrations with 95% confidence and prediction intervals. Secondary analyses evaluated metabolite-to-parent ratios, alternative matrices, and postmortem interval (PMI). Results: Twenty-three studies comprising 4335 oxycodone-positive decedents were included in the qualitative synthesis, and 14 studies in the quantitative meta-analysis. Fatal intoxication cases (n = 1555) showed a pooled geometric mean peripheral blood oxycodone concentration of 0.37 mg/L (95% CI: 0.24–0.58; I² = 93.5%), compared with 0.08 mg/L (95% CI: 0.04–0.15; I² = 98.5%) in non-intoxication deaths (n = 1409). Mono-intoxication cases (n = 135) exhibited higher concentrations (0.52 mg/L; 95% CI: 0.22–1.21; I² = 82.3%) than mixed-drug fatalities (n = 511; 0.29 mg/L; 95% CI: 0.13–0.65; I² = 93.1%). Metabolite data indicated that noroxycodone and oxymorphone patterns may assist in distinguishing acute intake and metabolic variability. Alternative matrices, particularly vitreous humor and solid tissues provided complementary interpretative information, while PMI contributed concentration variability. Conclusions: The key quantitative findings of this meta-analysis indicate higher peripheral blood oxycodone levels in fatal intoxications than in non-intoxication deaths. However, substantial heterogeneity precludes the definition of absolute concentration cut-offs, emphasizing the need to approach postmortem oxycodone interpretation within a probabilistic forensic framework integrating circumstantial evidence, sampling time, metabolite ratios, and data from alternative biological matrices.

Artificial intelligence (AI) is being investigated as a means to advance forensic histopathology from visual description to quantitative mapping, pattern recognition, and multimodal reconstruction of death. Recent developments in human postmortem analysis include validated whole-slide digitisation as foundational infrastructure and task-specific AI applications for diatom detection, glomerular quantification, coronary morphometry, myocardial classification, immunohistochemistry scoring, and virtual staining. AI-based postmortem interval (PMI) estimation remains experimental; the multi-organ study referenced in this commentary utilised an animal model, and human forensic validity has not yet been established. Foundation and vision-language models may ultimately extend these capabilities across organs and integrate microscopic findings with autopsy, toxicological, radiological, and circumstantial evidence. Postmortem tissue, however, is subject to autolysis, decomposition, agonal events, resuscitation, and non-standardised sampling, while the reference diagnosis is often a probabilistic whole-case opinion rather than an objective slide label. This work introduces FORENS-AI (FORensic Histopathology Evidence Network and Safeguards for AI), a conceptual architecture designed to convert computational outputs into traceable medicolegal evidence. FORENS-AI has not been empirically validated and is not presented as a standard, scoring system, clinical decision rule, or practice recommendation. The framework represents findings as an evidence graph, separates the Slide, Case, and Claim Gates, and proposes progressively stronger validation as outputs move from measurement to temporal, mechanistic, or causal inference. The primary aim is not to automate certification of death, but to identify safeguards to evaluate before AI-derived histological findings are permitted to inform expert opinion.