The following narrative review discusses the use of deep learning and 3D modeling in facial reconstruction from skeletal remains, focusing on accuracy, algorithmic bias, and evidential reliability. Forensic facial reconstruction (FFR) is a multidisciplinary field combining anthropology, medicine, and visual sciences to approximate the facial appearance of unidentified individuals from skeletal remains. Traditional manual methods, based on anatomical knowledge and facial soft tissue thickness (FSTT) measurements, are limited by subjectivity, labor intensity, and inter-expert variability. This narrative review summarizes contemporary AI-assisted approaches, with emphasis on convolutional neural networks (CNNs), generative adversarial networks (GANs), variational autoencoders (VAEs), and diffusion models, which enable probabilistic prediction of facial morphology while accounting for demographic variables such as sex, age, and population ancestry. Key challenges affecting reconstruction accuracy—including dataset limitations, population-specific variability, and algorithmic bias—are discussed, alongside quantitative validation methods and concerns regarding model transparency. Legal and ethical considerations, such as privacy, biometric data protection, and the need for explainable AI (XAI) frameworks, are highlighted. Future perspectives include hybrid expert–AI workflows, the development of globally representative datasets, and the integration of multimodal data sources, including DNA phenotyping, 3D morphometrics, and biomechanical modeling. These advances aim to create standardized, interpretable, and biologically informed frameworks that enable AI to support expert judgment and enhance the reliability of forensic facial reconstructions.

Introduction: Congenital adrenal hyperplasia (CAH), most commonly due to 21-hydroxylase deficiency, typically presents in the neonatal period with cortisol and aldosterone deficiency, and androgen excess. However, atypical manifestations may delay diagnosis and treatment. Case Presentation: We report a case of a two-day-old female neonate admitted with hematemesis. Imaging revealed a large right adrenal mass with features of hemorrhage and necrosis. Further evaluation confirmed classic CAH. Hormonal replacement therapy was initiated with favorable response. Discussion: Adrenal mass in a neonate is an uncommon presentation of CAH and necessitates differential diagnosis with adrenal hemorrhage or neoplasm. Early biochemical screening, including 17-hydroxyprogesterone measurement, is crucial. Prompt hormone replacement can prevent life-threatening complications and ensure normal development. Conclusion: This case highlights an unusual presentation of CAH and underscores the importance of considering endocrine etiologies in neonates with adrenal masses and gastrointestinal bleeding. Keywords: congenital adrenal hyperplasia neonate adrenal mass

Malignant ectomesenchymoma (MEM) is an uncommon and rapidly progressing malignant tumor affecting the nervous system or soft tissues, composed of both mesenchymal and neuroectodermal components. It is mostly found in the pelvic region, retroperitoneal area, and genitourinary system of pediatric patients. A 19-month-old child was hospitalized for an ultrasound and lab tests due to a painless nodular mass on the right forearm. The ultrasound showed a well-defined intramuscular lesion measuring 57 × 20 × 27 mm with a chaotic blood flow pattern, raising suspicion of a neoplastic condition. A biopsy confirmed ectomesenchymoma. The patient was scheduled for chemotherapy based on the CWS — VAIA III protocol and categorized as high-risk group (HRG); and staged as Group III according to the Intergroup Rhabdomyosarcoma Study classification (IRS III), with involvement of regional lymph nodes (N1). Diagnosis of MEM is challenging due to its rarity and variability, leading to prolonged treatment timelines. In the case analyzed, ultrasound showed malignant features, such as a subfascial position and a lesion over 5 cm, with irregular vascular patterns suggesting necrosis. Surgical intervention is the primary treatment, while chemotherapy and radiotherapy are generally avoided in children due to neurodevelopmental risks. Understanding MEM tumorigenesis may help identify better systemic treatments in the future. Keywords: malignant ectomesenchymoma pediatric oncology diagnostics

None. Keywords: brain metastases brain tumour radiotherapy whole brain radiotherapy WBRT

Small-cell lung carcinoma (SCLC) is one of the most aggressive and therapeutically challenging malignancies. It is characterised by rapid progression, early metastasis and frequent relapse. Despite considerable advances in molecular oncology, effective biomarkers for prognosis and treatment response remain elusive. In this review, we summarise and discuss recent evidence on microRNAs (miRNAs) as central regulators of SCLC biology and their potential clinical applications. A narrative review of the literature was conducted. Search of PubMed and Scopus databases identified 14 miRNAs, including miR-7-5p, miR-22-3p, miR-134, miR-181b, miR-200b, miR-335, miR-335-5p, miR-495, miR-24-3p, miR-30a-5p, miR-30a-3p, miR-100, miR-1 and miR-494, which are linked to tumour progression, therapy resistance and metastasis. These molecules influence several signalling cascades, including PI3K/Akt, Hippo, TGF-β, PARP1-mediated DNA repair and autophagy. Their abnormal expression correlates with patient outcome and may enable plasma- or exosome-based non-invasive monitoring. In particular, strategies that restore or inhibit miRNA activity using mimics or antagomiRs show promise in improving drug sensitivity and complementing current treatment options. Overall, emerging evidence supports the integration of miRNA profiling into precision oncology for SCLC, with the aim of refining diagnosis, risk assessment and therapeutic decision-making.