Monica Salerno

@unifg.it

Dipartimento di Scienze Mediche, Chirurgiche e Tecnologie Avanzate - “G. F. Ingrassia”
University of Catania

Monica Salerno


            Download Compact PDF  
https://researchid.co/26031982
144

Scopus Publications

Scopus Publications

  • Estimating the Post-Mortem Interval Under Extreme Heat Environments: A Climate-Adaptive Case Series Based on Artificial Intelligence-Supported Diagnostics
    Francesco Sessa, Clelia Grippaldi, Massimiliano Esposito, Carlos A. Gutierrez, Emina Dervišević, et al.
    Diagnostics, 2026
    Background/Objectives: Accurate post-mortem interval (PMI) estimation becomes increasingly difficult when bodies decompose under extreme heat. Hyperthermal Mediterranean environments accelerate soft-tissue degradation, induce early mummification, and distort classical thanatological indicators, often resulting in substantial PMI overestimation. This study analyzes three forensic cases affected by climate-driven decomposition anomalies and presents a climate-adaptive, AI-assisted diagnostic framework applied uniformly across all cases to improve PMI interpretation. Methods: A retrospective case series analysis was conducted on three individuals recovered during summer heatwaves. Crime scene investigation, post-mortem computed tomography (PMCT), autopsy, and genetic identification were integrated with 5–15-year meteorological datasets. Classical PMI estimations were compared with circumstantial data. A multimodal AI model, incorporating environmental features, decomposition morphology, and microenvironmental modifiers, was operationalized for each case using a hybrid Random Forest–LSTM architecture. Engineered indices included Accumulated Degree Days (ADD), a Decomposition Index, and climate-stress metrics (Thermal Load Index, Desiccation Pressure Factor, Microenvironmental Distortion Coefficient). Quantile regression provided calibrated prediction intervals. Results: Morphological assessments overestimated PMI in every case, suggesting intervals of 1–6 months despite true PMIs of approximately 20 days (Cases 1–2) or 36–48 h (Case 3). The AI model yielded conceptual outputs more consistent with verified PMIs, ~21 days (Case 1), ~23 days (Case 2), and ~42 h (Case 3), each accompanied by 50% and 90% prediction intervals. Explainability analyses identified thermal load, desiccation pressure, and microenvironmental distortion, particularly insulation in Case 3, as dominant drivers. Conclusions: Extreme heat fundamentally alters decomposition trajectories, rendering classical PMI methods unreliable. Applying a climate-aware, AI-assisted diagnostic framework across all three cases improved interpretability, providing uncertainty-aware estimates aligned with true PMIs. The AI framework is presented as a conceptual, non-trained, proof-of-concept system, and reported outputs represent operational demonstrations rather than validated predictions, offering a promising foundation for next-generation PMI diagnostics in hyperthermal forensic settings.
  • AI-Assisted Diagnostic Evaluation of IHC in Forensic Pathology: A Comparative Study with Human Scoring
    Francesco Sessa, Mara Ragusa, Massimiliano Esposito, Mario Chisari, Cristoforo Pomara, et al.
    Diagnostics, 2026
    Background/Objectives: Immunohistochemistry (IHC) is a critical diagnostic tool in forensic pathology, enabling molecular-level assessment of wound vitality, post-mortem interval, and cause of death. However, IHC interpretation is subject to variability due to its reliance on human expertise. This study investigates whether artificial intelligence (AI), specifically a generative model, can assist in the diagnostic evaluation of IHC slides and replicate expert-level scoring, thereby improving consistency and reproducibility. Methods: A total of 225 high-resolution IHC images were classified into five immunoreactivity categories. The AI model (ChatGPT-4V) was trained on 150 labeled images and tested blindly on 75 unseen slides. Performance was assessed using confusion matrices, per-class precision/recall/F1, overall accuracy, Cohen’s κ (unweighted and weighted), and binary metrics (sensitivity, specificity, MCC). Results: Overall accuracy was 81.3% (95% CI: 71.1–88.5%), with substantial agreement (κ = 0.767 unweighted; 0.805 linear-weighted; 0.848 quadratic-weighted). Binary classification achieved a sensitivity of 98.3%, specificity of 93.3%, MCC of 0.92. Accuracy was highest in extreme categories (− and +++, 93.3%), while intermediate classes (+ and ++) showed reduced performance (error rates up to 33%). Evaluation was rapid and consistent but lacked interpretative reasoning and struggled with borderline cases. Conclusions: AI-assisted diagnostic evaluation of IHC slides demonstrates promising accuracy and consistency, particularly in well-defined staining patterns. While not a replacement for human expertise, AI can serve as a valuable adjunct in forensic pathology, supporting rapid and standardized assessments. Ethical and legal considerations must guide its implementation in medico-legal contexts.
  • Predicting Physical Appearance from Low Template: State of the Art and Future Perspectives
    Francesco Sessa, Emina Dervišević, Massimiliano Esposito, Martina Francaviglia, Mario Chisari, et al.
    Genes, 2026
    Background/Objectives: Forensic DNA phenotyping (FDP) enables the prediction of externally visible characteristics (EVCs) such as eye, hair, and skin color, ancestry, and age from biological traces. However, low template DNA (LT-DNA), often derived from degraded or trace samples, poses significant challenges due to allelic dropout, contamination, and incomplete profiles. This review evaluates recent advances in FDP from LT-DNA, focusing on the integration of machine learning (ML) models to improve predictive accuracy and operational readiness, while addressing ethical and population-related considerations. Methods: A comprehensive literature review was conducted on FDP and ML applications in forensic genomics. Key areas examined include SNP-based trait modeling, genotype imputation, epigenetic age estimation, and probabilistic inference. Comparative performance of ML algorithms (Random Forests, Support Vector Machines, Gradient Boosting, and deep learning) was assessed using datasets such as the 1000 Genomes Project, UK Biobank, and forensic casework samples. Ethical frameworks and validation standards were also analyzed. Results: ML approaches significantly enhance phenotype prediction from LT-DNA, achieving AUC > 0.9 for eye color and improving SNP recovery by up to 15% through imputation. Tools like HIrisPlex-S and VISAGE panels remain robust for eye and hair color, with moderate accuracy for skin tone and emerging capabilities for age and facial morphology. Limitations persist in admixed populations and traits with polygenic complexity. Interpretability and bias mitigation remain critical for forensic admissibility. Conclusions: L integration strengthens FDP from LT-DNA, offering valuable investigative leads in challenging scenarios. Future directions include multi-omics integration, portable sequencing platforms, inclusive reference datasets, and explainable AI to ensure accuracy, transparency, and ethical compliance in forensic applications.
  • Generative artificial intelligence in forensic medicine: a pilot study on AI-simulated medico-legal reports in healthcare liability cases
    Federica Ministeri, Massimiliano Esposito, Martina Francaviglia, Lucio Di Mauro, Grazia Giulia Pantè, et al.
    International Journal of Legal Medicine, 2026
  • Genetic and epigenetic determinants of fetal alcohol spectrum disorders: Toward a precision medicine approach
    Francesco Sessa, Marco Carotenuto, Davide Ferorelli, Massimiliano Esposito, Cristoforo Pomara, et al.
    Experimental and Molecular Pathology, 2025
  • Fatal Dog Attacks in Italy (2009–2025): The Urgent Need for a National Risk Registry
    Fabrizio Iarussi, Francesco Sessa, Serena Piccirillo, Martina Francaviglia, Alessandra Recchia, et al.
    Animals, 2025
    Fatal dog attacks are rare but devastating events with significant public health, forensic, and legal implications. Italy lacks a centralized registry for such incidents, limiting the ability to monitor trends and implement preventive strategies. This retrospective study analyzes all verified fatal dog attacks in Italy from 2009 to 2025. Data were collected from national and regional media, cross-verified, and organized into a comprehensive database. Descriptive statistics, chi-square tests, logistic and Poisson regressions, and interaction analyses were performed to identify patterns in victim demographics, breed involvement, ownership status, and environmental context. A total of 54 fatal attacks were recorded, with an increasing trend observed in the last five years. Elderly individuals (≥65) and preschool-aged children (≤4) were the most affected groups. Molosser and bull-type breeds were implicated in 69% of cases, and 92.6% of attacks involved owned dogs—more than half belonging to the victim. Private settings accounted for 66.7% of incidents. Comparative analysis with U.S. data revealed similar demographic and breed-related patterns, but also highlighted Italy’s lack of a centralized behavioral risk registry. Fatal dog attacks in Italy follow recurring and preventable patterns. The absence of a national database severely limits surveillance and intervention. A centralized behavioral risk registry, modeled on international systems, should be established to support early detection, policy development, and multidisciplinary collaboration.
  • Applying the WHO ICF Framework to Fetal Alcohol Spectrum Disorder (FASD): A Forensic and Clinical Perspective on Disability Assessment and Patient Support
    Davide Ferorelli, Francesco Calò, Gianmarco Sirago, Dania Comparcini, Filippo Gibelli, et al.
    Healthcare Switzerland, 2025
    Background/Objectives: This article aims to investigate the multifaceted effects of alcohol on neurophysiopathological development from gestational stages through adult life and the consequent dynamic-relational challenges in individuals with Fetal Alcohol Spectrum Disorder (FASD). FASD, resulting from prenatal alcohol exposure (PAE), is characterized by a range of neurological, cognitive, behavioral, and sometimes physical impairments. This article explores how alcohol and its toxic metabolites cross the placenta, inducing direct cellular toxicity and epigenetic alterations that disrupt critical neurodevelopmental processes such as neurogenesis and brain circuit formation. Clinically, individuals with FASD exhibit diverse deficits in executive functioning, learning, memory, social skills, and sensory-motor abilities, leading to significant lifelong disabilities. A central focus is the application of the World Health Organization’s International Classification of Functioning, Disability and Health (ICF) criteria to comprehensively frame these disabilities. The ICF’s biopsychosocial model allows for a multidimensional assessment of impairments in body functions and structures, limitations in activities, and restrictions in participation, while also considering the crucial role of environmental factors. Methods: PubMed and Semantic Scholar databases were searched for relevant papers published in English. Results: This article highlights the utility of the ICF in creating individualized functioning profiles to guide interventions and support services, addressing the limitations of traditional assessment methods. Conclusions: While the ICF framework offers a robust approach for understanding and managing FASD, further research is essential to develop and validate FASD-specific ICF-based assessment tools to enhance support and social participation for affected individuals.
  • A nationwide forensic case-series of femicides in Italy – Part 1: Clues to the motives of the murder
    Rossana Cecchi, Anna Laura Santunione, Jessika Camatti, Alice Buzzelli, Alessandra De Martina, et al.
    Legal Medicine, 2025
  • A nationwide forensic case-series of femicides in Italy – Part 2: Clues to its epidemiology, prediction and prevention
    Rossana Cecchi, Jessika Camatti, Anna Laura Santunione, Marco Vinceti, Tommaso Filippini, et al.
    Legal Medicine, 2025
  • Ethical, Legal and Social Implications (ELSI) Regarding Forensic Genetic Investigations (FGIs)
    Journal of Academic Ethics, 2025
  • Advancing Diagnostic Tools in Forensic Science: The Role of Artificial Intelligence in Gunshot Wound Investigation—A Systematic Review
    Francesco Sessa, Mario Chisari, Massimiliano Esposito, Elisa Guardo, Lucio Di Mauro, et al.
    Forensic Sciences, 2025
  • Euthanasia in Mental Disorders: Clinical and Ethical Issues in the Cases of Two Women Suffering from Depression
    Giuseppe Bersani, Angela Iannitelli, Pascual Pimpinella, Francesco Sessa, Monica Salerno, et al.
    Healthcare Switzerland, 2025
  • From Description to Diagnostics: Assessing AI’s Capabilities in Forensic Gunshot Wound Classification
    Francesco Sessa, Elisa Guardo, Massimiliano Esposito, Mario Chisari, Lucio Di Mauro, et al.
    Diagnostics, 2025
  • Impact of liquid antibacterial soap and hand sanitizer on DNA transfer in forensic investigations: an experimental study
    Francesco Sessa, Elisabetta Panepinto, Monica Salerno, Mario Chisari, Massimiliano Esposito, et al.
    Forensic Sciences Research, 2025
  • The Rise of Fentanyl: Molecular Aspects and Forensic Investigations
    Cecilia Barletta, Virginia Di Natale, Massimiliano Esposito, Mario Chisari, Giuseppe Cocimano, et al.
    International Journal of Molecular Sciences, 2025
  • Diagnostic Challenges in Uncommon Firearm Injury Cases: A Multidisciplinary Approach
    Andrea Vittorio Maria Failla, Gabriele Licciardello, Giuseppe Cocimano, Lucio Di Mauro, Mario Chisari, et al.
    Diagnostics, 2025
  • Sudden cardiac death in young adults and the role of antipsychotic drugs: a multicenter autopsy study
    Massimiliano Esposito, Pietro Zuccarello, Francesco Sessa, Emanuele Capasso, Arianna Giorgetti, et al.
    Forensic Science Medicine and Pathology, 2025
  • Respect for bioethical principles and human rights in prisons: a systematic review on the state of the art
    Massimiliano Esposito, Konrad Szocik, Emanuele Capasso, Mario Chisari, Francesco Sessa, et al.
    BMC Medical Ethics, 2024
  • Analysis of the health conditions of migrants and asylum seekers in reception centers: From scene investigation to the evaluation of signs of torture
    Forensic Science International, 2024
  • Traumatic Brain Injury as a Public Health Issue: Epidemiology, Prognostic Factors and Useful Data from Forensic Practice
    Michele Ahmed Antonio Karaboue, Federica Ministeri, Francesco Sessa, Chiara Nannola, Mario Giuseppe Chisari, et al.
    Healthcare Switzerland, 2024
  • Burnout and Stress in Forensic Science Jobs: A Systematic Review
    Claudia Lombardo, Emanuele Capasso, Giuseppe Li Rosi, Monica Salerno, Mario Chisari, et al.
    Healthcare Switzerland, 2024
  • Sudden unexpected postnatal collapse and BUB1B mutation: first forensic case report
    Massimiliano Esposito, Francesco Sessa, Chiara Nannola, Maria Serenella Pignotti, Pantaleo Greco, et al.
    International Journal of Legal Medicine, 2024
  • Forensic investigation on a combined death by food aspiration and acute escitalopram intoxication occurred to a psychiatric subject in a nursing home
    P. Zuccarello, G. Carnazza, M. Salerno, M. Esposito, S. Cosentino, et al.
    International Journal of Legal Medicine, 2024
  • Congenital heart diseases (CHDs) and forensic investigations: Searching for the cause of death
    Francesco Sessa, Mario Chisari, Monica Salerno, Massimiliano Esposito, Pietro Zuccarello, et al.
    Experimental and Molecular Pathology, 2024
  • Special Issue “Molecular Biology in Forensic Science: Past, Present and Future”
    Francesco Sessa, Monica Salerno
    International Journal of Molecular Sciences, 2024